Rakesh Rajendran | Optimization Algorithms | Research Excellence Award

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Dr. Rakesh Rajendran | Optimization Algorithms | Research Excellence Award

Regenesys Institute of Management | India

Dr. Rakesh Rajendran, affiliated with the Department of Information Science and Technology, Chennai, India, is a distinguished researcher in the domain of cybersecurity and network resource management. With a focused expertise in denial-of-service (DoS) attack mitigation and resource usage tracking, Dr. Rakesh has contributed significantly to the advancement of secure computing systems. His scholarly output includes 10 peer-reviewed publications, collectively cited 107 times and 5 h-index,  reflecting a growing recognition within the global research community. Collaborating with 29 co-authors across diverse institutions, he has fostered interdisciplinary engagement, enhancing both theoretical insights and practical applications. Notably, his work addresses critical challenges in safeguarding digital infrastructures, underscoring a tangible societal impact by informing resilient cybersecurity practices. His research trajectory demonstrates a commitment to innovative, high-quality scholarship with relevance to both academic and industrial domains, positioning him as a recognized contributor to the advancement of information security and technological reliability worldwide.

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Top 5 Featured Publications

Saeid Barshandeh | Optimization | Best Researcher Award

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Dr. Saeid Barshandeh | Optimization | Best Researcher Award

Instructor-Researcher | Afagh Higher Education Institute | Iran

Dr. Saeid Barshandeh is a computational intelligence researcher specializing in metaheuristic optimization, machine learning, and advanced algorithm design, with a research portfolio comprising 14 scientific publications, 12 h-index and over 885 citations. His work focuses on developing innovative, nature-inspired optimization techniques capable of addressing complex, nonlinear problems prevalent in engineering, data science, and industrial systems. A key achievement is the development of the Puma Optimizer (PO), a novel metaheuristic algorithm that has rapidly gained global academic attention and demonstrates his expertise in algorithmic modeling, performance tuning, and machine-learning integration. His research activities are enriched by collaborations with more than 30 co-authors, reflecting active engagement in interdisciplinary networks spanning intelligent systems, evolutionary computation, and data-driven decision-making. Collectively, his contributions enhance the efficiency, scalability, and applicability of optimization methodologies across diverse domains such as energy management, automation, predictive analytics, and industrial process optimization. Through impactful publications and growing scholarly influence, Dr. Barshandeh advances the theoretical and practical foundations of intelligent optimization, contributing to technological innovation and the broader scientific community.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Abdollahzadeh, B., Khodadadi, N., Barshandeh, S., Trojovský, P., & … (2024). Puma optimizer (PO): A novel metaheuristic optimization algorithm and its application in machine learning. Cluster Computing, 27(4), 5235–5283.
Cited by: 661

2. Barshandeh, S., & Haghzadeh, M. (2021). A new hybrid chaotic atom search optimization based on tree-seed algorithm and Levy flight for solving optimization problems. Engineering with Computers, 37(4), 3079–3122.
Cited by: 129

3. Gharehchopogh, F. S., Abdollahzadeh, B., Barshandeh, S., & Arasteh, B. (2023). A multi-objective mutation-based dynamic Harris Hawks optimization for botnet detection in IoT. Internet of Things, 24, 100952.
Cited by: 128

4. Gharehchopogh, F. S., Nadimi-Shahraki, M. H., Barshandeh, S., & … (2023). Cqffa: A chaotic quasi-oppositional farmland fertility algorithm for solving engineering optimization problems. Journal of Bionic Engineering, 20(1), 158–183.
Cited by: 89

5. Barshandeh, S., Piri, F., & Sangani, S. R. (2022). HMPA: An innovative hybrid multi-population algorithm based on artificial ecosystem-based and Harris Hawks optimization algorithms for engineering problems. Engineering with Computers, 38(2), 1581–1625.
Cited by: 78

Dr. Barshandeh’s research advances the science of optimization by providing robust, efficient algorithms that strengthen machine-learning performance and industrial decision systems. His work contributes to global technological innovation, enabling smarter, more adaptive solutions for complex societal and engineering challenges.

Hao-Ting Lin | Feature-Driven Optimization | Best Researcher Award

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Assoc Prof. Dr. Hao-Ting Lin | Feature-Driven Optimization | Best Researcher Award

Associate Professor | National Chung Hsing University | Taiwan

Dr. Hao-Ting Lin is an Associate Professor at National Chung Hsing University specializing in robotics, control systems, and bio-industrial mechatronics engineering, with a strong focus on automation, intelligent systems, and sustainable agricultural technologies. He holds advanced degrees in mechanical and control engineering and has developed expertise in the design and integration of robotic mechanisms, sensor-based control, and pneumatic power systems for poultry and agricultural applications. His professional experience includes leading over 30 completed and several ongoing research and consultancy projects, authoring 20 peer-reviewed journal papers, and publishing a book chapter on smart agricultural technologies. Dr. Lin’s research focuses on IoT-enabled humane poultry slaughtering systems, deep learning-based chicken image recognition, precision pneumatic seeders, energy-efficient control strategies for wastewater and agricultural machinery, and robotic sorting systems. He has been granted 12 patents covering innovations in pneumatic automation, exoskeleton systems, aquaculture water quality management, and intelligent sewing and seeding devices. Dr. Lin’s contributions integrate control theory, mechatronics, artificial intelligence, and real-time systems to advance productivity, animal welfare, and sustainability in agriculture and industry. His scholarly impact is reflected in 170 citations by 161 documents, 20 published documents, and an h-index of 6.

Profile: Scopus | ORCID

Featured Publications

1. Lin H.T.*, Suhendra, Development and Implementation of an IoT-Enabled Smart Poultry Slaughtering System Using Dynamic Object Tracking and Recognition. Sensors, 2025, 25(16), 5028.

2. Chen H.C., Rohman Y.F., Ashlah M.B., Lin H.T., Sean W.Y.*, Electrification of Agricultural Machinery: One Design Case of a 4 kW Air Compressor. Energies, 2024, 17(15), 3647.

3. Lin H.T.*, Lee Y.H., Implementing a Precision Pneumatic Plug Tray Seeder with High Seeding Rates for Brassicaceae Seeds via Real-Time Trajectory Tracking Control. Actuators, 2023, 12(9), 340.

4. Liu H.W., Chen C.H., Tsai Y.C., Hsieh K.W., Lin H.T.*, Identifying Images of Dead Chickens with a Chicken Removal System Integrated with a Deep Learning Algorithm. Sensors, 2021, 21(11), 3579.

5. Lin H.T.*, A Novel Real-Time Path Servo Control of a Hardware-in-the-Loop for a Large-Stroke Asymmetric Rod-Less Pneumatic System under Variable Loads. Sensors, 2017, 17(6), 1283.