Abhilash Kancharla | Deep Learning | Editorial Board Member

Published on by Technology Scientists

Dr. Abhilash Kancharla | Deep Learning | Editorial Board Member

The University of Tampa | United States

Dr. Abhilash Kancharla is a researcher at the University of Tampa specializing in advanced computing and next-generation digital technologies, with expertise in edge computing, 6G networks, blockchain-based security and privacy, quantum machine learning, neural-inspired algorithms, and computational modeling of nanomaterials. He has published 23 peer-reviewed research articles, which have received 50 citations, and holds an h-index of 4, reflecting consistent academic impact in emerging interdisciplinary fields. His work is particularly notable for integrating intelligent learning models with secure communication architectures for future wireless networks, as well as applying computational intelligence to the analysis of self-healing materials. Through collaborations with 14 co-authors, he actively contributes to international research networks, fostering cross-disciplinary knowledge exchange. The broader social and technological impact of his research supports the development of secure, intelligent, and sustainable digital infrastructures, with relevance to future communication systems, smart technologies, and advanced material design.

Citation Metrics (Scopus)

50
40
30
20
10
0

Citations

50

Documents

23

h-index

4

Citations

Documents

h-index


View Scopus Profile
 View ORCID Profile
 View Google Scholar Profile

Top 5 Featured Publications

Mahmoud Iskandarani | AI | Editorial Board Member

Published on by Technology Scientists

Prof. Mahmoud Iskandarani | AI | Editorial Board Member

Professor | Al-Ahliyya Amman University | Jordan

Prof. Mahmoud Zaki Iskandarani’s research focuses on advancing wireless communication systems with specialization in wireless sensor networks (WSNs), intelligent reflecting surfaces (IRS), robotic communication platforms, adaptive beamforming techniques, and electromagnetic field modeling. With 84 publications, 167 citations, 5 h-index his scholarly output reflects sustained productivity and growing global recognition. His recent works address energy-efficient communication for robotic WSNs, SINR enhancement through adaptive IRS design, hybrid beamforming using Gaussian interpolation, and analytical–numerical modeling supported by neural predictors, demonstrating strong integration of computational intelligence with communication engineering. He has also contributed to transportation and mobility research through studies on BRT system impacts on congestion and safety, highlighting his capacity for multidisciplinary problem-solving. Collaborating with 11 co-authors across diverse domains, he publishes in reputable international journals such as IEEE Access, Journal of Communications, Journal of Robotics, and Cogent Engineering, reinforcing the breadth and relevance of his contributions. Collectively, his research advances theoretical models and practical frameworks that improve spectral efficiency, path-loss prediction accuracy, energy optimization, and network reliability in emerging 6G-oriented and autonomous systems, generating technological and societal value across communication, robotics, and smart mobility sectors.

Profiles: Scopus | ORCID | Google Scholar

Featured Publications

1. Gardner, J. W., Iskandarani, M. Z., & Bott, B. (1992). Effect of electrode geometry on gas sensitivity of lead phthalocyanine thin films. Sensors and Actuators B: Chemical, 9(2), 133–142.

Cited by: 63

2. Iskandarani, M. Z. (2008). Effect of information and communication technologies (ICT) on non-industrial countries—Digital divide model. Journal of Computer Science, 4(4), 315.

Cited by: 41

3. Shilbayeh, N. F., & Iskandarani, M. Z. (2004). Quality control of coffee using an electronic nose system. American Journal of Applied Sciences, 1(2), 129–135.

Cited by: 41

4. Iskandarani, M. Z. (2025). Effect of Intelligent Reflecting Surface on WSN Communication with Access Points Configuration. IEEE Access, 13, 13380–13394.

Cited by: 29

5. Iskandarani, M. Z. (2025). Energy and path loss analysis of wireless sensor networks on a robotic body (WS Robotic). Bulletin of Electrical Engineering and Informatics, 14(3), 1794–1807.

Cited by: 25

Prof. Mahmoud Zaki Iskandarani’s work advances the performance, adaptability, and intelligence of wireless communication systems, contributing to the foundations of future 6G networks and autonomous robotic platforms. His research supports societal and industrial innovation by enabling more efficient connectivity, improved mobility systems, and smarter technological infrastructures worldwide.

Chao Li | Machine Learning | Best Researcher Award

Published on by Technology Scientists

Assoc. Prof. Dr. Chao Li | Machine Learning | Best Researcher Award

Department Chair | Chengdu University of Technology | China

Assoc. Prof. Dr. Chao Li of Chengdu University of Technology is an expert in geophysical signal processing, seismic data reconstruction, and intelligent subsurface imaging, with a focus on integrating machine learning and advanced computational techniques into geoscience applications. He has authored 31 peer-reviewed publications cited 425 times, reflecting a strong research impact and an h-index of 12. His work includes the development of Generative Adversarial Networks for seismic reconstruction, non-subsampled contourlet transforms for low-amplitude structure detection, and hybrid neural architectures for source deblending, addressing critical challenges in exploration geophysics and subsurface data interpretation. Collaborating with over 50 co-authors, Dr. Li demonstrates a commitment to interdisciplinary and international research, bridging academia and industry. His contributions enhance the accuracy, efficiency, and sustainability of seismic exploration, providing tools for more reliable resource evaluation and environmental monitoring. By combining computational intelligence with applied geophysics, Dr. Li’s research promotes innovation in energy exploration, environmental stewardship, and global geoscience advancement, making significant scientific, industrial, and societal impacts.

Profile: Scopus

Featured Publications

1. Ke, C.-F., Zu, S.-H., Cao, J.-X., Jiang, X.-D., Li, C., & Liu, X.-Y. (2024). A hybrid WUDT‑NAFnet for simultaneous source data deblending. Petroleum Science, 21(3), 1649‑1659.
Cited by: 1

2. Low‑amplitude structure recognition method based on non‑subsampled contourlet transform. Petroleum Science.(2024)
Cited by: 1

3. Seismic Data Reconstruction via Least‑Squares Generative Adversarial Networks With Inverse Interpolation. IEEE Transactions on Geoscience and Remote Sensing.(2025)
Cited by: 1

Assoc. Prof. Dr. Chao Li’s pioneering work at the interface of geophysics and artificial intelligence is reshaping the future of seismic data interpretation, enabling smarter, data-driven exploration. His vision emphasizes leveraging AI-powered geoscience solutions to advance sustainable resource utilization and strengthen global resilience in energy and environmental systems.

Minoru Sasaki | Artificial Intelligence | Best Researcher Award

Published on by Technology Scientists

Prof. Dr. Minoru Sasaki | Artificial Intelligence | Best Researcher Award

Organizing Committee | Gifu University | Japan

Prof. Dr. Minoru Sasaki, a distinguished Emeritus Professor at Gifu University, has made significant contributions to the fields of mechanical engineering, control systems, and mechatronics throughout his academic and professional career. With a Ph.D. in Mechanical Engineering from Tohoku University (1985), he has held various academic positions in Japan and internationally, including visiting professorships at UCLA, Georgia Institute of Technology, and King Mongkut’s University of Technology Thonburi. He has also served in numerous leadership roles at Gifu University, such as Department Chair, Assistant President, and Director of the Career Center. His professional affiliations include IEEE Life Senior Member, ASME, JSME, SICE (Fellow), RSJ, JSASS, and others. He has actively contributed to global academic and research communities through editorial roles in prestigious journals and program committees of international conferences. His involvement extends to advisory roles and leadership positions within key engineering societies in Japan and abroad. A prolific researcher, Dr. Sasaki has authored 202 publications, which have been cited by 966, reflecting a strong academic impact with an h-index of 14. These metrics highlight the depth and relevance of his research in intelligent mechanical systems and applied electromagnetics.

Profiles: Scopus | Google Scholar | ORCID

Featured Publications

1. Taheri, S. M., Matsushita, K., & Sasaki, M. (2017). Virtual reality driving simulation for measuring driver behavior and characteristics. Journal of Transportation Technologies, 7(02), 123.
Cited by 84.

2. Takayama, K., & Sasaki, M. (1983). Effects of radius of curvature and initial angle on the shock transition over concave and convex walls. Report of the Institute of High Speed Mechanics, 46, 1–30.
Cited by 66.

3. Yoshida, T., Sasaki, M., Ikeda, K., Mochizuki, M., Nogami, Y., & Inokuchi, K. (2002). Prediction of coal liquefaction reactivity by solid state 13C NMR spectral data. Fuel, 81(11-12), 1533–1539.
Cited by 64.

4. Endo, T., Sasaki, M., Matsuno, F., & Jia, Y. (2016). Contact-force control of a flexible Timoshenko arm in rigid/soft environment. IEEE Transactions on Automatic Control, 62(5), 2546–2553.
Cited by 61.

5. Takeda, K., Sasaki, M., Kieda, N., Katayama, K., Kako, T., Hashimoto, K., … (2001). Preparation of transparent super-hydrophobic polymer film with brightness enhancement property. Journal of Materials Science Letters, 20(23), 2131–2133.
Cited by 56.