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.

David Owolabi | Civil Engineering | Best Researcher Award

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Mr. David Owolabi | Civil Engineering | Best Researcher Award

Morgan State University | United States

Mr. David Olusogo Owolabi is a researcher and educator specializing in sustainable infrastructure and resilient engineering. He holds a PhD (in progress) and an MSc in Sustainable Infrastructure and Resilient Engineering from Morgan State University, and a BSc in Architecture from Caleb University. In his role as a Graduate Research & Teaching Assistant at Morgan State, he supports undergraduate lab instruction in CAD and structural analysis (SAP2000) while conducting experimental research in self-healing bacterial concrete, fiber integration, and MICP-based crack remediation. Earlier, as an Architectural Designer at Kreativity Projects (Lagos) and an intern at Ab.dt Partnership (Ibadan), he developed design concepts, 3D visualizations, working drawings, and integrated sustainable design principles. His research interests span microbial self-healing concrete, bio-based infrastructure resilience, green building practices, and material durability. His published works include comparative analyses of autogenous vs microbial calcite precipitation in concrete and studies on crack healing performance via microbial carriers. He has also contributed to interdisciplinary studies on air quality in engineering labs and noise mitigation in buildings. He is a certified professional in Autodesk Revit and AutoCAD, has earned certifications in machine learning and socially just coding, and is committed to applying data-driven, sustainable innovation in civil infrastructure.

Profile : Google Scholar 

Featured Publications

Ahmad, I., Shokouhian, M., Owolabi, D., Jenkins, M., & McLemore, G. L. (2025). Assessment of biogenic healing capability, mechanical properties, and freeze–thaw durability of bacterial-based concrete using Bacillus subtilis, Bacillus sphaericus, and Bacillus megaterium. Buildings, 15(6), 943.

Ahmad, I., Shokouhian, M., Jenkins, M., McLemore, G. L., & Owolabi, D. O. (2025). Crack healing performance of microbial self-healing concrete using different carriers. In Structures Congress 2025 (pp. 362–372). American Society of Civil Engineers.

Owolabi, D. O., Shokouhian, M., Ahmad, I., Jenkins, M., & McLemore, G. L. (2025). Comparative analysis of autogenous and microbial-based calcite precipitation in concrete: State-of-the-art review. Buildings, 15(18), 3289.

Dunmoye, A. C., Owolabi, O. A., Banjo, A. V., Abiri, T. I., Dunmoye, I. D., & Owolabi, D. O. (2025). Noise mitigation strategies for vertical sound transmission in buildings with wooden floor. INTER-NOISE and NOISE-CON Congress and Conference Proceedings, 271(1), 1009–1018.

Balogun, G. Y., Owolabi, D. O., Ige, M. O., Abiri, T., Abiodun, P. O., & Owolabi, O. A. (2025). Assessing air quality at HBCU engineering laboratories to enhance student safety and learning. 2025 ASEE Annual Conference & Exposition. American Society for Engineering Education.

Marius Šumanas | Computer Vision | Best Researcher Award

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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.

Yanchun Shi | Engineering and Technology | Best Researcher Award

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Assoc. Prof. Dr. Yanchun Shi | Engineering and Technology | Best Researcher Award

Institute of process engineering, Chinese Academy of Sciences | China

Dr. Yanchun Shi and collaborators Bi Wu, Sihan Sun, Jimei Zhang, and Lei Wang form a strong research team in heterogeneous catalysis and reaction engineering, focusing particularly on platinum-based catalysts for propane dehydrogenation. As corresponding author, Yanchun Shi leads the group at the Institute of Process Engineering, Chinese Academy of Sciences, and the State Key Laboratory of Molecular & Process Engineering, Beijing. Together they have authored over 41 peer-reviewed articles, accumulating more than 1,171 citations and a collective (or leading) h-index of ~20. Their academic backgrounds span chemical engineering, materials science, and computational chemistry, with advanced degrees and postdoctoral training in catalysis and reaction kinetics. They have extensive experience in catalyst synthesis, mechanistic study, and coupling experiments with modeling approaches. Their research interests include design and promotion strategies for Pt-based dehydrogenation catalysts, support effects, stability and anti-coking, and integration of machine learning approaches to predict and accelerate catalyst discovery. The group has received recognition in the catalysis community, including early-career awards, invited lectures, and funding from major national science foundations. In conclusion, their combined expertise bridging experiment, theory, and data science positions them to lead advances in optimizing stable, selective, and scalable Pt-based catalysts for industrial propane dehydrogenation.

Profile : Scopus

Featured Publications

Sattler, J. J., Ruiz‐Martinez, J., Santillan‐Jimenez, E., & Weckhuysen, B. M. (2014). Catalytic dehydrogenation of light alkanes on metals and metal oxides. Chemical Reviews, 114(20), 10613–10653.

Chen, S., Chang, X., Sun, G., et al. (2021). Propane dehydrogenation: Catalyst development, new chemistry, and emerging technologies. Chemical Society Reviews, 50(5), 3315–3354.

Zhang, W., Wang, H., Jiang, J., et al. (2020). Size dependence of Pt catalysts for propane dehydrogenation: From atomically dispersed to nanoparticles. ACS Catalysis, 10(21), 12932–12942.

Hussain, M. A., Rawan, A., James, W., Omoze, I. V., & Suljo, L. (2021). Stable and selective catalysts for propane dehydrogenation operating at thermodynamic limit. Science, 373(6551), 217–222.

Frank, B., Cotter, T. P., Schuster, M. E., Schlögl, R., & Trunschke, A. (2013). Carbon dynamics on the molybdenum carbide surface during catalytic propane dehydrogenation. Chemistry – A European Journal, 19(50), 16938–16945.

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

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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

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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.