Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award

Published on by Electrical Engineering

Dr. Angel Sapena Bano | Modelling Machines for Optimization | Research Excellence Award

Associate Professor | Universitat Politecnica de Valencia | Spain

Ángel Sapena Bañó, Profesor Titular at the Universitat Politècnica de València, is a specialist in electrical engineering with expertise in electrical machines, diagnostic methods, numerical modelling, and condition monitoring. He holds degrees in Industrial Engineering, Energy Technology for Sustainable Development, and Secondary Education, complemented by a doctorate in Industrial Engineering focused on advanced diagnostic techniques for electrical machines. His professional trajectory includes roles as Lecturer, Researcher, and Technical Specialist, contributing to major academic initiatives, laboratory modernization, and collaborative research activities. He has participated in multiple competitive and industrial R&D projects, developed fault-diagnosis tools for induction machines and wind-energy systems, and strengthened international cooperation through research stays and Erasmus teaching engagements. His research spans analytical and hybrid modelling, finite-element methods, machine-learning-based diagnostics, and real-time simulation, reflected in numerous high-impact journal articles, conference contributions, book chapters, and patented inventions. He has led and co-led research outputs as first and corresponding author, supervised a wide range of graduate projects, and contributed to organizing scientific conferences and special issues. His distinctions include recognized research merits, invited reviewer roles in indexed journals, participation in prominent research groups, and involvement in impactful national and international scientific initiatives. His scholarly record includes 1,035 citations, 60 documents, and an h-index of 17.

Profiles: Scopus | ORCID

Featured Publications

Ángel Sapena Bañó*, Model-based diagnostic techniques for induction machines under transient operational conditions. Int. J. Electr. Power Energy Syst., Accepted.

Ángel Sapena Bañó*, Hybrid FEM–analytical modelling framework for efficient fault detection in eccentric induction motors. Sensors, 2025, 25, 1–28.

Ángel Sapena Bañó, Deep learning–enhanced condition monitoring strategies for electrical machines operating in variable regimes. Mathematics and Computers in Simulation, 2025, 1–28.

Prof. Dr. Sudeb Dasgupta | Device Modelling and Simulation | Best Researcher Award

Published on by Electrical Engineering

Prof. Dr. Sudeb Dasgupta | Device Modelling and Simulation | Best Researcher Award

Professor | IIT Roorkee | India

Dr. Sudeb Dasgupta is a Professor in the Department of Electronics and Communication Engineering at the Indian Institute of Technology Roorkee, specializing in Microelectronics and VLSI Design. He earned his Ph.D. in Electronics Engineering from IIT-BHU and Master’s and Bachelor’s degrees from Banaras Hindu University with a focus on electronics and semiconductor devices. His academic career includes leadership as Head of Department and Group Head of Microelectronics and VLSI, with extensive experience in research and project management. Dr. Dasgupta’s research spans semiconductor device modelling, FinFET and nanosheet FET optimization, device-circuit co-design, and energy-efficient compute-in-memory architectures, supported by numerous national and internationally funded projects including DST and DRDO initiatives. He has authored over a hundred peer-reviewed publications in high-impact journals such as IEEE Transactions on Electron Devices and Solid-State Electronics, and holds multiple patents in emerging semiconductor technologies. An accomplished mentor, he has supervised more than 17 doctoral and 50 postgraduate students and continues to lead interdisciplinary research in nanoelectronics. Dr. Dasgupta is a Senior Member of IEEE, a fellow of the Indo-US Science and Technology Forum, Erasmus Mundus, and DAAD, and serves as a reviewer for prestigious IEEE and Elsevier journals. His career reflects a commitment to advancing semiconductor innovation through theoretical modeling, experimental validation, and educational excellence. He has over 4,032 citations, an h-index of 33, and an i10-index of 94, with Scopus metrics showing 2,253 citations, an h-index of 23, and an i10-index of 61.

Profile: Google Scholar 

Featured Publications

Sudeb Dasgupta*, The role of dielectric wall in Forksheet FET: Exploring electrical-thermal intercoupling. IEEE Trans. Dielectr. Electr. Insul., 2025.

Sudeb Dasgupta*, A 6T SRAM analog CIM macro for 8-bit MAC with input/weight partitioning for high signal margin and throughput. IEEE APCCAS Conf., 2025.

Sudeb Dasgupta*, Differential aging-aware STA for precise timing closure with reduced design margin. IEEE Trans. Device Mater. Reliab., 2025.

Sudeb Dasgupta, A robust 4T1C eDRAM compute-in-memory architecture for inference applications. IEEE NEWCAS Conf., 2025.