Alexis Chavez | Renewable Energy Systems | Research Excellence Award

Published on by Electrical Engineering

Mr. Alexis Chavez | Renewable Energy Systems | Research Excellence Award

PhD Candidate | Universidad Mayor De San Simón | Bolivia

Ivan Alexis Chavez Flores is a Civil Engineer and Water Resources Engineer specializing in hydraulics, hydrology, and climate-resilient water systems, currently serving as an independent consultant at ELAXIS Ingeniería and a part-time academic instructor, with professional engagements across academia, consultancy, and applied engineering projects. He holds a Bachelor of Science in Civil Engineering with specialization in Hydraulics and Hydrology, graduating with highest academic distinction, and a Master of Science in Water Resources Engineering earned with cum laude recognition, complemented by advanced training in hydrological modeling, irrigation efficiency, His achievements include competitive international scholarships, institutional commendations for leadership and academic service, professional certifications, active membership in national and international engineering and water resources associations, and participation as a research collaborator within multidisciplinary scientific networks.

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Featured Publications

Ivan Alexis Chavez Flores*, Impacts of climate change on the hydropower potential of a multipurpose storage system project in Bolivian Andes. Journal of Hydrology: Regional Studies, 2025, Article 102903.

Ivan Alexis Chavez Flores, Mauricio Villazón, Diego Inturias, Pablo Pardo, Carolina Aldunate, Crítica, análisis y relleno de las series de tiempo hidrométricas de la Amazonía Boliviana: Ajuste de curvas de descarga H–Q (Tomo 1). FAO Bolivia, 2024.

Ivan Alexis Chavez Flores*, Crítica, análisis y relleno de las series de tiempo hidrométricas de la Amazonía Boliviana: Análisis, crítica y relleno de la información hidrométrica y caudales (Tomo 2). FAO Bolivia, 2024.

Santiago Núñez Mejía, Carina Villegas-Lituma, Patricio Crespo, Mario Córdova, Ronald Gualán, Johanna Ochoa, Pablo Guzmán, Daniela Ballari, Ivan Alexis Chavez Flores et al., Downscaling precipitation and temperature in the Andes: applied methods and performance—a systematic review protocol. Environmental Evidence, 2023, 12, Article 23.

Qingguo Lü | Electrical Engineering  | Research Excellence Award

Published on by Electrical Engineering

Dr. Qingguo Lü | Electrical Engineering  | Research Excellence Award

Associate Researcher | Chongqing University | China

Qingguo Lü is an Associate Researcher at Chongqing University specializing in distributed optimization, privacy-preserving machine learning, and smart grid systems. He earned his doctoral degree in computer science and technology with a strong focus on optimization theory and networked systems and subsequently advanced his expertise through postdoctoral research and international academic collaboration.  His scholarly contributions have delivered both theoretical advances and practical engineering solutions, achieving strong international visibility and impact. His academic influence is reflected by 1,174 citations, an h-index of 18, and an i10-index of 26. In recognition of his expertise and service, he holds multiple editorial and guest editorial appointments in international journals, serves on conference program committees, contributes extensively to peer review, holds innovation patents, and maintains professional standing as an IEEE Senior Member, demonstrating sustained excellence in research, leadership, and academic service suitable for a prestigious research award.

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Featured Publications

Distributed projection subgradient algorithm over time-varying general unbalanced directed graphs
H. Li, Q. Liu, T. Huang – IEEE Transactions on Automatic Control · Citations: 115
Accelerated convergence algorithm for distributed constrained optimization under time-varying general directed graphs
H. Li, Q. Lü, X. Liao, T. Huang – IEEE Transactions on Systems, Man, and Cybernetics: Systems · Citations: 104
Achieving acceleration for distributed economic dispatch in smart grids over directed networks
Q. Liu, X. Liao, H. Li, T. Huang – IEEE Transactions on Network Science and Engineering · Citations: 100
Convergence analysis of a distributed optimization algorithm with a general unbalanced directed communication network
H. Li, Q. Liu, T. Huang – IEEE Transactions on Network Science and Engineering · Citations: 96
Privacy masking stochastic subgradient-push algorithm for distributed online optimization
Q. Lü, X. Liao, T. Xiang, H. Li, T. Huang – IEEE Transactions on Cybernetics · Citations: 80

Mingxu Wang | Wireless Communication | Young Scientist Award

Published on by Electrical Engineering

Dr. Mingxu Wang | Wireless Communication | Young Scientist Award

Research Associate | Fudan University | China

Mingxu Wang is a Research Associate at Fudan University specializing in photonic terahertz and free-space optical communications within advanced radio access networks. He holds advanced academic training in electronic and optical engineering with a strong focus on high-capacity fiber–wireless integrated systems, developed through rigorous graduate-level education and collaborative research at leading international institutions. His scholarly output has achieved 687 citations with an h-index of 15 and an i10-index of 22, reflecting sustained impact in the field. He holds multiple patents related to advanced modulation and fiber–wireless integration techniques and actively contributes to the research community through professional memberships with IEEE, Optica, and SPIE. His excellence has been recognized through highly competitive international scholarships and distinctions, underscoring his leadership, innovation, and growing influence in electrical and photonic communications research.

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Featured Publications

Low complexity neural network equalization based on multi-symbol output technique for 200+ Gbps IM/DD short reach optical system
B. Sang, W. Zhou, Y. Tan, M. Kong, C. Wang, M. Wang, L. Zhao, J. Zhang, J. Yu – Journal of Lightwave Technology · Citations: 78
Integrated high-resolution radar and long-distance communication based-on photonic in terahertz band
Y. Wang, W. Li, J. Ding, J. Zhang, M. Zhu, F. Zhao, M. Wang, J. Yu – Journal of Lightwave Technology · Citations: 64
Joint communication and radar sensing functions system based on photonics at the W-band
Y. Wang, J. Liu, J. Ding, M. Wang, F. Zhao, J. Yu – Optics Express · Citations: 56
W-band simultaneous vector signal generation and radar detection based on photonic frequency quadrupling
Y. Wang, J. Ding, M. Wang, Z. Dong, F. Zhao, J. Yu – Optics Letters · Citations: 46
Photonics-assisted joint high-speed communication and high-resolution radar detection system
Y. Wang, Z. Dong, J. Ding, W. Li, M. Wang, F. Zhao, J. Yu – Optics Letters · Citations: 45

Yu Luo | Antenna Design | Research Excellence Award

Published on by Electrical Engineering

Prof. Dr. Yu Luo | Antenna Design | Research Excellence Award

Professor | Tianjin University | China

Yu Luo is a Full Professor at the School of Microelectronics, Tianjin University, and a leading expert in antenna theory and technology within the field of electrical and electronic engineering. He earned his Bachelor of Engineering and Doctorate degrees in electronic engineering, developing strong specialization in antennas, arrays, and high-frequency systems. His professional career encompasses academic appointments and research fellowships at internationally recognized universities, where he has contributed to advanced millimeter-wave and terahertz system development, led nationally funded research projects, and served as principal investigator for competitive programs and industry collaborations. His scholarly contributions have achieved wide international recognition and strong citation impact. Professor Luo serves as an Associate Editor for an international physics journal, chairs professional IEEE chapters, and leads technical program committees for major global conferences, and his academic profile reflects 2,226 citations, 201 published documents, and an h-index of 26.

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Featured Publications

A Flat-Top Beam Nonuniform Waveguide Slot Antenna Based on Beamforming
IEEE Antennas and Wireless Propagation Letters · Citations: 1
A Terahertz Wide-Angle Beam-Steering 3D-Printed Dual-Polarized GRIN Lens With Planar Focal Surface
IEEE Transactions on Terahertz Science and Technology · Citations: 3
A Stacked-Plate-Ball Antenna Design for Optimized Gain and Extended Bandwidth
IEEE Antennas and Wireless Propagation Letters · Citations: 1
Flat-Top Beamforming Synthesis Method Achieved With High-Order Mode Dipoles
IEEE Antennas and Wireless Propagation Letters · Citations: 2

Zhengying Cai | Electric Vehicles | Best Researcher Award

Published on by Electrical Engineering

Prof. Zhengying Cai | Electric Vehicles | Best Researcher Award

Prof | China Three Gorges University  | China

Zhengying Cai is a Professor in the College of Computer and Information Technology at China Three Gorges University, specializing in artificial intelligence and quantum computing, with a strong academic and research profile that underpins his nomination for this award. He earned his bachelor’s, master’s, and doctoral degrees from Huazhong University of Science and Technology with advanced specialization in computer and information technologies, establishing a solid foundation for interdisciplinary research. His professional experience encompasses academic leadership, supervision of graduate researchers, and active involvement in high-impact research projects, alongside contributions to curriculum development and institutional research advancement. His research focuses on artificial intelligence methodologies, quantum computing frameworks, and their applications, resulting in a substantial body of scholarly output, including 38 research documents that have received 224 citations and reflect an h-index of 9, demonstrating both productivity and sustained academic impact.

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Featured Publications

An Artificial Plant Community Algorithm for Collision-Free Multi-Robot Aggregation
Z. Cai, Q. Yu, Z. Lu, Z. Liu, G. Gong – Applied Sciences (Switzerland)

Financial Time Series Uncertainty: A Review of Probabilistic AI Applications
S. Eggen, T.J. Espe, K. Grude, M. Risstad, R. Sandberg – Journal of Economic Surveys

Forecasting Implied Volatilities of Currency Options with Machine Learning Techniques and Econometric Models
A. Olsen, G. Djupskås, P.E. de Lange, M. Risstad – International Journal of Data Science and Analytics

Mr. Nicholas Otumi | Biomedical Instrumentation | Research Excellence Award

Published on by Electrical Engineering

Mr. Nicholas Otumi | Biomedical Instrumentation | Research Excellence Award

Research Assistant | University of Rochester | United States

Nicholas Otumi is a biomedical imaging researcher and diagnostic imaging specialist affiliated with the University of Rochester, with expertise spanning diagnostic imaging, biomedical engineering, and artificial intelligence–driven medical image analysis. He holds a Master of Science in Diagnostic Imaging with specialization in bioengineering and biomedical engineering, and a Bachelor of Science in Diagnostic Imaging Technology, supported by advanced training in deep learning, signal processing, inverse problems, and clinical imaging. His professional experience includes research assistant roles across academic and clinical settings, where he has contributed to imaging model development, clinical data management, AI-based brain and chest image segmentation, and interdisciplinary healthcare research, alongside leadership and community engagement roles within university environments. His research focuses on medical image quality, user-centered imaging system evaluation, deep learning for disease classification, and the application of advanced MRI and CT techniques in both high- and low-resource settings, with multiple peer-reviewed journal publications and ongoing studies under review. He has received competitive research funding and fellowship recognition, institutional awards for leadership and versatility, and has participated in international scientific schools and specialized workshops in radiochemistry, medical physics, AI diagnostics, and imaging quality assurance. His academic service includes research collaboration, technical support, and scholarly dissemination, reflecting a strong commitment to advancing diagnostic imaging research and education.

Profiles:  Google Scholar | ORCID

Featured Publications

AD Piersson, G Nunoo, E Tettey, N Otumi, User-centered assessment of MRI equipment flexibility, workspace adequacy, user interface usability, and technical proficiency. Appl. Clin. Inform., 2025, 16(5), 1595–1605.

AD Piersson, G Nunoo, K Dzefi-Tettey, N Otumi, Utility of advanced brain MRI techniques for clinical and research purposes in a low-resource setting: A multicentre survey. Next Res., 2025, 100638.

A Piersson, E Frost, K Dzefi-Tettey, N Otumi, H Mumuni, S Kafwimbi, et al., Public attitudes and preferences towards artificial intelligence in diagnostic imaging for clinical diagnosis in a low-resource setting (n = 1,032). Eur. Soc. Radiol. (ECR), 2025.

E Fiagbedzi, J Arkorful, IF Brobbey, E Appiah, S Nyarko, N Otumi, et al., A case of ruptured infrapatellar bursa sac with Baker’s cyst. Radiol. Case Rep., 2025, 20(1), 700–704.

E Fiagbedzi, J Arkorful, E Appiah, N Otumi, I Ofori, PN Gorleku, A rare case of intussusception in a 6-month-old baby. Radiol. Case Rep., 2025, 19(10), 4451–4456.

Zhongjun Ma | Nanoelectronics | Research Excellence Award

Published on by Electrical Engineering

Dr. Zhongjun Ma | Nanoelectronics | Research Excellence Award

Engineer | Henan Normal University | China

Zhongjun Ma is a faculty researcher at the School of Environment, Henan Normal University, Xinxiang, China, specializing in microwave absorption and related electromagnetic functional materials. He earned his doctoral degree with a specialization in microwave absorption science, building a strong foundation in material design, absorption mechanisms, and device-oriented applications. Professionally, he has contributed through academic teaching, research project participation, and collaborative research activities, demonstrating leadership in experimental design and scholarly dissemination. His research focuses on microwave absorbing materials, absorption mechanisms, and the development of high-performance microwave absorbing devices, with contributions that advance both theoretical understanding and practical implementation. He has authored 22 scholarly documents that collectively reflect sustained research productivity and impact, achieving 521 citations and an h-index of 12, underscoring the relevance and influence of his work within the field.

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Featured Publications

Toroidal Curved Overlapping Patch Resonant Microwave Sensor for Bolt Loosening Detection
Han, X.-Y.; Zhang, D.; Liu, J.; Liu, X.; Sun, C.; Fu, C.-H.; Ma, Z.-J. – SSRN
ZIF-67-Derived Hierarchical Porous Hollow Shell Engineering for Efficient Microwave Absorption in Ku Band
Han, X.; Sun, C.; Zhang, S.; Liu, K.; Zhai, P.; Liu, X.; Zhang, D.; Liu, J.; Ma, Z. – SSRN
Conversion of Lignin into Porous Carbons for High-Performance Supercapacitors via Spray Drying and KOH Activation
Feng, S.; Ouyang, Q.; Huang, J.; Zhang, X.; Ma, Z.; Liang, K.; Huang, Q. – Journal of Renewable Materials

Rémi Cogranne | Signal & Image Processing | Research Excellence Award

Published on by Electrical Engineering

Dr. Rémi Cogranne | Signal & Image Processing | Research Excellence Award

Troyes University of Technology | France

Rémi Cogranne is an Associate Professor at Troyes University of Technology (UTT), France, and a leading researcher in signal processing, applied mathematics, computer science, and information forensics. His research focuses on hypothesis testing theory, statistical modeling of digital images, image forensics, steganography and steganalysis, and computer network traffic modeling for attack detection, resulting in a substantial body of high-impact journal articles, conference papers, patents, and book chapters. His scholarly influence is demonstrated by 4,624 citations, an h-index of 32, and an i10-index of 68. He has made significant contributions to the research community through editorial service as Senior Associate Editor and Associate Editor for leading IEEE and international journals, membership in prestigious IEEE technical committees, and leadership roles in major international conferences. His work has been widely recognized through best paper awards, editorial honors, and sustained contributions to advancing theory and practice in signal processing and information forensics.

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Featured Publications

Content-adaptive steganography by minimizing statistical detectability
V. Sedighi, R. Cogranne, J. Fridrich – IEEE Transactions on Information Forensics and Security · Citations: 663

Selection-Channel-Aware Rich Model for Steganalysis of Digital Images
T. Denemark, V. Sedighi, V. Holub, R. Cogranne, J. Fridrich – IEEE WIFS · Citations: 469

Moving steganography and steganalysis from the laboratory into the real world
A. D. Ker et al., including R. Cogranne – ACM Workshop on Information Hiding and Multimedia Security · Citations: 344

Rich Model for Steganalysis of Color Images
M. Goljan, J. Fridrich, R. Cogranne – IEEE WIFS · Citations: 203

The ALASKA Steganalysis Challenge: A First Step Towards Steganalysis “into the wild”
R. Cogranne, É. Giboulot, P. Bas – ACM Workshop on Information Hiding and Multimedia Security · Citations: 186

Sina Saadati | Signal & Image Processing | Research Excellence Award

Published on by Electrical Engineering

Mr. Sina Saadati | Signal & Image Processing | Research Excellence Award

Computer Scientist | Amirkabir University of Technology | Iran

Sina Saadati is an emerging researcher and academic affiliated with a higher education and research institution, with expertise spanning interdisciplinary scientific and engineering research. He holds advanced academic degrees with specialization aligned to his research domain, supported by rigorous scholarly training that underpins his analytical and methodological contributions. His professional experience includes active involvement in research projects, collaborative investigations, and academic responsibilities that demonstrate leadership, independence, and commitment to knowledge advancement. His research focuses on targeted thematic areas within his field, with peer-reviewed scholarly publications contributing to the academic literature and supporting evidence-based innovation. His work has achieved measurable academic impact, reflected in 21 citations, an h-index of 3, and an i10-index of 0, indicating growing recognition within the research community. In addition to his research output, he has engaged with the scholarly ecosystem through professional memberships, academic service, and adherence to recognized research standards, positioning him as a dedicated and promising contributor suitable for award recognition.

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Featured Publications

Revolutionizing Endometriosis Treatment: Automated Surgical Operation through Artificial Intelligence and Robotic Vision

S. Saadati, M. Amirmazlaghani – Journal of Robotic Surgery, Vol. 18(1), p. 383, 2024

A Natural Way of Solving a Convex Hull Problem

S. Saadati, M. Razzazi – Proceedings of the National Academy of Sciences, India Section A, 2025

Cloud and IoT Based Smart Agent-Driven Simulation of Human Gait for Detecting Muscle Disorders

S. Saadati, A. Sepahvand, M. Razzazi – Heliyon, Vol. 11(2), 2025

Nahid: AI-Based Algorithm for Operating Fully-Automatic Surgery

S. Saadati – arXiv Preprint, arXiv:2401.08584

Aseel Basheer | Machine Learning | Excellence in Research Award

Published on by Electrical Engineering

Dr. Aseel Basheer | Machine Learning | Excellence in Research Award

Postdoc | University of Oklahoma | United States

Aseel Basheer is a Graduate Research Assistant and Ph.D. candidate in Computer Science at the University of Oklahoma, with expertise in machine learning, data science, and large-scale data analytics. The candidate holds a master’s degree in Computer Science with a specialization in data analytics and is pursuing advanced doctoral research focused on predictive modeling, visual analytics, and AI-driven decision support. Professionally, Aseel has contributed to interdisciplinary research projects in public health intelligence and pandemic surveillance, developing AI/ML models, data-driven forecasting systems, and visualization platforms, while also demonstrating academic leadership through teaching, mentoring, and curriculum support in higher education. The candidate’s professional profile is further strengthened by recognized certifications in data analytics, machine learning, healthcare data science, and research rigor, alongside active engagement in scholarly communities. The scholarly impact is reflected through 22 citations, an h-index of 2, and an i10-index of 1.

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