Yosef Wubet | Electrical Engineering | Young Scientist Award

Published on by Popular Engineer

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.

Marius Šumanas | Computer Vision | Best Researcher Award

Published on by Popular Engineer

Assist. Prof. Dr Marius Šumanas | Computer Vision | Best Researcher Award

Vilnius Tech | Lithuania

Dr. Marius Šumanas is an Associate Professor in the Department of Mechatronics, Robotics, and Digital Manufacturing at Vilnius Gediminas Technical University (VILNIUS TECH).  His research interests encompass robotics, machine learning, and digital manufacturing. Dr. Šumanas has authored several publications, including a study on improving positioning accuracy of articulated robots using deep Q-learning algorithms. He has also participated in various conferences, presenting topics related to machine learning applications in robotics. In addition to his academic roles, Dr. Šumanas has practical experience in the industry. Since 2018, he has been working as a Process Engineer and ERP Systems Business Analyst at MB Pramones algoritmas. He has also held positions in marketing and sales management in previous years. Dr. Šumanas’ work bridges the gap between theoretical research and practical application, contributing to advancements in robotics and digital manufacturing.

Profile : Orcid

Featured Publications

Andrijauskas, I., Šumanas, M., Dzedzickis, A., Tanaś, W., & Bučinskas, V. (2025). Computer vision-based optical odometry sensors: A comparative study of classical tracking methods for non-contact surface measurement. Sensors.

Šumanas, M., Treciokaite, V., Čerškus, A., Dzedzickis, A., Bučinskas, V., & Morkvenaite-Vilkonciene, I. (2022). Sitting posture monitoring using Velostat based pressure sensors matrix. In Smart Sensor Systems (pp. 1–12). Springer.

Bučinskas, V., Dzedzickis, A., Šumanas, M., Sutinys, E., Petkevicius, S., Butkiene, J., Virzonis, D., & Morkvenaite-Vilkonciene, I. (2022). Improving industrial robot positioning accuracy to the microscale using machine learning method. Machines, 10(10), 940.

Šumanas, M., Urbonis, D., Petronis, A., Stankaitis, S., Januškevičius, T., Iljin, I., & Dzedzickis, A. (2021). Evaluation of motion characteristics using absolute sensors. In Advances in Mechatronics and Intelligent Robotics (pp. 1–12). Springer.

Šumanas, M., Petronis, A., Urbonis, D., Januskevicius, T., Rasimavicius, T., Morkvenaite-Vilkonciene, I., Dzedzickis, A., & Bučinskas, V. (2021, April 22). Determination of excavator tool position using absolute sensors. In 2021 Open Conference of Electrical, Electronic and Information Sciences (eStream). IEEE.

Ahmed Fouly | Mechanical Engineering | Best Academic Researcher Award

Published on by Popular Engineer

Assoc. Prof. Dr. Ahmed Fouly | Mechanical Engineering | Best Academic Researcher Award

College of Engineering, King Saud University | Saudi Arabia

Dr. Ahmed Fouly is an accomplished engineer and researcher with a robust interdisciplinary profile: he holds a PhD in Mechatronics and Robotics (2017) from the Egypt–Japan University of Science and Technology, and earlier earned an MSc and BSc in Production Engineering & Mechanical Design from Minia University. Over the years he has progressed through academic ranks to become Associate Professor at King Saud University and concurrently in Minia University. He has published over 90 peer-reviewed articles . 873 citations and a current h-index of 18 as per Google Scholar . His research spans materials science tribology and wear, mechatronics and MEMS, AI modeling, and contact modeling using FEA. His academic experience includes service as course instructor in mechatronics, robotics, control, sensors, mechanical design, and finite element analysis, and supervising numerous projects in biomedical composites and robotics. He has secured competitive research grants (e.g. from King Salman Center, oriented research programs) and won multiple awards including “scientific publication awards” over successive years, best conference paper awards, and institutional recognition for robotics design. In sum, Dr. Fouly is a dynamic scholar fusing engineering, materials, and intelligent systems, with strong publication impact and leadership in emerging interdisciplinary fields.

Profiles : Google Scholar | Scopus | Orcid

Featured Publications

Fouly, A., Ibrahim, A. M. M., Sherif, E. S. M., FathEl-Bab, A. M. R., & Badran, A. H. (2021). Effect of low hydroxyapatite loading fraction on the mechanical and tribological characteristics of poly (methyl methacrylate) nanocomposites for dentures. Polymers, 13(6), 857.

Ahmadian, H., Fouly, A., Zhou, T., Kumar, A. S., Fathy, A., & Weijia, G. (2024). Investigating the valence balance of adding Nano SiC and MWCNTs on the improvement properties of copper composite using mechanical alloying and SPS techniques. Diamond and Related Materials, 145, 111113.

Fouly, A., & Alkalla, M. G. (2020). Effect of low nanosized alumina loading fraction on the physicomechanical and tribological behavior of epoxy. Tribology International, 152, 106550.

Fouly, A., Assaifan, A. K., Alnaser, I. A., Hussein, O. A., & Abdo, H. S. (2022). Evaluating the mechanical and tribological properties of 3D printed polylactic-acid (PLA) green-composite for artificial implant: Hip joint case study. Polymers, 14(23), 5299.

Fouly, A., Abdo, H. S., Seikh, A. H., Alluhydan, K., Alkhammash, H. I., Alnaser, I. A., … (2022). Evaluation of mechanical and tribological properties of corn cob-reinforced epoxy-based composites—theoretical and experimental study.

Suk-Ju Kang | Computer Science and Artificial Intelligence | Best Researcher Award 

Published on by Popular Engineer

Prof. Suk-Ju Kang | Computer Science and Artificial Intelligence | Best Researcher Award 

Sogang University | South Korea

Prof. Suk-Ju Kang is a distinguished Professor in the Department of Electronic Engineering at Sogang University, Seoul, Korea, specializing in visual computing, computer vision, and artificial intelligence. His research spans image synthesis and restoration, real-time 2D/3D human and hand pose estimation, and industrial AI applications such as anomaly detection and remaining useful life prediction. Prior to joining Sogang University in 2015, he served as Assistant Professor at Dong-A University and worked as a Senior Research Engineer at LG Display, contributing to advanced display technologies. He earned his Ph.D. in Electrical Engineering from POSTECH under the supervision of Dr. Young Hwan Kim, and his B.S. in Electronic Engineering from Sogang University. Prof. Kang has authored over 209 peer-reviewed publications, which have collectively garnered over 2,143 citations with an h-index of 25, reflecting his global research impact. He has been recognized with numerous honors, including the 2025 Haedong Best Paper Award, multiple Samsung Best Paper Awards (2023, 2024), the 2022 Merck Young Scientist Award, and the 2020 Young Researcher Award from The Korean Institute of Broadcast and Media Engineers. He also plays an active leadership role in academia, serving as Chairman of the AI and Computational Technology Society for Display, Chairman of the Image Processing Research Society, and Organizing Committee Chair for major international conferences such as ITC-CSCC and AISPC.

Profiles: Scopus | Google Scholar

Featured Publications

“Luminance Compensation for Stretchable Displays Using Deep Visual Feature-Optimized Gaussian-Weighted Kernels.” Journal of the Society for Information Display, 2025.

“DGTFNet: Depth-Guided Tri-Axial Fusion Network for Efficient Generalizable Stereo Matching.” IEEE Robotics and Automation Letters, 2025.

“CRAN: Compressed Residual Attention Network for Lightweight Single Image Super-Resolution.” IEEE Signal Processing Letters, 2025.

“Supervised Denoising for Extreme Low-Light Raw Videos.” IEEE Transactions on Circuits and Systems for Video Technology, 2025.

“Query-Vector-Focused Recurrent Attention for Remaining Useful Life Prediction.” IEEE Transactions on Reliability, 2025.

Alessio Fasano | Robotics | Best Researcher Award

Published on by Popular EngineerLeave a Comment on Alessio Fasano | Robotics | Best Researcher Award

Dr Alessio Fasano | Robotics | Best Researcher Award

Research Engineer in Don Carlo Gnocchi Foundation ONLUS at Italy

Alessio Fasano is a dedicated research engineer specializing in biomedical engineering and neurorobotics. Born on June 20, 1991, in Italy, he is currently affiliated with the Fondazione Don Carlo Gnocchi ONLUS, where he focuses on advancing rehabilitation technologies. With a robust academic background, including a Ph.D. in BioRobotics from Scuola Superiore Sant’Anna, Fasano’s work is marked by a commitment to enhancing patient care through innovative robotics and data analysis. He has co-authored numerous peer-reviewed publications and participates actively in international conferences, emphasizing collaboration and research excellence.

Profile

Orcid

Strengths for the Award

  1. Extensive Research Experience:
    • Alessio has a robust background in biomedical engineering and neurorobotics, demonstrated by his roles in prominent projects such as the Human Brain Project and Fit4MedicalRobotics. His ongoing contributions to innovative research in rehabilitation robotics underline his commitment to advancing the field.
  2. Strong Academic Credentials:
    • With a Ph.D. in BioRobotics and multiple degrees with honors from reputable institutions, Alessio showcases a solid academic foundation that supports his research activities. His educational achievements are complemented by a consistent record of excellence.
  3. Publication Record:
    • Alessio has co-authored several impactful publications in peer-reviewed journals, indicating his active engagement in cutting-edge research. His work on postural control in children with movement disorders and rehabilitation protocols after stroke highlights significant contributions to both clinical and theoretical aspects of biomedical engineering.
  4. Technical Proficiency:
    • Proficient in advanced programming (Python, MATLAB), data analysis, and computational modeling, Alessio possesses the technical skills essential for conducting high-level research. His familiarity with neurophysiological signal analysis and machine learning further enhances his research capabilities.
  5. Collaboration and Leadership:
    • His involvement in interdisciplinary projects and collaboration with clinical professionals exemplifies his ability to work effectively within teams. Alessio’s experience in managing projects and supervising students demonstrates his leadership potential.

Areas for Improvement

  1. Broader Networking:
    • While Alessio has a solid publication record, expanding his professional network could enhance his visibility in the global research community. Engaging in more international collaborations may open up additional funding opportunities and broaden the impact of his work.
  2. Grant Writing Experience:
    • Although Alessio has experience in grant applications, further development in this area could strengthen his capacity to secure funding for future projects. Participating in workshops or mentorship programs focused on grant writing could be beneficial.
  3. Public Engagement:
    • Increasing his engagement with public audiences and non-academic stakeholders could enhance the societal impact of his research. Alessio might consider public talks or outreach initiatives to share his findings and promote the importance of rehabilitation technologies.

Education

Alessio Fasano holds a Ph.D. in BioRobotics from Scuola Superiore Sant’Anna, awarded with merits in November 2022. Prior to this, he completed his Master’s in Biomedical Engineering at the University of Naples Federico II in 2018, graduating with top honors (110/110 cum laude). His academic journey began with a Bachelor’s degree in Biomedical Engineering, also from the University of Naples Federico II, where he graduated with the same distinction. Throughout his education, Fasano has developed a strong foundation in robotics, neural systems, and biomedical applications.

Experience

Currently a research engineer at Fondazione Don Carlo Gnocchi ONLUS, Alessio Fasano engages in projects related to robotic rehabilitation. His previous role as a research associate at the Instituto di BioRobotica involved collaboration on significant projects like the Human Brain Project, where he analyzed EEG data and developed neural network models. His earlier experience includes an internship at Maastricht University, focusing on functional magnetic resonance imaging. Throughout his career, Fasano has managed projects, supervised students, and contributed to various research initiatives, emphasizing his commitment to advancing medical technologies.

Research Focus

Alessio Fasano’s research focuses on the integration of robotics in neurorehabilitation, utilizing advanced technologies like EEG and biomechanical modeling to enhance patient recovery. He explores the interplay between human neural systems and robotic interfaces, aiming to develop customized rehabilitation protocols. His work extends to analyzing biomechanical movement patterns and investigating the efficacy of digital rehabilitation tools in clinical settings. Through collaboration on international projects, Fasano seeks to bridge the gap between technology and clinical practice, ultimately improving outcomes for patients with movement disorders.

Publication Top Notes

  • Restoring of Interhemispheric Symmetry in Patients with Stroke Following Bilateral or Unilateral Robot-Assisted Upper-Limb Rehabilitation: A Pilot Randomized Controlled Trial 🤖🧠
  • Rehabilitation with and without Robot and Allied Digital Technologies (RADTs) in Stroke Patients: A Study Protocol for a Multicentre Randomised Controlled Trial on the Effectiveness, Acceptability, Usability, and Economic-Organizational Sustainability of RADTs from Subacute to Chronic Phase (STROKEFIT4) 🏥📊
  • Implementation of a Robot-Mediated Upper Limb Rehabilitation Protocol for a Customized Treatment after Stroke: A Retrospective Analysis 🦾📈
  • Assessment of Postural Control in Children with Movement Disorders by Means of a New Technological Tool: A Pilot Study 👶⚖️
  • Modeling Vestibular Afferents for Neuromorphic Sensing and Eye Movement Control 🧪👁️
  • Maximum Downward Slope of Sleep Slow Waves as a Potential Marker of Attention-Deficit/Hyperactivity Disorder Clinical Phenotypes 💤🧠
  • Reaching and Grasping Movements in Parkinson’s Disease: A Review ✋📖
  • Modeling the Brain and Its Pathologies 🧠🔍
  • Maximum Downward Slopes of Sleep Slow Waves as a Potential Marker of Attention Deficit Hyperactivity Disorder Clinical Phenotypes 💤📉
  • The Neurorobotics Platform: Virtual Bodies for Biologically Realistic Brain Models and Vice Versa 🤖🌐

Conclusion

Alessio Fasano stands out as a candidate for the Best Researcher Award due to his extensive research experience, strong academic background, and impressive publication record. His technical skills and collaborative spirit further bolster his qualifications. By focusing on expanding his network, enhancing grant writing capabilities, and engaging with the public, Alessio can continue to elevate his contributions to biomedical engineering and neurorobotics, ultimately benefiting a wider audience and enhancing his career trajectory.