Hongzhen Wang | HealthTech and Wearables | Women Researcher Award

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Dr. Hongzhen Wang | HealthTech and Wearables | Women Researcher Award

Associate Professor at Zhejiang A&F University, China

Wang Hongzhen is an accomplished Associate Professor and Master’s Supervisor specializing in plant biochemistry and medicinal plant research. With over two decades of academic and research experience, she has focused on advancing the authenticity, classification, and cultivation of Anoectochilus roxburghii, a highly valued medicinal orchid. Her academic journey spans Shanxi University, Guizhou University, and a Ph.D. from Linnaeus University in Sweden, equipping her with a global research perspective. Currently serving at Zhejiang A&F University, she integrates traditional plant sciences with modern biotechnological tools, including hyperspectral imaging and machine learning, to address challenges in medicinal plant authenticity and health applications. Having authored more than 30 high-impact papers, led numerous provincial and national projects, and earned awards for her contributions, Wang’s research significantly contributes to the advancement of health-related technologies and the sustainable development of medicinal plant resources.

Professional Profile

Scopus

Education

Wang Hongzhen’s education reflects a solid foundation in biological sciences and plant biochemistry. She began her academic training at the College of Life Sciences, Shanxi University, where she acquired essential knowledge of genetics and plant physiology. She then pursued postgraduate studies at the Institute of Genetic Engineering and Molecular Biology, Guizhou University, focusing on genetic regulation and biochemical pathways in plants. To advance her expertise, she completed her doctoral studies at Linnaeus University, Sweden, where she conducted extensive research in plant biochemistry, molecular biology, and the physiological mechanisms underlying medicinal plants. Her education uniquely combines traditional Chinese medicine plant studies with modern molecular tools and international scientific methodologies. This broad educational background prepared her to address critical questions in plant-based healthcare and medicinal resource development. Through this journey, she gained the capacity to integrate advanced research technologies, including hyperspectral imaging and bioinformatics, into her research on medicinal plant authentication.

Experience

Wang Hongzhen has built a rich academic and research career that bridges plant biochemistry, medicinal plant cultivation, and health-related applications. She began her professional journey as a teacher at Zhejiang Forestry College, where she contributed to developing courses in biotechnology and plant sciences. After completing her Ph.D. in Sweden, she joined Zhejiang A&F University in, where she continues to serve in the Discipline of Chinese Medicine. Over her career, she has presided over or contributed to more than 14 national and provincial projects, including studies funded by the National Natural Science Foundation of China. Her project leadership includes topics such as germplasm quality evaluation, resistance mechanisms, and cultivation innovations for Anoectochilus roxburghii. Beyond academic teaching, she has actively collaborated in advancing agricultural biotechnology and integrating medicinal plant research with modern imaging and computational analysis. Her career illustrates a continuous progression toward interdisciplinary, impactful scientific contributions in HealthTech and plant sciences.

Research Focus

Wang Hongzhen’s research focuses on the intersection of plant biochemistry, computational imaging, and medicinal resource sustainability. Her primary work centers on Anoectochilus roxburghii, a rare and valuable medicinal orchid widely used in traditional medicine. She investigates quality evaluation of germplasm resources, development of high-yield and disease-resistant varieties, and protocorm-like body formation mechanisms for scalable cultivation. Recently, she has integrated hyperspectral imaging and machine learning to achieve small-sample authenticity identification and variety classification, bridging biotechnology with cutting-edge computational methods. This research ensures authenticity, prevents adulteration, and enhances traceability of medicinal plants in healthcare applications. Additionally, she has explored molecular mechanisms such as polyamine regulation, enzyme gene function, and stress resistance in medicinal species. Her work is not only fundamental for improving the pharmacological reliability of herbal resources but also future-oriented in connecting plant sciences with HealthTech innovations, including wearable biosensing and AI-based diagnostic tools.

Publication Top Note

Title: Small-Sample Authenticity Identification and Variety Classification of Anoectochilus roxburghii (Wall.) Lindl. Using Hyperspectral Imaging and Machine Learning
Authors: Wang Hongzhen.
Summary: The study combines hyperspectral imaging with machine learning to authenticate and classify A. roxburghii from small samples, offering a fast and reliable method to prevent adulteration in medicinal plants.

Conclusion

Wang Hongzhen’s research demonstrates a rare combination of depth in plant biochemistry and breadth in applying advanced computational tools such as hyperspectral imaging and machine learning to address real-world problems in medicinal plant science. Her contributions in germplasm evaluation, cultivation, and molecular regulation of Anoectochilus roxburghii are significant, impactful, and forward-looking. With further emphasis on interdisciplinary international collaboration and AI-driven translational outputs, she is highly suitable for the Women Researcher Award.

Mahsa Fadavighaffari | Neurorehabilitation | Best Researcher Award

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Ms. Mahsa Fadavighaffari | Neurorehabilitation | Best Researcher Award

Faculty member occupational therapy Instructor at Ahvaz Jundishapur University of Medical Sciences, Iran

Mahsa Fadavighaffari is an accomplished researcher and lecturer in occupational therapy, specializing in neurorehabilitation and geriatric rehabilitation. She serves as a faculty member at the Musculoskeletal Research Center, School of Rehabilitation Sciences, Ahvaz Jundishapur University of Medical Sciences. Her career has been marked by a strong integration of teaching, clinical practice, and research, focusing on rehabilitation strategies for individuals with neurological disorders and older adults with cognitive or motor impairments. Mahsa’s academic journey began with a Bachelor of Occupational Therapy at Shiraz University of Medical Sciences, followed by a Master’s in Occupational Therapy at Iran University of Medical Sciences. Her contributions include randomized clinical trials, psychometric validation of rehabilitation tools, and cross-cultural adaptation of assessment instruments, ensuring evidence-based practice for Iranian populations. With numerous peer-reviewed publications and presentations at national and international conferences, she has established herself as a promising voice in the global rehabilitation research community.

Professional Profile

Google Scholar | ORCID

Education

Mahsa Fadavighaffari pursued her Bachelor of Science in Occupational Therapy at Shiraz University of Medical Sciences, where she graduated with distinction. Her bachelor thesis explored the effects of Cawthorne and Cooksey exercises on balance and quality of life in elderly individuals, highlighting her early commitment to geriatric care. Building on this foundation, she completed her Master of Science in Occupational Therapy at Iran University of Medical Sciences. Her master thesis focused on the translation, reliability, and validation of the Persian version of the Patient-Rated Wrist Evaluation (PRWE) for patients with distal radius and scaphoid fractures. This work demonstrated her strong expertise in psychometric evaluation and evidence-based practice. Through her education, Mahsa combined clinical research with academic rigor, producing impactful findings that remain highly relevant in rehabilitation sciences. Her educational background reflects both scientific depth and a strong focus on practical applications of occupational therapy within diverse patient populations.

Experience 

Mahsa has accumulated extensive academic and clinical experience in occupational therapy and rehabilitation sciences. She has served as a faculty member and lecturer at Ahvaz Jundishapur University of Medical Sciences, teaching courses on neurorehabilitation, occupational therapy for neurological disorders, and geriatric care. She has supervised student internships in stroke rehabilitation centers and hospital-based clinical settings. Previously, she held a lecturer position at Shiraz University of Medical Sciences, where she guided internships in multiple sclerosis and spinal cord injury rehabilitation. Her clinical experience includes working at Tavanafza Private Clinic, Shahid Rajaei Hospital, and Noorafshar Hospital, where she treated patients with neurological disorders. She also contributed to geriatric rehabilitation at Shiraz School of Rehabilitation Sciences. Across academic and clinical settings, Mahsa has consistently integrated teaching, research, and therapy, fostering evidence-based interventions while mentoring students. Her dual role as educator and practitioner highlights her dedication to advancing occupational therapy practice.

Research Focus 

Mahsa Fadavighaffari’s research is centered on neurorehabilitation, psychometrics, and geriatric care. She focuses on developing and validating culturally adapted rehabilitation assessment tools, ensuring reliability and applicability in clinical practice. Her notable works include the Persian adaptation of the Patient-Rated Wrist Evaluation (PRWE) and the psychometric validation of the Falls Efficacy Scale for elderly populations in nursing homes. She has also contributed to clinical trials, such as evaluating Cawthorne and Cooksey exercises for balance and quality of life among older adults. More recently, her research extends to innovative therapies such as action observation training for multiple sclerosis patients, reflecting her forward-looking approach to neurological rehabilitation. Mahsa’s interdisciplinary scope includes musculoskeletal rehabilitation, behavioral assessment, and geriatric fall prevention, aligning clinical practice with research-driven solutions. Her focus on bridging evidence-based research with direct patient outcomes positions her as a promising leader in neurorehabilitation research and clinical translation.

Awards and Honors 

Mahsa has received several honors that underscore her academic excellence and professional contributions. At Shiraz University of Medical Sciences, she won multiple first-place awards at the “Celebration of Knowledge and Research of Distinguished Students” and the Shiraz University Alumni Association Festival. During her master’s program at Iran University of Medical Sciences, she ranked among the top students in occupational therapy. She earned recognition at the Shahid Motahari Festival for her innovative teamwork project in clinical education. She was also awarded a provincial prize for successfully implementing life skills education in schools. Beyond individual accolades, she has actively contributed to academic committees, including the executive and scientific committees of the National and International Clinical Movement Sciences Congresses. These recognitions reflect her blend of research impact, teaching excellence, and community engagement. Her awards highlight her growing influence in rehabilitation sciences and her capacity to translate research into meaningful clinical and educational practices.

Publication Top Notes

Title: Effect of Cawthorne and Cooksey Exercises on Balance and Quality of Life of 60 to 80 Year-Old Individuals in Shiraz: A Randomized Clinical Trial
Authors: AF Abarghuei, M Fadavi-Ghaffari, S Tousi, M Amini, AR Salehi
Journal: Medical Journal of the Islamic Republic of Iran.
Summary: This trial showed that Cawthorne and Cooksey exercises significantly improved balance and quality of life in elderly participants, offering a cost-effective fall-prevention method.

Title: Falls Efficacy Scale and Single Item Question: Screening Accuracy for Older Adults Residing in Nursing Homes
Authors: M Meimandi, M Fadavi-Ghaffari, G Taghizadeh, A Azad, L Lajevardi
Journal: Clinical Gerontologist.
Summary: The study validated simple tools for assessing fall risk in nursing home residents, proving effective for large-scale geriatric screening.

Title: Translation, Cultural Adaptation, Face and Content Validity of the Persian Version “Patient-Rated Wrist Evaluation” (PRWE-Persian) Questionnaire
Authors: M Fadavi-Ghaffari, A Azad, H Shariatzadeh, G Taghizadeh, S Aminizadeh
Journal: Journal of Modern Rehabilitation.
Summary: This research adapted and validated the PRWE into Persian, ensuring reliability for evaluating pain and disability in wrist injuries.

Title: The Psychometric Properties of Falls Efficacy Scale in the Elderly Iranian Residents of Nursing Homes
Authors: M Fadavi-Ghaffari, A Azad, M Meimandi, Z Arani-Kashani, H Ghorbanpoor
Journal: Iranian Rehabilitation Journal.
Summary: Confirmed the validity and reliability of the Falls Efficacy Scale in elderly Iranian nursing home residents, enhancing clinical use.

Title: The Psychometric Features of the Patient-Rated Wrist Evaluation in Iranians With Scaphoid or Distal Radius Fracture
Authors: M Fadavi-Ghaffari, A Azad, G Taghizadeh, N Nakhostin-Ansari, H Shariatzadeh, S Aminizadeh
Journal: Iranian Rehabilitation Journal.
Summary: Evaluated PRWE’s psychometric properties in fracture patients, confirming its reliability across musculoskeletal injuries.

Title: Comparison of Students’ Performance and Attitude Between Collaboration Testing and Written Examination of Ethics Course
Authors: R Mofateh, N Orakifar, N NooriMombeini, M Fadavighaffari
Journal: Future of Medical Education Journal.
Summary: Compared collaborative testing with traditional exams, finding that teamwork assessments improved engagement and learning.

Title: Effect of Zoledronic Acid and Vitamin E on Surgical–Induced Femoral Head Osteonecrosis in Rabbit
Authors: K Gharanizadeh, S Aminizadeh, AX Amir Darbandi, S Nadjafi, M Fadavighaffari, et al.
Journal: Archives of Bone and Joint Surgery.
Summary: Animal model study showing that combined therapy reduced osteonecrosis risk, suggesting potential for clinical application.

Conclusion

Mahsa Fadavighaffari’s research contributions, particularly in psychometric validation, geriatric rehabilitation, and evidence-based occupational therapy interventions, establish her as a promising and impactful researcher in rehabilitation sciences. Her blend of clinical, academic, and research expertise supports her suitability for recognition under the Best Researcher Award. With continued expansion of her international research visibility and adoption of emerging rehabilitation technologies, she is well-positioned to make even greater contributions to the field.

Peter Passias | Adult Spinal Deformity | Best Researcher Award

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Prof. Peter Passias | Adult Spinal Deformity | Best Researcher Award

Professor at Duke University, United States

Dr. Peter G. Passias is a leading academic spine surgeon and clinical researcher specializing in adult spinal deformity and cervical spine disorders. Based at NYU Langone Orthopedic Hospital, he has developed an international reputation for advancing surgical strategies that improve patient outcomes while reducing risks and healthcare costs. His career is marked by over 400 peer-reviewed publications, extensive participation in multicenter collaborative studies, and pioneering efforts to incorporate artificial intelligence and algorithmic frameworks into surgical planning. He serves on the editorial boards of top-tier journals including The Spine Journal and Journal of Neurosurgery: Spine, shaping the direction of global spine research. Beyond his clinical and research impact, Dr. Passias has contributed significantly to training the next generation of spine surgeons and researchers worldwide. His combination of leadership, innovation, and translational research places him at the forefront of adult spinal deformity care and scientific advancement.

Professional Profile

ORCID | Scopus

Education

Dr. Passias’ educational background reflects a rigorous combination of clinical training and academic development that underpins his research excellence. He completed his medical education and advanced residency in orthopedic surgery at Tufts University School of Medicine, followed by fellowship training in complex spinal surgery at the Massachusetts General Hospital/Harvard Medical School program. His education was augmented by continued scholarly training in biomechanics, surgical innovation, and translational science, equipping him with the expertise to approach spinal deformity from multiple perspectives. Over time, he has further enhanced his academic profile with advanced research engagements, including NIH-supported projects that integrate computational models, biomechanics, and biologics into spinal reconstruction. This combination of strong surgical foundation, research acumen, and exposure to multidisciplinary collaboration during his formative years laid the groundwork for his leadership role at NYU Langone and his international recognition as one of the foremost researchers in adult spinal deformity surgery.

Experience 

Dr. Passias currently serves as Professor of Orthopedic Surgery at NYU Langone Orthopedic Hospital. His professional experience includes leading complex adult spinal deformity surgeries, overseeing NIH- and industry-funded clinical trials, and mentoring research fellows and residents. Previously, he trained and practiced at premier institutions including Tufts Medical Center and Harvard-affiliated hospitals, gaining expertise in complex spine care. He has also held visiting professorships and delivered invited lectures internationally, reinforcing his global reputation. Beyond direct clinical practice, he has spearheaded multicenter research collaborations across North America and Europe, tackling challenges such as revision risk, perioperative complications, alignment optimization, and cost-effectiveness. Dr. Passias has combined academic leadership with clinical innovation, driving advancements in surgical planning, biologic therapies, and AI integration. His career reflects a balanced contribution across patient care, translational science, academic publishing, and mentorship, making him a leading authority in adult spinal deformity research.

Research Focus 

Dr. Passias’ research focuses on advancing surgical strategies and improving patient outcomes in adult spinal deformity and cervical deformity surgery. His work integrates biomechanics, artificial intelligence, predictive analytics, and biologics to address key challenges such as surgical alignment, cost-effectiveness, and revision risk. A core aspect of his research involves quantifying spinal parameters to develop patient-specific surgical planning models, including AI-driven decision support systems. He has pioneered multicenter studies evaluating outcomes, complications, and realignment goals across diverse populations, providing evidence that directly informs surgical guidelines. Recently, he has explored the role of biologics and regenerative strategies in enhancing fusion and recovery. His work also emphasizes healthcare value, using cost-utility frameworks to ensure that surgical innovations translate to sustainable clinical practice. Overall, his research trajectory is both innovative and translational, bridging the gap between advanced science and practical solutions that improve long-term outcomes for patients with complex spinal deformities.

Awards and Honors 

Dr. Passias’ distinguished career has been recognized through numerous national and international awards. He has received multiple nominations for the prestigious Whitecloud Award, honoring excellence in spinal deformity research, and the Hibbs Award from the Scoliosis Research Society for his innovative contributions. The North American Spine Society (NASS) has acknowledged his work with Value Awards for studies linking surgical strategies with improved cost-effectiveness. His role as principal investigator on NIH-funded research further underscores his standing as a leading academic surgeon-scientist. Beyond research accolades, he has been invited as a keynote speaker and visiting professor at international conferences, reflecting global recognition of his expertise. His editorial leadership on journals such as The Spine Journal and Artificial Intelligence Surgery highlights his influence in shaping the future of spine research. Collectively, these awards and honors demonstrate not only his personal achievement but also his enduring impact on advancing the field of adult spinal deformity.

Publication Top Notes

Title: Implementation of Artificial Intelligence (AI) in ASD Treatment
Journal: North American Spine Society Journal (NASSJ).
Contributors: Kyriakos D. Chatzis; Peter Tretiakov; Peter G. Passias
Summary: Showcases AI-driven predictive tools in adult spinal deformity treatment, supporting better alignment planning and lowering risks of complications.

Title: Proximal Junctional Kyphosis and Failure Prophylaxis Improves Cost Efficacy, While Maintaining Optimal Alignment, in Adult Spinal Deformity Surgery
Journal: Neurosurgery.
Contributors: Peter G. Passias; Oscar Krol; Tyler K. Williamson; Claudia Bennett-Caso; Justin S. Smith; Bassel Diebo; Virginie Lafage; Renaud Lafage; Breton Line; Alan H. Daniels et al.
Summary: Demonstrates that targeted prophylaxis reduces failure rates in adult spinal deformity surgery, achieving cost savings while preserving spinal alignment.

Title: Are we Getting Better at Achieving Optimal Lumbar Segmental Sagittal Alignment in Complex Adult Spine Deformity Surgery?
Journal: Spine.
Contributors: Peter G. Passias; Oluwatobi O. Onafowokan; Renaud Lafage; Justin Smith; Kojo D. Hamilton; Andrew J. Schoenfeld; Anthony Yung; Max R. Fisher; Bassel Diebo; Alan H. Daniels et al.
Summary: Evaluates progress in lumbar segmental alignment, highlighting improved surgical precision but ongoing challenges in complex cases.

Title: Cause and Effect of Revisions in Adult Spinal Deformity Surgery: A Multicenter Study on Outcomes Based on Etiology
Journal: The Spine Journal.
Contributors: Peter G. Passias; Pooja Dave; Justin S. Smith; Renaud Lafage; Oluwatobi O. Onafowokan; Peter Tretiakov; Jamshaid Mir; Breton Line; Bassel Diebo; Alan H. Daniels et al.
Summary: Multicenter study identifies underlying causes of revision surgeries and links them to outcome variability, guiding prevention strategies.

Title: Spinal Idiopathic Hypertrophic Pachymeningitis: A Systematic Review of Diagnostic Features, Clinical Management, and Surgical Outcomes
Journal: World Neurosurgery.
Contributors: Kishore Balasubramanian; Abdurrahman F. Kharbat; Francisco Call-Orellana; Sruthi Ranganathan; Romulo A. A. de Almeida; Kiran Sankarappan; Nitin Agrawal; Steven Hwang; Peter Passias; Angela Downes et al.
Summary: Reviews clinical and surgical management of this rare spinal condition, standardizing diagnostic markers and outcomes.

Title: Optimizing TLIF Approach Selection: An Algorithmic Framework with Illustrative Cases
Journal: Journal of Clinical Medicine.
Contributors: Alyssa M. Bartlett; Summer Shabana; Caroline C. Folz; Mounica Paturu; Christopher I. Shaffrey; Parastou Quist; Olumide Danisa; Khoi D. Than; Peter Passias; Muhammad M. Abd-El-Barr
Summary: Proposes an algorithmic framework for TLIF approach selection, improving decision-making in patient-specific spine surgery.

Title: Quantifying the Importance of Upper Cervical Extension Reserve in Adult Cervical Deformity Surgery and Its Impact on Baseline Presentation and Outcomes
Journal: Neurosurgery.
Contributors: Peter G. Passias; Jamshaid M. Mir; Andrew J. Schoenfeld; Anthony Yung; Justin S. Smith; Virginie Lafage; Renaud Lafage; Bassel Diebo; Alan H. Daniels; Breton G. Line et al.
Summary: Highlights the predictive value of cervical extension reserve for surgical outcomes, informing preoperative assessment.

Title: Have We Made Advancements in Optimizing Surgical Outcomes and Enhancing Recovery for Patients With High-Risk Adult Spinal Deformity Over Time?
Journal: Operative Neurosurgery.
Contributors: Peter G. Passias; Lara Passfall; Peter S. Tretiakov; Ankita Das; Oluwatobi O. Onafowokan; Justin S. Smith; Virginie Lafage; Renaud Lafage; Breton Line; Jeffrey Gum et al.
Summary: Longitudinal study showing improved recovery trends in high-risk deformity patients through refined surgical protocols.

Conclusion

Dr. Peter G. Passias is a highly suitable candidate for the Best Researcher Award. His exceptional research record, leadership in both clinical and academic settings, and pioneering integration of biomechanics, biologics, and AI into spinal deformity surgery underscore his position at the forefront of the field. Continued emphasis on investigator-driven trials, interdisciplinary applications, and policy engagement could further amplify his impact. Nonetheless, his sustained excellence and global recognition make him a strong and deserving nominee for this award.

Ruth Cristina Martín Sanz | Technology Scientists Innovations | Best Researcher Award

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Assist. Prof. Dr. Ruth Cristina Martín Sanz | Technology Scientists Innovations | Best Researcher Award

Assistant Professor at Universidad de Valladolid, Spain.

Ruth Cristina Martín Sanz is an Assistant Professor at the University of Valladolid, Spain, specializing in forest ecology, soil science, and climate resilience. She earned her Ph.D. in Conservation and Sustainable Use of Forest Systems (2018, Cum Laude, International Mention), advancing research on soil fertility and sustainable forest management. Over the past decade, she has built a reputation as a dynamic scholar, combining rigorous research with strong outreach activities. Her work focuses on adaptive traits in Mediterranean pines, forest-soil interactions, and fire ecology, positioning her at the intersection of climate change adaptation and ecosystem resilience. She has published extensively in Q1/D1 international journals, contributed to European and national projects, and received recognition for notable papers such as her award-winning publication in Forests. Beyond academia, she is deeply engaged in public science communication, mentoring, and editorial roles, making her a versatile and influential figure in her field.

Professional Profile

ORCID | Google Scholar

Education 

Ruth Cristina Martín Sanz obtained her Ph.D. in Conservation and Sustainable Use of Forest Systems from the University of Valladolid, graduating Cum Laude with International Mention. Her doctoral research integrated soil-forest interactions, adaptive forest genetics, and sustainable resource management, bridging ecology and applied forestry. Prior to her doctorate, she completed a master’s program recognized for academic excellence, focusing on forest productivity and ecological sustainability. During her studies, she undertook multiple international research stays, gaining experience at leading global institutions such as Charles Darwin University in Australia, the University of Georgia (USA), and the UK Centre for Ecology and Hydrology. These experiences enriched her methodological approaches, ranging from field ecology to advanced spectroscopy. She has also undertaken postdoctoral training through European and Spanish-funded research programs, ensuring continuity between theoretical ecology, applied soil sciences, and adaptive management of Mediterranean forest ecosystems.

Experience 

Ruth Cristina Martín Sanz currently serves as an Assistant Professor at the University of Valladolid. She has participated in national and European research projects addressing forest genetics, soil fertility, and the resilience of Mediterranean ecosystems to climate change. Notably, she has contributed to projects funded by the Spanish Ministry of Science, European Union, and regional excellence programs. She has worked in roles ranging from project researcher to project manager, contributing both scientific expertise and organizational leadership. Beyond her research, she has coordinated outreach initiatives such as Science in Action and Ciencia en el 109, merging academic science with community engagement. She has also served as Chief Editor of the Cuadernos de la Sociedad Española de Ciencias Forestales. Her experience blends academic rigor, applied project development, and science dissemination, ensuring wide-reaching impact across research, education, and public engagement.

Research Focus

Ruth Cristina Martín Sanz’s research focuses on forest science, evolutionary ecology, and soil-forest interactions in Mediterranean ecosystems. Her core work explores adaptive traits in pines, including serotiny, bark allocation, and fire-adaptive strategies, contributing to the evolutionary ecology of resilience under climate stress. She also investigates soil phosphorus dynamics, ecosystem services, and nutrient cycles, employing advanced analytical tools like ATR-FTIR spectroscopy and 31P-NMR. Her integrated approach connects above-ground tree traits with below-ground soil processes, offering holistic insights into forest productivity and sustainability. She emphasizes the trade-offs and trait integration in forest phenotypes, contributing to international discussions on sustainable use of genetic resources. Her work aligns with global challenges in climate change adaptation, biodiversity preservation, and sustainable forestry. By bridging genetics, ecology, and soil science, her research provides practical frameworks for forest management, conservation, and restoration, ensuring both scientific advancement and applied solutions.

Publication Top Notes

Title: Early dynamics of natural revegetation on roadcuts of the Salamanca province 
Authors: R.C. Martín-Sanz, B. Fernández-Santos, C. Martínez-Ruiz
Journal: Ecological Engineering.
Citations: 22
Summary: Analyzes vegetation recovery on roadcuts, showing soil–plant interactions drive early succession and providing restoration guidelines.

Title: Disentangling plasticity of serotiny, a key adaptive trait in a Mediterranean conifer
Authors: R.C. Martín-Sanz, L. Santos-del-Blanco, E. Notivol, M.R. Chambel, J. Climent
Journal: American Journal of Botany.
Citations: 33
Summary: Explores how plasticity shapes serotiny in Mediterranean pines, linking fire adaptation to environmental variability.

Title: Maintenance costs of serotiny in a variably serotinous pine: the role of water supply
Authors: R.C. Martín-Sanz, M. Callejas-Díaz, J. Tonnabel, J.M. Climent
Journal: PLoS ONE.
Citations: 23
Summary: Shows serotiny incurs water-related maintenance costs, highlighting adaptive trade-offs under drought conditions.

Title: How Does Environment Affect the Allocation to Bark in a Mediterranean Conifer?
Authors: R.C. Martín-Sanz, R. San-Martín, H. Poorter, A. Vázquez de la Cueva, J. Climent
Journal: Frontiers in Plant Science.
Citations: 19
Summary: Examines how environmental factors shape bark allocation, emphasizing its role in fire resistance and growth balance.

Title: Trade-offs and trait integration in tree phenotypes: consequences for the sustainable use of genetic resources
Authors: J. Climent, R. Alía, K. Karkkainen, C. Bastien, M. Benito-Garzon, L. Bouffier, R.C. Martín-Sanz, et al.
Journal: Current Forestry Reports.
Citations: 17
Summary: Discusses trait trade-offs and integration in trees, offering insights into sustainable forestry and genetic resource management.

Title: Influence of soil properties on P pools and its effect on forest productivity in Mediterranean calcareous soils
Authors: R.C. Martín-Sanz, V. Pando, T. Bueis, M.B. Turrión
Journal: Forests.
Citations: 8
Summary: Investigates phosphorus pools in Mediterranean soils, linking soil fertility with forest productivity and sustainability.

Title: Evolutionary ecology of fire-adaptive traits in a Mediterranean pine species
Authors: R.C. Martín-Sanz
Journal: Conference Contribution.
Citations: 2
Summary: Explores fire-adaptive traits in Mediterranean pines, emphasizing evolutionary drivers of serotiny and resilience.

Title: Characterization of soil phosphorus in different land use over calcareous soils by chemical extraction methods and 31P-NMR spectroscopy
Authors: R.C. Martín-Sanz, F. Lafuente, M.B. Turrión
Journal: Revista de Ciências Agrárias.
Citations: 1
Summary: Provides soil phosphorus characterization across land uses, advancing analytical methods for nutrient management.

Conclusion

Ruth Cristina Martín Sanz is a highly promising and impactful researcher whose work advances both scientific understanding and practical solutions in forest ecology, adaptive traits, and soil-forest interactions. Her balance of high-quality publications, research innovation, and commitment to science communication makes her a strong candidate for the Best Researcher Award. With further growth in citation impact, broader project leadership, and international recognition, she is poised to become a leading figure in sustainable forestry research and climate resilience.

Sima Rezvantalab | Neuroscience | Best Researcher Award

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Dr. Sima Rezvantalab | Neuroscience | Best Researcher Award

Assistant professor at Urmia University of Technology, Iran.

Dr. Sima Rezvantalab is a faculty member at Urmia University of Technology, Iran, with a strong interdisciplinary background in chemical engineering, nanomedicine, and computational neuroscience. Her academic journey began with a Master’s degree in Polymer Engineering at Sharif University of Technology, followed by a Ph.D. at Amirkabir University of Technology in collaboration with RWTH Aachen, Germany, where she focused on riboflavin-functionalized nanocarriers for drug delivery. Over the years, she has advanced research on PLGA nanoparticles, microfluidics, AI-driven nanomedicine, and novel biomaterials. She has authored influential publications, including the widely cited study on PLGA nanoparticles in cancer therapy, and has expanded her research to areas such as neurodegenerative disease modeling, β-amyloid targeting, and nanoscaffold design for tissue regeneration. Her work is notable for blending molecular simulations, machine learning, and experimental validation. As an emerging leader in neuroscience-related nanotechnology, she continues to pioneer innovations that bridge chemistry, biology, and computational science.

Professional Profile

Google Scholar | Scopus

Education 

Dr. Rezvantalab’s educational journey reflects depth in both engineering fundamentals and biomedical applications. She earned her Ph.D. in Chemical Engineering from Amirkabir University of Technology, Tehran, with a joint research collaboration at RWTH Aachen University, Germany, under the supervision of Prof. Fabian Kiessling and Prof. Mostafa Keshavarz Moraveji. Her dissertation explored microfluidic synthesis of riboflavin-functionalized nanocarriers, integrating targeted drug delivery and advanced characterization. Prior to her doctorate, she completed her Master of Science in Polymer Engineering at Sharif University of Technology, focusing on polypropylene production with broad molecular weight distribution, supervised by Prof. Ahmad Ramezani. Her strong foundation began with undergraduate studies in Chemical Engineering at the University of Mohaghegh Ardabili, where she consistently ranked among the top students. This rigorous educational background equipped her with a strong understanding of polymer chemistry, nanotechnology, and bioengineering, setting the stage for her impactful contributions to neuroscience, nanomedicine, and translational research.

Experience 

Dr. Rezvantalab has served as a faculty member at Urmia University of Technology, where she teaches advanced courses including Physical Chemistry of Polymers, Transport Phenomena in Polymer Systems, Advanced Thermodynamics, and Computational Methods in Chemical Engineering. Her academic career is marked by active involvement in both research and mentoring, contributing to the growth of young scientists in nanomedicine and computational neuroscience. Beyond teaching, she has collaborated internationally, publishing extensively with researchers from Germany, Finland, and other global institutions. Her expertise spans experimental nanocarrier design, AI-based predictive modeling, and molecular dynamics simulations. She has also presented her work at numerous international conferences, ranging from membrane science to environmental engineering, reflecting her interdisciplinary scope. Through her leadership and cross-disciplinary collaborations, Dr. Rezvantalab has advanced research at the intersection of polymer engineering, nanotechnology, and brain health applications, positioning herself as a driving force in the neuroscience research community.

Research Focus

Dr. Rezvantalab’s research is centered on nanomedicine for neurological and systemic diseases, with a strong emphasis on polymeric nanoparticles, targeted drug delivery, and AI-driven biomaterials design. Her work integrates computational molecular dynamics, machine learning, and experimental nanotechnology to develop intelligent drug delivery systems. A significant part of her contributions includes engineering PLGA-based nanoparticles for cancer and neurodegenerative disorders, investigating β-amyloid targeting frameworks for Alzheimer’s disease, and creating 3D-printed nanoscaffolds for tissue regeneration. She also explores microfluidics-based nanoparticle synthesis for precision medicine and artificial intelligence for predicting nanoparticle behaviors. Another research line includes environmental and biomedical membranes, applying nanomaterials to water purification and ion-selective separations. This multidisciplinary approach allows her to bridge neuroscience, computational biology, and material sciences, making her work highly relevant for translational medicine. Her ability to combine drug delivery platforms with neurobiological applications positions her as a leader in next-generation therapeutics at the nano-bio interface.

Awards and Honors 

Dr. Rezvantalab’s academic excellence has been consistently recognized through multiple honors. She was ranked first among Ph.D. students in Chemical Engineering at Amirkabir University of Technology and second in her B.Sc. class at the University of Mohaghegh Ardabili. She also achieved national distinction by ranking within the top 30 and 35 among more than 1000 participants in competitive entrance exams for graduate studies in Chemical Engineering and Biotechnology. Beyond academic rankings, her publications have been highlighted in top journals, including cover features in ACS Biomaterials Science & Engineering and ACS Omega, reflecting international recognition of her innovative contributions. She has delivered invited talks and presentations at prestigious conferences, advancing discussions on nanomedicine, environmental engineering, and neurotherapeutics. These honors underscore her strong academic foundation, research leadership, and growing influence in the global scientific community. Her achievements position her as a deserving recipient of awards that celebrate excellence in neuroscience-related innovation.

Publication Top Notes

Title: PLGA-based nanoparticles in cancer treatment
Authors: S. Rezvantalab, N.I. Drude, M.K. Moraveji, N. Güvener, E.K. Koons, Y. Shi, T. Lammers, F. Kiessling
Journal: Frontiers in Pharmacology.
Citations: 599
Summary: This highly cited review discusses PLGA nanoparticles as versatile, biocompatible carriers for cancer therapy. It highlights synthesis strategies, ligand targeting, and clinical translation, making it a cornerstone in nanomedicine.

Title: Microfluidic assisted synthesis of PLGA drug delivery systems
Authors: S. Rezvantalab, M.K. Moraveji
Journal: RSC Advances.
Citations: 151
Summary: This paper introduces microfluidics for controlled PLGA nanoparticle synthesis. It shows how micro-scale flow systems improve uniformity, reproducibility, and scalability in drug delivery.

Title: A molecular investigation of urea and creatinine removal in the wearable dialysis device using Two-Dimensional materials
Authors: R. Maleki, A.M. Jahromi, S. Mohaghegh, S. Rezvantalab, M. Khedri, L. Tayebi
Journal: Applied Surface Science.
Citations: 42
Summary: Using molecular dynamics, this work shows how 2D nanomaterials can adsorb toxins like urea and creatinine, paving the way for wearable dialysis technologies.

Title: 3D printing of complicated GelMA-coated Alginate/Tri-calcium silicate scaffold for accelerated bone regeneration
Authors: N. Beheshtizadeh, A. Farzin, S. Rezvantalab, Z. Pazhouhnia, et al.
Journal: International Journal of Biological Macromolecules.
Citations: 39
Summary: This study develops a hybrid GelMA-alginate/Tri-calcium silicate scaffold via 3D printing. The construct improves osteogenic activity and bone repair, with strong applications in regenerative medicine.

Title: Artificial intelligence deep exploration of influential parameters on physicochemical properties of curcumin‐loaded electrospun nanofibers
Authors: M. Khedri, N. Beheshtizadeh, M. Rostami, A. Sufali, S. Rezvantalab, M. Dahri, et al.
Journal: Advanced NanoBiomed Research.
Citations: 30
Summary: This work applies machine learning to optimize electrospun curcumin-loaded nanofibers. The approach identifies key parameters for drug release and mechanical performance.

Title: Engineering of 2D nanomaterials to trap and kill SARS-CoV-2: a new insight from multi-microsecond atomistic simulations
Authors: M. Khedri, R. Maleki, M. Dahri, M.M. Sadeghi, S. Rezvantalab, H.A. Santos, et al.
Journal: Drug Delivery and Translational Research.
Citations: 29
Summary: The paper uses simulations to show how 2D nanomaterials destabilize viral proteins, offering strategies for antiviral coatings and filters against COVID-19.

Title: Investigation of recent changes in Urmia salt lake
Authors: S. Rezvantalab, M.H. Amrollahi
Journal: International Journal of Chemical and Environmental Engineering.
Citations: 27
Summary: This environmental study analyzes the chemical and hydrological decline of Urmia Salt Lake, stressing sustainable water management.

Title: An insight into the role of riboflavin ligand in the self-assembly of PLGA nanoparticles – a molecular simulation and experimental approach
Authors: S. Rezvantalab, M.K. Moraveji, M. Khedri, R. Maleki
Journal: Soft Matter.
Citations: 24
Summary: This paper shows how riboflavin ligands influence PLGA nanoparticle assembly, enhancing stability and drug targeting. It combines simulations with experimental validation.

Conclusion

The candidate demonstrates outstanding scholarly impact, innovation, and interdisciplinary strength, making them highly suitable for the Best Researcher Award. Their contributions in polymeric nanoparticles, computational modeling, and AI-driven nanomedicine are of global relevance, addressing critical challenges in cancer therapy, regenerative medicine, and advanced materials. With further focus and translational emphasis, their research trajectory is poised to achieve even greater influence in both academic and applied domains.

Amin Najafi | Robotics and Automation | Best Researcher Award

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Mr. Amin Najafi | Robotics and Automation | Best Researcher Award

PhD candidate at University of Zanjan, Iran.

Amin Najafi is a researcher specializing in advanced fault-tolerant control, robotics, and intelligent transportation systems. His expertise lies in designing resilient control algorithms for UAVs, MAGLEV trains, and autonomous guidance systems. Through a strong portfolio of high-quality publications, Najafi has contributed significantly to enhancing the stability, safety, and performance of robotic systems operating under uncertain and fault-prone conditions. His work in adaptive barrier sliding mode control and finite-time stabilization has been widely recognized for bridging theoretical advancements with practical applications. Najafi’s research has appeared in leading journals, including IEEE Transactions on Transportation Electrification, Mathematics, ISA Transactions, and the Journal of Vibration and Control. Beyond research, he actively contributes to the scientific community through peer-review engagements across prestigious journals. His growing influence demonstrates his commitment to advancing robust, intelligent, and reliable autonomous systems, making him a promising candidate for recognition in robotics and automation research.

Professional Profile

Google Scholar | Scopus | ORCID

Education

Amin Najafi’s academic training has been grounded in control engineering, robotics, and automation. His education equipped him with advanced knowledge in nonlinear control, adaptive systems, and fault-tolerant design, laying a strong foundation for tackling complex challenges in autonomous platforms. Building on this foundation, Najafi engaged deeply with theories of stability, guidance, and fault diagnosis while also exploring practical aspects of UAVs and intelligent transportation. His progression through academic programs allowed him to develop both analytical rigor and applied research capabilities. The interdisciplinary nature of his training helped him connect mathematics, control theory, and engineering applications, which is reflected in his publications that combine theoretical robustness with engineering relevance. Najafi’s educational journey reflects a balance of theory and practice, giving him the ability to produce impactful work that speaks to both the academic community and the broader engineering industry in robotics and automation.

Experience

Amin Najafi has developed his career around solving critical problems in robotics, automation, and transportation electrification. His research experience includes designing innovative fault-tolerant controllers for quadrotor UAVs, advancing resilient strategies for MAGLEV train systems, and contributing to aerospace and defense-related guidance systems. His international collaborations with researchers such as S. Mobayen, A. Fekih, and L. Fridman demonstrate his ability to work within diverse, high-caliber teams. Najafi has also built strong credentials as a peer reviewer, having reviewed more than 60 manuscripts for prestigious journals including IEEE Transactions on Transportation Electrification, IEEE Access, and the Asian Journal of Control. This dual role as an author and reviewer highlights both his subject matter expertise and his standing in the global robotics and control community. Through his experience, he has consistently contributed to advancing autonomous and fault-resilient systems, ensuring his research holds both academic and applied significance.

Research Focus

Najafi’s research is anchored in fault-tolerant control, nonlinear dynamics, and resilient robotics. His primary focus lies in developing adaptive barrier sliding mode controllers, finite-time stabilization strategies, and robust diagnosis methods for actuator faults. UAVs represent a central application in his portfolio, where he has addressed actuator reliability, real-time guidance, and performance optimization under uncertain conditions. Beyond UAVs, he has extended his contributions to MAGLEV trains and interceptor-target systems, demonstrating the versatility of his control strategies. His work is characterized by integrating theoretical rigor, such as linear matrix inequality approaches, with real-world engineering challenges, making his contributions impactful across multiple domains. The broader vision of his research is to enable safe, intelligent, and adaptive robotic systems capable of operating in dynamic and fault-prone environments. By combining control theory with automation and robotics, Najafi continues to advance the frontiers of resilient and intelligent autonomous technologies.

Publication Top Notes

Title: Adaptive Barrier Fast Terminal Sliding Mode Actuator Fault-Tolerant Control Approach for Quadrotor UAVs
Authors: A. Najafi, M.T. Vu, S. Mobayen, J.H. Asad, A. Fekih
Journal: Mathematics.
Citations: 51
Summary: Proposes an adaptive barrier fast terminal sliding mode controller for quadrotor UAVs. Ensures finite-time stability, fault tolerance, and resilience against actuator faults with validated simulations.

Title: Design of Linear Matrix Inequality-Based Adaptive Barrier Global Sliding Mode Fault-Tolerant Control for Uncertain Systems with Faulty Actuators
Authors: K. Naseri, M.T. Vu, S. Mobayen, A. Najafi, A. Fekih
Journal: Mathematics.
Citations: 22
Summary: Introduces an LMI-based adaptive barrier global sliding mode controller. Provides robust stability and effective fault management in uncertain nonlinear systems.

Title: Robust Adaptive Fault-Tolerant Control for MAGLEV Train Systems: A Non-Singular Finite-Time Approach
Authors: A. Najafi, S. Mobayen, S.H. Rouhani, Z. Mokhtare, A. Jalilvand, L. Fridman, et al.
Journal: IEEE Transactions on Transportation Electrification.
Citations: 3
Summary: Develops a finite-time robust adaptive controller for MAGLEV trains. Enhances fault tolerance, passenger safety, and system robustness under disturbances.

Title: Multiple Actuator Fault Diagnosis Based on Parity Space for Quadrotor System
Authors: A. Najafi, D. Bustan
Journal: Journal of Aeronautical Engineering (JOAE).
Citations: 2
Summary: Presents a parity-space-based approach to detect and isolate multiple actuator faults in quadrotors, ensuring reliable UAV performance.

Title: Design of Adaptive Barrier Function-Based Backstepping Finite-Time Guidance Control for Interceptor-Target Systems
Authors: Z. Mokhtare, M.A. Sepestanki, S. Mobayen, A. Najafi, W. Assawinchaichote, et al.
Journal: Journal of Vibration and Control.
Citations: –
Summary: Proposes a backstepping control method with adaptive barrier functions for interceptor-target systems. Guarantees finite-time convergence and robust guidance under uncertainties.

Conclusion

Amin Najafi demonstrates strong potential and achievement in fault-tolerant control systems for UAVs and transportation applications, with impactful publications, innovative methodologies, and active engagement in peer review. While there is scope for growth in terms of citation impact and broader collaborations, his research contributions are highly relevant to the advancement of resilient and intelligent autonomous systems. He can be considered a suitable and promising candidate for the Best Researcher Award, particularly within the subject category of Control Systems, UAVs, and Intelligent Transportation.

Souleyman Hassan | Technology Scientists Innovations | Best Researcher Award

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Mr. Souleyman Hassan | Technology Scientists Innovations | Best Researcher Award

PhD student at University of N’Djamena in Chad.

Souleyman Hassan is a dedicated biochemist and PhD student at the University of N’Djamena, Chad, whose work focuses on discovering novel small molecules to combat malaria and related parasitic diseases. His research bridges traditional medicinal knowledge with modern computational and experimental approaches, such as bio-guided fractionation and high-throughput screening. He has collaborated with global pharmaceutical leaders including MMV, Pfizer, Merck, H3D, and Johnson & Johnson, contributing to the identification of potent antimalarial compounds, notably the picomolar pyrazole derivative MMV1794211. As an ambassador for SPARK Africa and an active member of ISSX Africa, he advocates for advancing research capacity across the continent. Souleyman has also co-founded EcoFast, reflecting his commitment to innovation and entrepreneurship. With support from the Bill & Melinda Gates Foundation, DAAD, and Grand Challenges Africa, his work exemplifies the integration of academic research, industrial collaboration, and social impact in the fight against malaria.

Professional Profile

ORCID

Education 

Souleyman Hassan is pursuing a PhD in Biochemistry at the University of N’Djamena, Chad. His doctoral research centers on malaria therapeutics, particularly the discovery and optimization of natural and synthetic molecules targeting resistant Plasmodium falciparum strains. He gained academic enrichment through the YaBiNaPA project (Yaoundé–Bielefeld Graduate School for Natural Products with Antiparasite and Antibacterial Activity), funded by DAAD, where he developed expertise in bio-guided fractionation, pharmacokinetic optimization, and parasite assays. His training also includes exposure to computational drug discovery and structure-based screening, providing him with a dual skillset bridging wet-lab and in silico research. Souleyman has benefited from workshops and collaborations with the University of Yaoundé I, the University of South Florida, and multiple pharmaceutical partners, where he strengthened his understanding of global health research pipelines. His educational journey reflects a strong commitment to integrating African research excellence with international scientific standards.

Experience 

Souleyman Hassan has gained diverse research and industrial experience through collaborations with international pharmaceutical companies and research institutions. His work with Medicines for Malaria Venture (MMV) provided hands-on experience in screening open-access compound libraries such as the COVID Box, Malaria Box, and Pathogens Box, evaluating their antiparasitic activity. His involvement in the Bill & Melinda Gates Foundation-funded project led to the discovery of highly potent antiplasmodial pyrazole derivatives, underscoring his contribution to frontline drug discovery efforts. Additionally, he has worked on plant-based drug leads, such as Drymaria cordata and Macaranga monandra, used traditionally against malaria. Souleyman is also engaged with community and academic organizations as a member of ISSX, SPARK Africa, and the Association of Health Sciences Researchers in Chad. His co-founding of EcoFast illustrates his ability to extend research innovations into entrepreneurial ventures, reflecting an applied dimension to his academic expertise.

Research Focus 

Souleyman Hassan’s research focuses on the biochemistry and pharmacology of antimalarial drug discovery. He integrates natural product isolation with computational methods to identify promising bioactive molecules and improve pharmacokinetics. His focus extends to high-throughput screening of both natural and synthetic libraries, enabling the rapid identification of potent leads such as MMV1794211, which showed picomolar-level activity against resistant Plasmodium falciparum. His research also explores the repurposing of existing molecules, reducing the cost and time of developing antiparasitic drugs. By combining indigenous plant knowledge, such as investigations into Terminalia ivorensis and Mitragyna inermis, with modern medicinal chemistry approaches, his work represents a fusion of traditional wisdom and cutting-edge science. This dual focus positions his research at the forefront of global health innovation, tackling neglected tropical diseases and contributing to the broader fight against drug resistance in malaria and other parasites.

Publication Top Notes

Title: Unveiling the antimalarial properties of Terminalia ivorensis stem bark aqueous extract
Journal: International Journal of Plant-Based Pharmaceuticals, April 2024. 
Summary: Validated traditional use of T. ivorensis with in vivo tests and docking studies, confirming strong antimalarial potential.

Title: Discovery of a picomolar antiplasmodial pyrazole derivative from MMV Global Health Priority Box
Journal: VeriXiv, October 16, 2024. 
Authors: Mariscal Brice Tchatat Tali; Darline Dize; Aubin Youbi Kamche; Boniface Pone Kamdem; Souleyman Hassan; et al.
Summary: Identified MMV1794211, a pyrazole derivative with exceptional potency (IC50 < 10 pM) against resistant Plasmodium falciparum.

Title: Bio-guided investigation of Mitragyna inermis unveils natural isolates with cross-activity against Plasmodium falciparum
Journal: Journal of Ethnopharmacology, August 7, 2025. 
Summary: Discovered compounds from M. inermis effective against both sensitive and multidrug-resistant malaria strains.

Title: Targeting the intra-erythrocytic life cycle of Plasmodium falciparum using Drymaria cordata and Macaranga monandra
Journal: Journal of Ethnopharmacology, January 2025.
Summary: Identified plant-based compounds disrupting parasite life cycle, providing new antimalarial drug leads.

Conclusion

Souleyman Hassan shows strong potential and suitability for the Best Researcher Award, particularly in the context of young, early-career scientists making impactful contributions to neglected tropical diseases research. His innovative use of open-access compound libraries, his integration of computational and experimental drug discovery, and his discovery of highly potent antiplasmodial derivatives all point to significant promise. With further consolidation through high-impact publications, translational applications, and expanded international collaborations, he is well on track to becoming a leading figure in the field of global health drug discovery.

Naveed Ahmed | Technology Scientists Innovations | Best Researcher Award

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Assist. Prof. Dr. Naveed Ahmed | Technology Scientists Innovations | Best Researcher Award

Assistant Professor at University of Tabuk in Saudi Arabia.

Dr. Naveed Ahmed is a distinguished scientist in Medical Microbiology whose research seamlessly blends laboratory science with clinical impact. Currently serving as Assistant Professor at the University of Tabuk, Saudi Arabia, he earned his Ph.D. from Universiti Sains Malaysia, where he was recognized for academic excellence and timely graduation. His work spans infectious disease diagnostics, antimicrobial resistance mechanisms, nanomedicine applications, and computational vaccine design. With over 46 Q1/Q2 publications, an H-index of 23, Dr. Ahmed has contributed to global health datasets and collaborative studies published in top-tier journals such as The Lancet. His innovations include patented laboratory protocols for microbial diagnostics and immune profiling. Known for his capacity to integrate molecular methods, bioinformatics, and translational science, Dr. Ahmed’s career reflects both depth of expertise and breadth of interdisciplinary collaboration, making him a prominent figure in the global fight against infectious diseases.

Professional Profile

Scopus | Google Scholar | ORCID

Education 

Dr. Ahmed holds a Doctor of Philosophy in Medical Microbiology from Universiti Sains Malaysia. His doctoral research, supported by competitive scholarships and awards, focused on molecular pathogenesis of Epstein–Barr Virus-associated cancers and immune checkpoint modulation. Prior to his Ph.D., he earned a Master of Science in Microbiology from the University of Central Punjab, Pakistan, where he developed expertise in bacteriology, immunology, and clinical diagnostics. His academic journey began with a BS (Honors) in Medical Laboratory Technology from the University of the Punjab, Pakistan, where he cultivated laboratory proficiency and research skills. Throughout his education, Dr. Ahmed actively engaged in research projects, academic presentations, and interdisciplinary collaborations, laying a foundation for high-impact publications and translational innovations. This diverse and rigorous educational background enables him to tackle complex biomedical challenges through both experimental and computational approaches.

Experience 

Dr. Ahmed’s professional trajectory blends academic teaching, laboratory management, and high-impact research. As Assistant Professor at the University of Tabuk, he teaches undergraduate and diploma-level courses, designs curricula, and fosters research collaborations with international teams. Previously, as a Graduate Research Assistant at Universiti Sains Malaysia, he managed grant-funded projects, secured ethical clearances, coordinated multi-institutional studies, and delivered results published in Q1/Q2 journals. Earlier roles as Laboratory Technologist at the Pakistan Kidney and Liver Institute and as Microbiology Supervisor at Chughtai Lab honed his expertise in clinical diagnostics, antimicrobial stewardship, biosafety, and ISO 15189 implementation. His teaching experience includes visiting lectureships at the University of Central Punjab and Imperial College of Business Studies. Across all roles, Dr. Ahmed has demonstrated leadership in laboratory innovation, research project management, and academic mentorship, ensuring his contributions extend from the bench to the classroom and into public health policy.

Research Focus 

Dr. Ahmed’s research focuses on the intersection of microbial pathogenesis, diagnostics, and therapeutic innovation. His investigations into antimicrobial resistance encompass genetic profiling of multidrug-resistant pathogens, elucidating resistance mechanisms induced by heavy metal exposure, and identifying virulence factors in hospital-acquired infections. In virology, he has advanced understanding of Epstein–Barr Virus latency genes and their role in immune checkpoint regulation, with implications for immunotherapy. He also explores nanomedicine, developing carbon-based nanomaterials and bioactive microbial compounds as diagnostic and therapeutic agents against cancer. His computational vaccine design projects leverage immunoinformatics to engineer multi-epitope vaccines targeting high-burden pathogens. Additionally, Dr. Ahmed contributes to global health surveillance datasets, applying systematic review and meta-analysis methods to epidemiological trends. His integrative approach combines molecular biology, bioinformatics, and translational science, aiming to bridge laboratory research with deployable healthcare solutions that address both infectious diseases and oncology in resource-diverse settings.

Awards & Honors 

Dr. Ahmed’s achievements are recognized through numerous competitive awards. He received the Graduate on Time Award (2024) and was nominated for the Best Ph.D. Thesis Award at Universiti Sains Malaysia. His presentation skills earned him 2nd place and the Young Investigator Award at the 9th Regional Conference on Molecular Medicine (2023). He twice won the prestigious Sanggar Sanjung Award (2021, 2022) for best publication-based research among USM students and was recognized as Best Oral Presenter in the departmental journal club (2022). Early in his career, he won Best Poster Presentation at the Annual Conference of Medical Microbiology and Infectious Diseases Society of Pakistan (2020). His research funding success includes grants from the Malaysian Ministry of Higher Education and industry collaborations with Medical Innovation Ventures. Combined with international fellowships and professional memberships, these honors underscore his sustained excellence in research, innovation, and scholarly dissemination.

Publication Top Notes

Title: The Microbial Sources of Bioactive Compounds: Potential Anticancer Therapeutic Options
Authors: Ahmed, N., Abusalah, M. A. H. A., Absar, M., Nasir, M. H., Farzand, A., Ahmad, I., Sohail, Z., Singh, K. K. B., Baig, A. A., & Yean, C. Y.
Journal: Nano Life, Vol. 15, 2430007.
Summary: Microbial metabolites from bacteria and fungi were isolated, characterized, and screened for anticancer activity. Several showed high selectivity and strong molecular target binding, offering sustainable leads for oncology drug development.

Title: Carbon-based Nanomaterials as Multifunctional Particles for Cancer Diagnosis and Treatment
Authors: Ahmed, N., Abusalah, M. A. H. A., Absar, M., Noor, M. S., Bukhari, B., Anjum, S. A., Singh, K. K. B., & Yean, C. Y.
Journal: Nano Life, Vol. 15, 2430005.
Summary: Graphene oxide, carbon nanotubes, and fullerenes were functionalized for targeted cancer imaging and therapy. They enabled enhanced tumor visualization, sustained drug release, and effective photothermal/photodynamic treatment, advancing nanotheranostic applications.

Title: Immunoinformatic Execution and Design of an Anti–Epstein–Barr Virus Vaccine with Multiple Epitopes Triggering Innate and Adaptive Immune Responses
Authors: Ahmed, N., Rabaan, A. A., Alwashmi, A. S., et al.
Journal: Microorganisms, Vol. 11, 2448.
Summary: A computational pipeline identified epitopes from EBV latent and lytic proteins, modeled their MHC binding, and simulated strong immune responses. Codon optimization suggested efficient bacterial expression, supporting rapid vaccine prototyping.

Title: Heavy Metal (Arsenic) Induced Antibiotic Resistance among Extended-Spectrum β-Lactamase (ESBL) Producing Bacteria of Nosocomial Origin
Authors: Ahmed, N., Tahir, K., Aslam, S., et al.
Journal: Pharmaceuticals, Vol. 15, 1426.
Summary: Arsenic in hospital effluents was linked to co-selection of plasmid-borne ESBL and arsenic resistance genes. This co-resistance highlights environmental drivers of antimicrobial resistance and the need for better wastewater control.

Title: Updates on Epstein–Barr Virus (EBV)-Associated Nasopharyngeal Carcinoma: Emphasis on the Latent Gene Products of EBV
Authors: Ahmed, N., Abusalah, M. A. H. A., Farzand, A., Absar, M., Yusof, N. Y., Rabaan, A. A., et al.
Journal: Medicina, Vol. 59, Issue 2.
Summary: This review outlines how EBV latent proteins like LMP1 and EBNA1 drive oncogenesis, evade immunity, and present therapeutic targets, emphasizing potential immunotherapy approaches for endemic regions.

Title: The Antimicrobial Efficacy against Selective Oral Microbes, Antioxidant Activity and Preliminary Phytochemical Screening of Zingiber officinale
Authors: Ahmed, N., Karobari, M. I., Yousaf, A., et al.
Journal: Infection and Drug Resistance,pp. 2773–2785.
Summary: Methanolic and aqueous ginger extracts inhibited oral pathogens and showed strong antioxidant activity linked to high phenolic and flavonoid content, supporting its use in oral health products.

Title: Antibiotic Resistance Profile in Relation to Virulence Genes fimH, hlyA and usp of Uropathogenic E. coli Isolates in Lahore, Pakistan
Authors: Ahmed, N., Zeshan, B., Naveed, M., et al.
Journal: Tropical Biomedicine, Vol. 36, pp. 559–568.
Summary:In clinical isolates, fimH and hlyA genes correlated with multidrug resistance. The findings stress the dual risk of resistance and virulence in urinary tract infections.

Conclusion

Dr. Naveed Ahmed possesses the academic excellence, research productivity, and global engagement expected of a Best Researcher Award recipient. His combination of high-impact publications, patents, conference recognition, and international collaborations demonstrates a clear commitment to advancing knowledge and innovation in medical microbiology and infectious diseases. With continued emphasis on leadership in large-scale research initiatives and translational impact, he is exceptionally well-suited for this award and has strong potential to contribute even more significantly to the scientific community in the future.

Axel Ransinangue | Computer Vision Systems | Best Academic Researcher Award

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Mr. Axel Ransinangue | Computer Vision Systems | Best Academic Researcher Award

PhD Candidate at University of Bordeaux in France.

Axel Ransinangue is a Ph.D. candidate at Bordeaux University, conducting research at the intersection of artificial intelligence and geosciences. Specializing in deep learning for carbonate reservoir characterization, his work integrates advanced image processing, computer vision, and geological interpretation. Axel’s expertise spans Python, MATLAB, TensorFlow, PyTorch, and geospatial tools such as QGIS and ArcGIS, enabling him to develop innovative solutions for analyzing thin section images, petrophysical properties, and hyperspectral datasets. Collaborating closely with TotalEnergies, he has designed semi-supervised classification systems, synthetic data generation pipelines, and multiscale segmentation techniques that bridge synthetic and real-world geological imagery. His contributions extend beyond research, actively engaging in scientific communication through conferences and leading discussions in the computer vision community. Driven by a passion for data-driven science, Axel’s work demonstrates both academic rigor and industrial relevance, making him a promising leader in AI-driven geoscience innovation.

Professional Profile

Google Scholar

Education

Axel holds a Bachelor’s degree in Earth Sciences and Environment with honors from Pau University, where he developed strong foundations in porous media analysis and image processing. He pursued a Master’s degree in Engineering from Bordeaux INP – ENSEGID, graduating with honors, and participated in an international exchange at Kyushu University, Japan, expanding his technical and cultural perspectives. Currently, Axel is a Ph.D. candidate in Artificial Intelligence, Sciences, and Environment at Bordeaux University, working in collaboration with TotalEnergies. His doctoral research integrates AI methodologies with carbonate petrography to enhance reservoir characterization. Under the supervision of experts in geology and computer science, he specializes in representation learning, domain adaptation, and synthetic data conditioning for geological imagery. This interdisciplinary education has equipped him with a unique blend of computational, analytical, and field-specific skills, positioning him at the forefront of AI applications in earth sciences.

Experience 

Axel’s professional experience blends academic research with industrial applications. At TotalEnergies, as a Geologist Intern, he analyzed carbonate thin sections, interpreting petrographic features for reservoir evaluation. Later, as a Data Scientist at AGEOS, he applied hyperspectral imaging to mineralogical quantification, developing regression models and calibrating point cloud acquisitions. His current role as a Ph.D. researcher involves designing deep learning systems for carbonate reservoir characterization, focusing on semi-supervised classification, conditional synthetic dataset generation, and multiscale image segmentation. He has also explored model explainability, ensuring AI decisions are interpretable for geological experts. Additionally, Axel has worked on integrating bi-modal classification models combining imagery with petrophysical data, as well as anomaly detection frameworks. His cross-domain expertise enables the translation of AI methodologies into practical tools for geoscience, creating value both in research and industrial operations.

Research Focus 

Axel’s research lies at the convergence of computer vision, deep learning, and carbonate petrography. His primary objective is to enhance geological image analysis through advanced AI-driven methodologies. Key areas include representation learning with invariance to interpretation biases, synthetic dataset generation conditioned on geological parameters, and domain adaptation to bridge synthetic and real-world imagery. He specializes in texture synthesis, pixel harmonization, and object packing strategies for creating high-quality training data when labeled datasets are scarce. His work also involves developing heuristics-based regularization techniques for improved segmentation accuracy and integrating statistical analysis to link image descriptors with petrophysical properties. By leveraging semi-supervised and multi-modal approaches, Axel aims to create robust and generalizable AI models that address challenges in reservoir characterization. This research not only advances geological sciences but also contributes to broader AI applications in image-based data interpretation across environmental and industrial domains.

Publication Top Notes

Title: SynSection: Sedimentology-driven data generation for deep learning applications in carbonate petrography
Authors: A. Ransinangue, R. Labourdette, E. Houzay, S. Guillon, R. Bourillot, et al.
Journal: Marine and Petroleum Geology, Article ID 107490.
Summary: The study presents SynSection, a framework for generating synthetic carbonate thin section images based on sedimentological parameters. Combining texture synthesis, object packing, and pixel harmonization, it produces realistic datasets to train deep learning models when labeled geological data is scarce. Demonstrated improvements in image classification and segmentation highlight its potential for reservoir characterization and data-driven petrography.

Conclusion

Axel Ransinangue presents a compelling case for recognition as a Best Academic Researcher. The work combines cutting-edge AI methodologies with domain-specific geological expertise, producing research that is both academically valuable and industrially applicable. With ongoing expansion of publication output and interdisciplinary collaborations, the candidate has strong potential to emerge as a leading figure in AI-driven geoscience research. Their contributions already reflect a blend of innovation, rigor, and practical relevance that aligns well with the award’s intent.

Le Xuan-Bach | Advanced Simulation Techniques | Best Researcher Award

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Dr. Le Xuan-Bach | Advanced Simulation Techniques | Best Researcher Award

Postdoctoral at Seoul National University of Science and Technology in South Korea.

Le Xuan Bach is a leading researcher in advanced semiconductor packaging, specializing in fracture mechanics, thermo-mechanical reliability, and structural optimization. Currently serving as a Postdoctoral Researcher at the MEMS and Packaging System Lab, Seoul National University of Science and Technology, he has led multiple high-value, government-funded projects in Korea. His work combines deep theoretical insight with industrial application, focusing on preventing structural failures in semiconductor devices through cutting-edge simulation and optimization techniques. Dr. Bach’s research spans advanced packaging materials, hybrid bonding processes, and glass interposer technologies, addressing critical challenges in electronics manufacturing. His strong publication record in top-tier journals, combined with presentations at major international conferences, underscores his influence in the microelectronics community. With a forward-looking vision for integrating AI-based simulation methods into semiconductor reliability assessment, Dr. Bach continues to shape the future of microelectronics design and manufacturing through innovation, precision, and impactful collaborations.

Professional Profile

Google Scholar | Scopus

Education 

Le Xuan Bach earned his Ph.D. in Nano IT Design Fusion from Seoul National University of Science and Technology, where his dissertation focused on “Assessment and Prevention of Crack Formation in 2.5D Glass Interposer and Hybrid Bonding Structure.” His doctoral research integrated advanced finite element modeling, fracture mechanics, and thermo-mechanical simulations to tackle industrially significant packaging challenges. He previously obtained a Master of Science in Mechanical Engineering from Hanoi University of Science and Technology, completing a thesis on actuator properties of two-dimensional materials for robotic applications. His undergraduate studies in Mechanical Engineering at the same institution explored low-dimensional materials for artificial muscles. This academic progression reflects a strong foundation in mechanical systems, materials science, and computational simulation, enabling him to bridge fundamental research with real-world semiconductor reliability solutions. Each stage of his education has been characterized by innovation, interdisciplinary integration, and application-driven outcomes, forming the backbone of his current expertise.

Experience 

Le Xuan Bach’s professional journey blends academic research with industry-driven problem-solving. Currently, he is a Postdoctoral Researcher at Seoul National University of Science and Technology, specializing in structural and thermal analysis for advanced semiconductor packaging. Previously, he was a Research Student at the International Institute for Computational Science and Engineering in Vietnam, focusing on nanomechanics and stability analysis of 2D materials. His industry roles include collaborating with Maxflow Technology Vietnam on lifetime prediction and structural optimization, and working in product development at Showa Auto Parts Vietnam (2017–2018), where he contributed to mold design and flow simulation. He has served as Principal Researcher on multiple Korean national projects, overseeing large-scale grants for semiconductor reliability enhancement, laser debonding processes, and next-generation interposer development. His career reflects a rare balance between deep scientific inquiry and practical engineering solutions, with measurable impacts on microelectronics manufacturing efficiency and reliability.

Research Focus 

Le Xuan Bach’s research centers on advanced simulation techniques for semiconductor reliability, combining numerical analysis, finite element modeling, and optimization strategies to solve complex manufacturing challenges. His primary focus includes hybrid bonding reliability, prevention of crack formation in 2.5D/3D packaging, warpage-induced stress mitigation, and glass interposer structural integrity. He develops computational models that simulate thermo-mechanical and structural behaviors, enabling predictive lifetime assessment of microelectronic devices. His work extends to vibration analysis for gyroscope sensors, selective EMI shielding technologies, and optimization of laser-assisted bonding processes. Leveraging tools like ANSYS, ABAQUS, and COMSOL, Dr. Bach integrates simulation-driven design into industrial-scale production, improving both performance and durability. His forward vision includes incorporating AI and machine learning into simulation workflows, enabling adaptive, data-driven semiconductor packaging solutions that reduce failure rates, enhance manufacturability, and accelerate technology adoption in emerging electronics and IoT devices.

Publication Top Notes

Title: Assessment of the Risk of Crack Formation at a Hybrid Bonding Interface Using Numerical Analysis
Authors: Le, X. B., & Choa, S. H.
Summary: This study uses advanced finite element modeling to predict crack formation in hybrid bonding interfaces, a key challenge in next-generation semiconductor packaging. The simulation framework captures thermo-mechanical stress distributions with high precision, enabling proactive bonding parameter adjustments. This validated numerical approach reduces costly production failures and supports large-scale manufacturing reliability.

Title: A Comprehensive Numerical Analysis for Preventing Cracks in 2.5D Glass Interposer
Authors: Le, X. B., & Choa, S. H.
Summary: Focused on 2.5D packaging, this paper develops a simulation-driven strategy to predict and mitigate cracking in glass interposers. Through modeling complex temperature and stress cycles, it presents optimized annealing and structural designs that enhance stability and yield in semiconductor production.

Title: Mechanical Reliability Assessment of a Flexible Package Fabricated Using Laser-Assisted Bonding
Authors: Le, X. L., Le, X. B., Hwangbo, Y., Joo, J., Choi, G. M., Eom, Y. S., … & Choa, S. H.
Summary: This work assesses the reliability of flexible semiconductor packages fabricated with laser-assisted bonding. Using multiphysics simulations, it evaluates deformation and interfacial stresses, offering design guidelines to improve durability in wearable and foldable electronics.

Title: Electromechanical Properties of Monolayer Sn-Dichalcogenides
Authors: Bach, L. X., Van Thanh, V., Van Bao, H., Van Truong, D., & Hung, N. T.
Summary: Explores electromechanical properties of monolayer tin dichalcogenides using density functional theory. The results show strain-dependent behavior critical for NEMS applications.

Title: Turning Electronic and Optical Properties of Monolayer Janus Sn-Dichalcogenides by Biaxial Strain
Authors: Van Thanh, V., Dung, N. T., Bach, L. X., Van Truong, D., & Hung, N. T.
Summary: Investigates how biaxial strain alters the electronic and optical characteristics of Janus Sn-dichalcogenides. The study provides simulation-based design pathways for tunable optoelectronics.

Title: Strain Effects on Electronic and Optical Properties of Monolayer Mo-Dichalcogenides
Authors: Van Vuong, T., Nguyen, T. D., Le, X. B., Van, L. G., Van, B. H., Do Wang, T., & Tuan, H. N. 
Summary: Applies computational mechanics to analyze strain impacts on molybdenum dichalcogenide monolayers, revealing tunable band structures and optical absorption profiles for flexible electronics.

Conclusion

Le Xuan Bach presents a compelling case for recognition as a Best Researcher Award recipient. His leadership in high-value projects, consistent publication record, and direct contributions to advancing semiconductor packaging technologies underscore his standing as an accomplished and innovative researcher. With strategic expansion into more interdisciplinary and translational research avenues, his influence and impact are poised to grow even further, making him a highly deserving nominee for the award.