Mona Ali | Computer Science and Artificial Intelligence | Research Excellence Award

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Prof. Mona Ali | Computer Science and Artificial Intelligence | Research Excellence Award

King Faisal University | Saudi Arabia

Dr. Mona Abdelbaset Sadek Ali is an Associate Professor of Computer Science specializing in artificial intelligence, machine learning, and image processing. She earned her PhD in Computer Science (Wireless Computer Communications) from Cardiff University, UK, after completing an MSc in Information Technology (Image Processing) and a BSc in Information Technology with honors from Cairo University. With extensive academic experience spanning the UK, Saudi Arabia, and Egypt, her research integrates deep learning, optimization techniques, computer vision, IoT, mobile security, and intelligent healthcare systems. Dr. Ali has authored over 30 peer-reviewed research articles published in high-impact Web of Science-indexed journals and conferences, achieving an h-index of approximately 17, with more than 871 citations and 29 research documents. Her work frequently appears in Q1 and Q2 journals such as Mathematics, Electronics, Sustainability, PLOS ONE, and Applied Sciences. She has led and co-led numerous funded research projects supported by national and institutional bodies and has supervised multiple postgraduate MSc and PhD researchers. Her academic excellence has been recognized through competitive research funding and research poster awards. Overall, Dr. Ali’s career reflects sustained contributions to applied artificial intelligence and data-driven solutions with strong interdisciplinary and societal impact.

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Featured Publications


Tomato leaves diseases detection approach based on support vector machines

11th International Computer Engineering Conference (ICENCO), 246–250, 2015 · Citations: 222


Identifying two of tomatoes leaf viruses using support vector machine

Information Systems Design and Intelligent Applications, 2015 · Citations: 145


Detection of breast abnormalities of thermograms based on a new segmentation method

Federated Conference on Computer Science and Information Systems, 2015 · Citations: 78


Thermogram breast cancer prediction approach based on neutrosophic sets and fuzzy c-means algorithm

IEEE Engineering in Medicine and Biology Conference, 2015 · Citations: 76


A hybrid segmentation approach based on neutrosophic sets and modified watershed: A case of abdominal CT liver parenchyma

11th International Computer Engineering Conference (ICENCO), 2015 · Citations: 70

Zohaib Khan | Engineering and Technology | Excellence in Research Award

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Dr. Zohaib Khan | Engineering and Technology | Excellence in Research Award

Jiangsu University | China

Zohaib Khan is a PhD candidate in Control Science and Engineering at Jiangsu University, specializing in machine learning–driven perception and control for intelligent robotic systems. With over six years of research and applied experience, his work bridges deep learning, computer vision, and real-time robotic control, with a strong focus on agricultural robotics and precision farming. He has authored more than 10 high-impact SCI-indexed journal articles, achieving an h-index of 6, with 11 research documents and 121 citations. His research interests include object detection and segmentation (YOLO series, transformer-based models, RCNN), vision-guided navigation, precision spraying, and robust control of autonomous robots in unstructured environments. Zohaib has contributed as both first and co-author to leading journals such as Computers and Electronics in Agriculture, Agronomy, Sensors, and IEEE Transactions on Industrial Electronics. Alongside research, he has extensive experience supervising student projects and developing real-time AI pipelines using Python, PyTorch, OpenCV, ROS, and C/C++. His academic excellence is recognized through multiple national and international awards, including innovation, debate, and research excellence honors. Overall, Zohaib Khan represents a strong blend of theoretical rigor and practical AI deployment, aiming to advance large-scale industrial and agricultural perception systems.

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Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

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Mr. Ibrahim Khalil Kabir | Engineering and Technology | Best Researcher Award

King Fahd University of Petroleum and Minerals | Saudi Arabia

Ibrahim Khalil Kabir is a control and robotics researcher working at the intersection of control theory and artificial intelligence, with a strong focus on learning-based robotics, socially aware navigation, and human–robot interaction. He holds an MSc in Systems and Control Engineering and a BEng in Mechatronics Engineering, with a solid academic record and advanced training in autonomous systems. His research experience spans graduate teaching and research assistantships, where he contributed to robot path planning, navigation, and hands-on laboratory instruction using real robotic platforms. His scholarly output includes peer-reviewed journal and conference publications covering UAV control, mobile robot navigation, deep reinforcement learning, and socially aware robotic systems. According to Google Scholar, his research profile reflects an emerging h-index supported by multiple indexed documents and a steadily growing citation count, indicating increasing impact in robotics and intelligent control research. His work has appeared in reputable venues such as IEEE Access, Machine Learning and Knowledge Extraction, and IEEE conferences. He has received several academic honors, including national merit scholarships and highest GPA awards. Overall, his research trajectory demonstrates a strong foundation and growing influence in intelligent robotics, positioning him well for advanced doctoral research in learning-enabled autonomous systems.

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Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

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Mr. Oussama El Othmani | Computer Science and Artificial Intelligence | Best Innovation Award

Ecole Polytechnique de Tunisie | Tunisia

Oussama El Othmani is an emerging researcher and software engineer whose work bridges artificial intelligence, explainable machine learning, and applied computer engineering. He is currently pursuing a PhD in ETIC, following a strong academic foundation in computer engineering and preparatory mathematics–physics, with rigorous training in artificial intelligence, advanced learning algorithms, computer architecture, databases, and software methodology. Professionally, he has contributed to complex, mission-critical software systems, working across the full software development lifecycle while applying agile methodologies, object-oriented design, and hardware-aware optimization. His research interests focus on explainable and interpretable AI, machine learning, rough set theory, soft computing, computer vision, natural language processing, and AI applications in healthcare and high-stakes decision systems. He has led and contributed to multiple applied AI projects, including medical chatbots, diagnostic decision-support systems, blood anomaly detection, and antibiotic resistance classification. His scholarly output includes peer-reviewed publications in applied AI, He has also gained recognition through research-driven projects aligned with national and institutional initiatives. Overall, his profile reflects a strong balance of academic research, applied innovation, and real-world impact, positioning him as a promising contributor to the future of trustworthy and explainable artificial intelligence.

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Liu Ying | Mechanical Engineering | Research Excellence Award

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Dr. Liu Ying | Mechanical Engineering | Research Excellence Award

East China Jiaotong University | China

Ying Liu is a dedicated researcher and Lecturer specializing in vehicle engineering with a strong academic trajectory and growing research impact, reflected in an h-index of 2, 4 published documents, and 14 citations across indexed platforms. She earned a combined Master’s and PhD degree in Mechanical Engineering from Shanghai University, followed by a Bachelor’s degree in Mechanical Design, Manufacturing and Automation from Changchun Institute of Technology. Her professional career includes serving as a Lecturer at East China Jiaotong University, where she contributes to teaching, mentoring, and interdisciplinary research. Her work focuses on target optimization, image detection, reinforcement learning, computer vision, intelligent control, and smart vehicle technologies. She has completed five research projects, contributed to two national-level and multiple provincial and horizontal projects, and actively engages in consultancy with ten industry-linked initiatives. She has authored seven SCI-indexed papers, produced twenty-five patents, and participated in major scientific collaborations including a project funded with 5 million yuan. As a recipient of Jiangxi’s Early-Career Young Talents Program, she continues to advance innovation in intelligent vehicle systems. She remains committed to impactful research, advancing engineering applications, and contributing to societal and technological development.

Profile : Scopus

Featured Publications

Liu, Y., & [Co-author(s) if any]. (2025). Continuous path tracking of robots based on positioning error compensation with iterative learning control. IEEE Transactions on Instrumentation and Measurement.

Alexey Beskopylny | Civil Engineering | Best Researcher Award

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Prof. Dr. Alexey Beskopylny | Civil Engineering | Best Researcher Award

Don State Technical University | Russia

Dr. Alexey N. Beskopylny is a distinguished researcher and Vice Rector at Don State Technical University, serving as a Professor in the Department of Transport Systems. He holds a Doctor of Technical Sciences degree and has made significant contributions to civil and structural engineering, materials science, and transport systems. His studies span concrete technology, geopolymers, recycled construction materials, digital modeling, and structural optimization using AI and machine learning. Dr. Beskopylny’s works are frequently featured in high-impact journals such as Scientific Reports, Polymers, Buildings, and Applied Sciences. He has collaborated extensively on international projects focusing on sustainable materials and innovative construction technologies. Recognized for his academic excellence and leadership, he has received multiple institutional honors for advancing the field of transport infrastructure and sustainable construction. His continued efforts contribute to the modernization of engineering education and the promotion of environmentally responsible building practices worldwide.

Profile : Orcid

Featured Publications

Zubarev, K. P., Razveeva, I., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., Mailyan, L. R., Shakhalieva, D. M., Chernil’nik, A., & Nikora, N. I. (2025). Predicting the strength of heavy concrete exposed to aggressive environmental influences by machine learning methods. Buildings, 15(21), Article 3998.

Özkılıç, Y. O., Kalkan, İ., Aksoylu, C., Madenci, E., Umiye, O. A., Althaqafi, E., Stel’makh, S. A., Shcherban’, E. M., & Beskopylny, A. N. (2025). Effect of stirrup spacing and recycled steel wires on the shear and energy dissipation of pultruded GFRP hybrid beams. Journal of Engineered Fibers and Fabrics, 20, Article 15589250251380680.

Ecemiş, A. S., Yildizel, S. A., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., Aksoylu, C., Madenci, E., & Özkılıç, Y. O. (2025). Sustainable concrete with waste tire rubber and recycled steel fibers: Experimental insights and hybrid PINN–CatBoost prediction. Polymers, 17(21), Article 2910.

Özkılıç, Y. O., Başaran, B., Aksoylu, C., Karalar, M., Zeybek, Ö., Althaqafi, E., Beskopylny, A. N., Stel’makh, S. A., Shcherban’, E. M., & Umiye, O. A. (2025). Bending performance of reinforced concrete beams with partial waste glass aggregate replacement assessed by experimental, theoretical and digital image correlation analyses. Scientific Reports, 15, Article 20716.

Stel’makh, S. A., Shcherban’, E. M., Beskopylny, A. N., Mailyan, L. R., Shilov, A. A., Razveeva, I., Oganesyan, S., Pogrebnyak, A., Chernil’nik, A., & Elshaeva, D. (2025). Enhancing the mechanical properties of sulfur-modified fly ash/metakaolin geopolymers with polypropylene fibers. Polymers, 17(15), Article 2119.

Olga Tarasova | Genetics and Genomics | Best Researcher Award

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Dr. Olga Tarasova | Genetics and Genomics | Best Researcher Award

Institute of Biomedical Chemistry, Russian Academy of Medical Sciences (RAMS) | Russia

Dr Olga A. Tarasova is a bioinformatician and computational chemist whose research bridges cheminformatics, machine-learning and virus–host interaction modelling. She gained her M.S. in Medical Cybernetics and PhD in Bioinformatics from the Institute of Biomedical Chemistry (Moscow, Russia). Since then, she has progressed through roles from junior researcher to senior researcher now leading advanced computational modelling studies of antiviral compounds and virus–host interplay (e.g., at the Laboratory of Structure-Based Drug Design and recently heading the Laboratory of Big Data Analysis in Digital Pharmacology at IBMC). Her research interests include (Q)SAR/QSPR modelling, fragment-based drug design, molecular docking, text/data mining and machine-learning for prediction of metabolic, toxicity and viral-resistance profiles. Among her honours: the First-Degree Prize for Best Investigation at the Young Scientists Forum of the Russian Academy of Sciences for her work on HIV–host interactions. Dr Tarasova combines rigorous methodological development with applied antiviral and host-interaction modelling, making her a strong contributor to computational drug-discovery and virology informatics.

Profile : Orcid

Featured Publications

Pozdniakova, N., Generalov, E., Shevelev, A., & Tarasova, O. (2025). RNA therapeutics: Delivery problems and solutions A review. Pharmaceutics, 17(10), 1305.

Ivanov, S. M., Sukhachev, V. S., Tarasova, O. A., Lagunin, A. A., & Poroikov, V. V. (2025). Analysis of genomic and transcriptomic data revealed key genes and processes in the development of major depressive disorder. International Journal of Molecular Sciences, 26(19), 9557.

Shevelev, A., Pozdniakova, N., Generalov, E., & Tarasova, O. (2025). siRNA therapeutics for the treatment of hereditary diseases and other conditions: A review. International Journal of Molecular Sciences, 26(17), 8651.

Tarasova, O., Petrou, A., Ivanov, S. M., Geronikaki, A., & Poroikov, V. (2024). Viral factors in modulation of host immune response: A route to novel antiviral agents and new therapeutic approaches. International Journal of Molecular Sciences, 25(17), 9408.

Stolbova, E. A., Stolbov, L. A., Filimonov, D. A., Poroikov, V. V., & Tarasova, O. A. (2024). Quantitative prediction of human immunodeficiency virus drug resistance. Viruses, 16(7), 1132.

Chih-Lyang Hwang | Electrical Engineering | Best Researcher Award

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Prof. Chih-Lyang Hwang | Electrical Engineering | Best Researcher Award

National Taiwan University of Science and Technology | Taiwan

Dr. Chih-Lyang Hwang (SM’08) is a distinguished researcher and academic in the field of electrical and mechanical engineering, currently serving as a Research Fellow at the Intelligent Robot Center, National Taiwan University of Science and Technology (NTUST), Taipei, Taiwan. He earned his Ph.D. in Mechanical Engineering from Tatung Institute of Technology  and subsequently held professorial positions at Tatung Institute of Technology, Tamkang University, and NTUST. With an extensive academic career spanning over three decades, he has contributed significantly to robotics, fuzzy neural modeling, nonlinear control, and human–robot interaction. His research also encompasses distributed visual and wireless localization, UAV control, and emotion recognition. Dr. Hwang has been a Visiting Scholar at Georgia Institute of Technology and Auburn University, broadening his international academic collaborations. He has authored numerous influential journal and conference papers, amassing over 3,383 citations, 533 documents, and an H-index of 29. Recognized among the world’s top 2% scientists by Stanford University for multiple years, he has also received Excellent and Outstanding Research Awards from NTUST and 2024. His enduring contributions continue to advance intelligent robotics and control systems research globally.

Profile : Google Scholar

Featured Publications

Hwang, C.-L., Yang, C.-C., & Hung, J.-Y. (2017). Path tracking of an autonomous ground vehicle with different payloads by hierarchical improved fuzzy dynamic sliding-mode control. IEEE Transactions on Fuzzy Systems, 26(2), 899–914.

Hwang, C.-L., Jan, C., & Chen, Y.-H. (2001). Piezomechanics using intelligent variable-structure control. IEEE Transactions on Industrial Electronics, 48(1), 47–59.

Hwang, C.-L., Chang, L.-J., & Yu, Y.-S. (2007). Network-based fuzzy decentralized sliding-mode control for car-like mobile robots. IEEE Transactions on Industrial Electronics, 54(1), 574–585.

Hwang, C.-L., Chiang, C.-C., & Yeh, Y.-W. (2013). Adaptive fuzzy hierarchical sliding-mode control for the trajectory tracking of uncertain underactuated nonlinear dynamic systems. IEEE Transactions on Fuzzy Systems, 22(2), 286–299.

Hwang, C.-L. (2004). A novel Takagi–Sugeno-based robust adaptive fuzzy sliding-mode controller. IEEE Transactions on Fuzzy Systems, 12(5), 676–687

Yosef Wubet | Electrical Engineering | Young Scientist Award

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Mr. Yosef Wubet | Electrical Engineering | Young Scientist Award

University of Gondar Institute of Technology | Ethiopia

Yosef Birara Wubet is a lecturer and researcher in Electrical and Computer Engineering, specializing in power systems and renewable energy. He holds a Master of Science in Power System Engineering and a Bachelor of Science in Electrical Power and Control Engineering, both from Bahir Dar University, Ethiopia. Since joining the University of Gondar as Lecturer (previously Assistant Lecturer), he has taught, supervised undergraduate projects and internships, reviewed journals, managed team projects, and contributed to practical works in both academic and industrial settings. His research interests span transient stability analysis using machine learning (notably artificial neural networks), fault classification and detection, solar power system design, smart grid technologies, modeling and design of controllers, system stability and forecasting, and modeling renewable energy integration. He has published multiple articles in peer-reviewed journals, including “Transient Stability Assessment and Enhancement of Hydropower Plant Using Artificial Neural Network” and “Design and modeling of ANN-based automatic generation control and voltage regulator for integrated hydropower plants in Ethiopia.” His honors include high academic distinctions (CGPA 3.96/4.0 in MSc, “Very great distinction”), the “Best Project of the Year 2018” at Bahir Dar Institute of Technology, and an Electrical Installation License from the Ethiopian Petroleum and Energy Authority. Yosef’s work contributes both theoretically and practically toward more stable, reliable, and renewable-energy-enabled power systems in Ethiopia and beyond.

Profile : Google Scholar

Featured Publications

Wubet, Y. B., Getahun, H. M., Alemu, Y. A., & Gela, T. T. (2025). Transient stability assessment and enhancement of hydropower plant using artificial neural network. Scientific African, Elsevier.

Wubet, Y. B., Gela, T. T., & Getahun, H. M. (2025). Design and modeling of ANN-based automatic generation control and automatic voltage regulator for two integrated hydro power plants in Ethiopia. Scientific African, Elsevier.