Dr. Muh Asriadi AM | Instructional Technology | Excellence in Research Award

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Dr. Muh Asriadi AM | Instructional Technology | Excellence in Research Award

Universitas Pendidikan Indonesia | Indonesia

Dr. Muh. Asriadis AM, S.Pd., M.Pd., born in Watu, is a lecturer in Early Childhood Education at Universitas Pendidikan Indonesia Cibiru and currently pursuing his doctoral studies at Universitas Pendidikan Indonesia. He holds a Bachelor’s degree from UIN Alauddin Makassar and a Master’s degree in Education from Universitas Negeri Yogyakarta, with academic expertise in educational evaluation, physics education, Instructional Technology and early childhood learning. He has served in several professional and organizational roles, including Head of the Activity Unit UKKS, Project Coordinator for Yayasan Senyum Kita, Manager of event programs, and member or leader in academic communities such as KMP UNY, HIMMPAS, and HEPI. Dr. Asriadis has also worked with institutions such as PT Ebiz Prima Nusa and LBB Primagama Yogyakarta, contributing to educational projects and training programs. He is actively involved in research, publishing through academic platforms including Google Scholar, Scopus, SINTA, Garuda, ORCID, and Web of Science. With academic status as Lektor/Assistant Professor, he continues to develop expertise in educational evaluation, early childhood education, and science learning, while contributing significantly to academic, organizational, and community-based educational initiatives.

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Assoc. Prof. Dr. Xiaoqing Sun | Vibration Control | Research Excellence Award

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Assoc. Prof. Dr. Xiaoqing Sun | Vibration Control | Research Excellence Award

Donghua University | China

Dr. Sun Xiaoqing holds a PhD in Engineering and serves as a Master’s Supervisor at the School of Mechanical Engineering, Donghua University, Shanghai. He earned his PhD from Shanghai Jiao Tong University’s State Key Laboratory of Mechanical Systems and Vibration, where he focused on mechanical system integration design, micro-vibration active and passive control, and virtual simulation and optimization. He also holds a Master’s degree in Mechanical Design and Theory from Wuhan University, specializing in system dynamics modeling, CAD/CAE, virtual design, and fatigue life prediction. Dr. Sun has participated in several significant research projects, including serving as the Principal Investigator for the National Natural Science Foundation of China Youth Project, where he developed a collaborative vibration isolation mechanism, vibration control and compliant tensioning platform for thin-film mirrors to achieve ultra-precision positioning and vibration suppression. He also contributed to research on non-destructive testing technology for bolt preload for Nanjing CRRC Puzhen Rolling Stock Co., Ltd., and to the development of a space six-DOF micro-vibration isolation platform for the Shanghai Aerospace Systems Engineering Research Institute, proposing and validating an innovative active–passive vibration isolation scheme. His expertise spans mechanical vibration, system dynamics, control theory, and advanced simulation.

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Assoc. Prof. Dr. Entesar Eliwa | Deep Learning for Robotic Vision | Excellence in Research Award

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Assoc. Prof. Dr. Entesar Eliwa | Deep Learning for Robotic Vision | Excellence in Research Award

King Faisal University | Saudi Arabia

Dr. Entesar Hamed I. Eliwa is an Associate Professor at King Faisal University, Faculty of Science, Department of Mathematics and Statistics. She holds a B.Sc. in Computer Science from Minia University, where she also served as a Teaching Assistant before completing her M.Sc. and Ph.D. in the Computer Science Department. After joining King Faisal University as an Assistant Lecturer, her strong research productivity and academic contributions led to her promotion to Associate Professor. Her work focuses on data mining, knowledge discovery, predictive modeling, supervised learning, classification, association rule mining, Deep Learning for Robotic Vision and artificial intelligence. She has successfully completed 28 research projects and is currently leading 6 ongoing studies. Her scholarly influence is reflected in her most recent citation metrics, with 443 total citations across 373 citing documents, demonstrating a solid and expanding research footprint. She has produced 22 research documents contributing to advancements in computational intelligence, and she maintains an h-index of 8, underscoring the depth and consistency of her academic impact. Through her research, publications, and academic service, Dr. Eliwa continues to strengthen the fields of computer science, data analytics, and artificial intelligence within both regional and global research communities.

Profile: Scopus | Orcid | Google Scholar

Featured Publications

El Koshiry, A., Eliwa, E., Abd El-Hafeez, T., & Tony, M. A. A. (2026). The effectiveness of an e-learning platform in developing digital citizenship skills among blind students.  https://doi.org/10.1007/978-3-031-94770-4_21

Hamed, E., & Abd El-Hafeez, T. (2025). Deep learning for sustainable agriculture: Automating rice and paddy ripeness classification for enhanced food security. Egyptian Informatics Journal. https://doi.org/10.1016/j.eij.2025.100785

Amr, A., Eliwa, E., Tony, A. A., Shalgham, A., & Contributors from King Faisal University; Minia University; Arish University. (2025). The effectiveness of using Box-to-Box technology to develop some of the composite physical and technical capabilities of footballers. Fusion: Practice and Applications. https://doi.org/10.54216/fpa.170224

Eliwa, E. H. I., & Abd El-Hafeez, T. (2025). A robust deep learning pipeline for multi-class cervical cancer cell identification. Egyptian Informatics Journal. https://doi.org/10.1016/j.eij.2025.100787

Eliwa, E. H. I., & Abd El-Hafeez, T. (2025). A novel YOLOv11 framework for enhanced tomato disease detection. PeerJ Computer Science. https://doi.org/10.7717/peerj-cs.3200

Dr. Faisal Saeed | Object Detection | Excellence in Research Award

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Dr. Faisal Saeed | Object Detection | Excellence in Research Award

Shenzhen University | China

Dr. Faisal Saeed is an ai research scientist specializing in computer vision, deep learning, and intelligent manufacturing, with a strong research portfolio built through advanced academic training and international research appointments. He earned his master’s combined Ph.d. in computer science from Kyungpook National University, South Korea, where his work focused on transformer-based architectures for industrial small-object detection, culminating in the thesis feature enhanced assignment-based detection transformer for industrial small object detection. His academic contributions include 21 documents, a growing research footprint of 738 citations, and an h-index of 10, reflecting the global impact of his work across ai-driven automation, defect detection, and predictive maintenance. Professionally, he has served as a university research assistant and later as a postdoctoral fellow in both South Korea and China, contributing to deep learning theory, medical image analysis, multimodal ai, Object Detection and industrial visual inspection systems. His research integrates digital twins, time-series forecasting, and transformer models to advance intelligent manufacturing and robotics. Committed to bridging theoretical innovation with real-world applications, Dr. Saeed continues to publish influential work, secure funding for emerging ai research, and contribute to the scientific community through teaching, collaboration, and cutting-edge industrial ai development.

Profile: Scopus | Google Scholar

Featured Publications

Shah, H. A., Saeed, F., Yun, S., Park, J. H., Paul, A., & Kang, J. M. (2022). A robust approach for brain tumor detection in magnetic resonance images using finetuned EfficientNet. IEEE Access, 10, 65426–65438.

Saeed, F., Paul, A., Rehman, A., Hong, W. H., & Seo, H. (2018). IoT-based intelligent modeling of smart home environment for fire prevention and safety. Journal of Sensor and Actuator Networks, 7(1), 11.

Saeed, F., Paul, A., Karthigaikumar, P., & Nayyar, A. (2020). Convolutional neural network based early fire detection. Multimedia Tools and Applications, 79(13), 9083–9099.

Saeed, F., Ahmed, M. J., Gul, M. J., Hong, K. J., Paul, A., & Kavitha, M. S. (2021). A robust approach for industrial small-object detection using an improved faster regional convolutional neural network. Scientific Reports, 11(1), 23390.

Rehman, A., Rathore, M. M., Paul, A., Saeed, F., & Ahmad, R. W. (2018). Vehicular traffic optimisation and even distribution using ant colony in smart city environment. IET Intelligent Transport Systems, 12(7), 594–601.

Dr. Yinglong Li | Fuzzy Decision | Research Excellence Award

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Dr. Yinglong Li | Fuzzy Decision | Research Excellence Award

Zhejiang University of Technology | China

Yinglong Li is an associate professor in the school of computer science and technology at Zhejiang University of Technology, specializing in intelligent privacy protection, deep learning, computer vision, and fuzzy intelligence. He earned his Ph.d. in computer science from Renmin university of China and previously served as a senior lecturer at the University of Bristol. As an active researcher, he has authored more than 20 high-quality papers in leading journals and conferences such as IEEE TFS, IEEE TVT, fuzzy set syst, ieee iwqos, ieee mass, fuzzy decision and applied soft computing. His academic impact is reflected in 211 citations, documented in 204 citing documents, along with 33 published documents and an h-index of 7. he has completed or is undertaking nine research projects, published ten patents. With industry collaborations including Ningbo Bodao Co., Ltd. On marine ai systems and China mobile Hangzhou research institute on privacy-preserving surveillance, his work bridges academic innovation and real-world application. He is also a member of IEEE, ACM, and CCF, actively contributing as a journal reviewer and mentor to graduate researchers.

Profiles: Scopus | Orcid | Google Scholar

Featured Publications

Chen, T., Jiang, Q., Li, Y., Chen, T., & Li, J. (2025). Privacy-aware edge intelligent parking recommendation using intuitionistic fuzzy sets. IEEE Transactions on Industrial Informatics.

Li, Y., Chen, T., Li, J., Liu, W., & Chen, T. (2025). QoS-aware fuzzy decision-based data forwarding in edge-centric vehicular networks. Applied Soft Computing.

Chen, T., Tian, X., Li, Y., Jiang, Q., & Liu, Z. (2024). FuzzyFollow: A novel privacy-aware intelligent vehicle-following scheme for safe driving on risky roads using fuzzy sets. In 2024 27th International Conference on Computer Supported Cooperative Work in Design (CSCWD).

Li, Y., Huang, Z., Chen, T., Xu, X., Liu, W., & Lv, M. (2023). TCFP: A novel privacy-aware edge vehicular trajectory compression scheme using fuzzy Markovian prediction. In 2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Li, Y., Meng, D., Xu, X., Chen, T., Li, Y., Wang, T., & Li, Y. (2023). fuzzyForward: A novel multi-hop data forwarding scheme using fuzzy decision for edge VANETs. In 2023 IEEE 24th International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM).

Dr. Zhifeng Chen | Motion Correction | Excellence in Research Award

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Dr. Zhifeng Chen | Motion Correction | Excellence in Research Award

Neusoft Medical Systems Co. Ltd | China

Dr. Zhifeng Chen is a distinguished researcher in biomedical imaging, specializing in advanced MRI acquisition and reconstruction techniques, with a strong record of scientific innovation across academia and industry. He currently serves as a principal scientist and research collaboration specialist at the institute of research and clinical innovations, neusoft medical systems, and has held influential research positions at Monash biomedical imaging, the university of southern California, Harvard medical school, and Massachusetts general hospital. His academic training includes a Ph.d. In biomedical engineering from Zhejiang university and a B.S. In electronic and information engineering from Shandong University. Over the past decade, he has contributed extensively to rapid neuroimaging, quantitative mri, non-cartesian imaging, motion-resistant dce-mri, Motion Correction and deep learning–driven reconstruction methods. Dr. Chen has authored 26 scientific documents, which have collectively received 214 citations from 189 citing documents, and he holds an h-index of 9, reflecting the impact and consistency of his research contributions. He has also led and collaborated on major projects involving physics-guided deep learning, compressed sensing, low-rank modeling, contrastive learning, and diffusion-based reconstruction methods. Alongside his research, he is an active reviewer, grant evaluator, and editorial board member, contributing significantly to the global advancement of medical imaging science.

Profile: Scopus | Orcid | Google Scholar

Featured Publications

Chen, Z., Pawar, K., Islam, K. T., Peiris, H., Egan, G., & Chen, Z. (2026). Motion‐informed deep learning for human brain magnetic resonance image reconstruction framework. NMR in Biomedicine.

Bi, X., Liu, X., Chen, Z., Chen, H., Du, Y., Chen, H., Huang, X., & Liu, F. (2025). Complex-valued image reconstruction for compressed sensing MRI using hierarchical constraint. Magnetic Resonance Imaging.

Ekanayake, M., Pawar, K., Chen, Z., Egan, G., & Chen, Z. (2025). PixCUE: Joint uncertainty estimation and image reconstruction in MRI using deep pixel classification. Journal of Imaging Informatics in Medicine.

Ekanayake, M., Pawar, K., Chen, Z., Egan, G., & Chen, Z. (2025). PixCUE: Joint uncertainty estimation and image reconstruction in MRI using deep pixel classification (Updated version). Journal of Imaging Informatics in Medicine.

Ekanayake, M., Chen, Z., Egan, G., Harandi, M., & Chen, Z. (2025). SeCo-INR: Semantically conditioned implicit neural representations for improved medical image super-resolution. Proceedings of the IEEE Winter Conference on Applications of Computer Vision.

Prof. Huiqin Pei | Multi-Agent System | Research Excellence Award

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Prof. Huiqin Pei | Multi-Agent System | Research Excellence Award

East China JiaoTong University | China

Prof. Huiqin Pei is an accomplished associate professor at the school of electrical and automation engineering, East China Jiaotong University, specializing in control science and control engineering. She has established a strong academic foundation with a bachelor’s, master’s, and doctor of engineering degree from East China Jiaotong university. She has served in various academic roles, including lecturer positions at Nanchang University of Technology and East China Jiaotong University, and later as a visiting scholar at shanghai Jiao Tong University. Her research interests span swarm dynamics, cooperative control, complex network modeling, multi-agent systems, multi-agent system and cooperative optimization in robotic systems. Over the years, she has produced a significant body of scholarly work, with 30 published documents, 389 citations by 349 documents, and an h-index of 10, reflecting her impact in the field. As a reviewer for leading journals such as IEEE transactions on cybernetics and nonlinear dynamics, she contributes to advancing high-quality research. She also serves as an evaluation expert for the national natural science foundation and the national graduate education evaluation system. Honored with the second prize of the natural science award, she continues to influence the fields of nonlinear dynamics and cooperative control.

Profile: Scopus

Featured Publications

Pei, H. (2025). Collaborative consistency tracking in hybrid multiple agent systems under slow time varying disturbance signals. IEEE Systems Journal.

Pei, H. (2025). Observer-based event-triggered group consensus tracking of hybrid multi-agent systems. Transactions of the Institute of Measurement and Control.

Pei, H. (2025). Multi-agent multi-target search with multi-head attention. In Proceedings of the Conference.

 

Assoc. Prof. Dr. Michael Ehizuelen | Development Economics | Research Excellence Award

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Assoc. Prof. Dr. Michael Ehizuelen | Development Economics | Research Excellence Award

Institute of African Studies | China

Dr. Michael Mitchell Omoruyi Ehizuelen is a distinguished scholar of development economics and a leading voice in Africa – China relations, with over a decade of academic, research, and policy engagement experience. He holds a Ph.d. in world economics and an M.A. in Chinese political economy from Xiamen University, where he also earned a certificate in chinese language and cultural studies. Currently an associate professor and research fellow at the institute of African studies, Zhejiang normal university, he serves as the executive director of the research center for nigerian studies and has authored more than 100 publications. his scholarly impact includes 100 citations, 13 documents, and an h-index of 4, reflecting meaningful contributions to sino-african cooperation, foreign aid analysis, public policy, maritime security, Development Economics and sustainable development. Dr. Ehizuelen has pioneered major academic platforms, including the china–nigeria academic exchange programme, the research center for Nigerian studies, the Abuja forum, and the ibadan forum, strengthening cross-continental collaboration and intellectual exchange. He has secured multiple research grants, mentored emerging scholars, and shaped innovative curricula in international aid and african development. Widely recognized for advancing evidence-based policymaking and regional integration, he remains committed to fostering academic excellence, informed governance, and sustainable economic transformation across Africa.

Profile: Scopus

Featured Publication

Ehizuelen, M. (2025). Assessing the possible influence of maritime piracy on African Continental Free Trade Area (AfCFTA) in Nigeria. Journal of Shipping and Trade.

Mr. Angelos Athanasiadis | Deep Learning for Robotic Vision | Research Excellence Award

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Mr. Angelos Athanasiadis | Deep Learning for Robotic Vision | Research Excellence Award

Aristotle University of Thessaloniki | Greece

Mr. Angelos Athanasiadis is a Ph.d. candidate in electrical and computer engineering at the Aristotle University of Thessaloniki, specializing in fpga-based acceleration of convolutional neural networks and heterogeneous computing systems. he holds an M.Eng. in electronics and computer systems and an mba with high distinction, combining strong technical expertise with strategic insight. his research focuses on full-precision CNN acceleration, FPGA architectures, cyber-physical systems, Deep Learning for Robotic Vision and distributed embedded system emulation. Angelos has contributed to major eu-funded research projects, including the adviser and redesign projects, and has completed industrial internships at cadence design systems in Munich. He has also worked in r&d and embedded development roles at exapsys and seems pc, strengthening his applied engineering experience. Academically, he has collaborated with Professor Ioannis papaefstathiou and assistant professor nikolaos tampouratzis, contributing to innovations in energy-efficient cnn inference and high-fidelity system emulation. his open-source framework, fusion, integrates qemu and omnet++ using hla/certi for deterministic, timing-accurate, multi-node execution. Although early in his publication journey, angelos has 1 citation, 1 scopus-listed document, and an h-index of 1, reflecting the initial impact of his contributions. Driven by interdisciplinary research, he aims to advance reconfigurable computing for next-generation autonomous and embedded intelligent systems.

Profiles: Orcid | Google Scholar

Featured Publications

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2025). An efficient open-source design and implementation framework for non-quantized CNNs on FPGAs. Integration, 102625.

Athanasiadis, A., Tampouratzis, N., & Papaefstathiou, I. (2024). An open-source HLS fully parameterizable matrix multiplication library for AMD FPGAs. WiPiEC Journal – Works in Progress in Embedded Computing, Article 62.

Katselas, L., Athanasiadis, A., Jiao, H., Papameletis, C., Hatzopoulos, A., & Marinissen, E. J. (2017). Embedded toggle generator to control the switching activity during test of digital 2D-SoCs and 3D-SICs. In 2017 27th International Symposium on Power and Timing Modeling, Optimization and Simulation (PATMOS) (pp. 1–8). IEEE.

Prof. Dr. Abdelkrim Kamel Oudjida | Real-Time Robotic Control | Research Excellence Award

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Prof. Dr. Abdelkrim Kamel Oudjida | Real-Time Robotic Control | Research Excellence Award

Centre de Développement des Technologies Avancées | Algeria

Prof. Dr. Abdelkrim Kamel Oudjida is a distinguished director of research at the Centre De Développement des Technologies Avancées, recognized for his extensive contributions to computer arithmetic and its applications in Cryptography, DSP, robotics, Real-Time Robotic Control and VLSI digital design. With a strong academic and professional background, he has authored 22 publications, delivered 35 communications, and contributed to 2 patents, establishing himself as a leading figure in advanced digital circuit design. his research achievements include developing advanced binary recoding methods and pioneering new arithmetic strategies for efficient asic/fpga implementation of linear systems. His work has earned him 328 citations, based on 263 citing documents, supported by 34 documents, and an h-index of 8, reflecting his growing scholarly impact. in addition to his role as a full-time researcher, he serves as a lecturer in computer arithmetic and cryptography at the national higher school of mathematics. He has supervised more than 50 engineering, master’s, and phd projects, further strengthening the scientific community through mentorship. As a reviewer for prestigious journals such as ieee tcas, elsevier microelectronics, and jolpe, and collaborating with several european research labs, oudjida continues to advance the field through innovation, leadership, and international engagement.

Profiles: Scopus | Orcid

Featured Publications

Liacha, A., Oudjida, A. K., & Bellal, R. N. (2025). On the complexity of constant multiplication problem. International Journal of Circuit Theory and Applications. Advance online publication.

Nait-Abdesselam, F., Oudjida, A. K., Khouas, A., & Liacha, A. (2025). On computing the double point multiplication in elliptic curve cryptography. Cryptologia. Advance online publication.

Echikr, A., Yachir, A., Kerrache, C. A., Oudjida, A. K., & Sahraoui, Z. (2024). Interoperable IoRT for healthcare: Securing intelligent systems with decentralized blockchain. Acta Informatica Pragensia.

Oudjida, A. K., & Liacha, A. (2021). Radix-2ʷ arithmetic for scalar multiplication in elliptic curve cryptography. IEEE Transactions on Circuits and Systems I: Regular Papers, 68(5), 1984–1997.

Oudjida, A. K. (n.d.). Multiple constant multiplication algorithm for high-speed and low-power design.