Prof. Abderrahim Yousfi | Renewable Energy Systems | Renewable Electrical Innovation Award

Published on by Electrical Engineering

Prof. Abderrahim Yousfi | Renewable Energy Systems | Renewable Electrical Innovation Award

Assistant Director | University Mohamed Elbachir Elibrahimi of Borj Bou Arréridj | Algeria

Dr. Abderrahim Yousfi is a Professor of Electronics specializing in micro-electronics at the University of Mohamed El Bachir El Ibrahimi, Algeria, within the Institute of Electronics and Telecommunications, where he holds senior academic and research leadership responsibilities. He earned bachelor’s, engineering, master’s, and doctoral degrees in electronics and micro-electronics, with advanced specialization in instrumentation and academic qualification accreditation. His professional experience includes postgraduate teaching and supervision, leadership of academic departments and research teams, coordination of scientific programs, and active involvement in international collaborations and conferences. His research focuses on perovskite solar cells, semiconductor device modeling, photovoltaic and optoelectronic materials, thin-film electronics, nanoelectronics, and numerical simulation, resulting in 35 scholarly publications with 352 citations and an h-index of 10. His academic profile is further strengthened by recognitions for scholarly contributions, extensive peer-review and editorial service for high-impact journals, and active membership in international scientific communities.

Citation Metrics (Scopus)

352
35
30
25
20
15
10
0

Citations

352

Documents

35

h-index

10

Citations

Documents

h-index

View Scopus Profile View Google Scholar

View ResearchGate View ORCID Profile

Featured Publications

An Optimized Design of 10-nm-Scale Dual-Material Surrounded Gate MOSFETs for Digital Circuit Applications
F. Djeffal, N. Lakhdar, A. Yousfi
Physica E: Low-Dimensional Systems and Nanostructures · Highly Cited

Current-Voltage Analytical Model and Multi-Objective Optimization of a Short-Channel Gate-All-Around Junctionless MOSFET
F. Pezzimenti, H. Bencherif, A. Yousfi, L. Dehimi
Solid-State Electronics · High-Impact Journal

Revealing the Secrets of High-Performance Lead-Free CsSnCl₃-Based Perovskite Solar Cells Using DFT and SCAPS-1D
O. Saidani, A. Yousfi, D. P. Samajdar, X. Xu, et al.
Solar Energy Materials and Solar Cells · Top-Tier Journal

Improved InₓGa₁₋ₓP/GaAs/Ge Tandem Solar Cell Using Light-Trapping Engineering and Multi-Objective Optimization
H. Bencherif, L. Dehimi, F. Pezzimenti, A. Yousfi, et al.
Optik · Advanced Photovoltaic Design

Analytical Model for Light-Trapping Effects in ZnO:Al/c-Si/SiGe/c-Si Solar Cells with Optimized Design
H. Bencherif, L. Dehimi, F. Pezzimenti, A. Yousfi
International Conference on Applied Smart Systems

Mr. Jufeng Han | Materials Informatics | Best Researcher Award

Published on by Electrical Engineering

Mr. Jufeng Han | Materials Informatics | Best Researcher Award

Master | Institute of Semiconductors | China

Dr. Jufeng Han, currently pursuing a Master’s degree in Artificial Intelligence for Science at the Institute of Semiconductors, Chinese Academy of Sciences, is an emerging researcher specializing in materials informatics and semiconductor and optoelectronic materials. His academic foundation combines advanced studies in artificial intelligence with applications in materials science, focusing on the integration of data-driven modeling with physical principles. Professionally, he has contributed to innovative research projects, most notably the development of a symbolic–neural hybrid modeling framework for perovskite bandgap prediction—an approach that enhances accuracy and interpretability in photovoltaic material screening. His work has been recognized with a Best Paper Candidate nomination and publication acceptance in Materials Today Energy. Beyond research, he collaborates within interdisciplinary teams at the Institute of Semiconductors, demonstrating leadership in bridging AI methodologies with materials discovery. His research contributions have strengthened the role of AI in accelerating semiconductor innovation, particularly in energy-efficient and sustainable technologies. He is a member of the Association for the Advancement of Artificial Intelligence (AAAI) and maintains a strong academic presence through his Google Scholar profile. Jufeng Han’s combination of technical expertise, academic excellence, and forward-looking research vision positions him as a promising scholar in AI-driven materials science and a deserving nominee for the Best Researcher Award.

Profile: Scopus

Featured Publications

Han, Jufeng*, Bandgap prediction for perovskite materials based on symbolic–neural hybrid modeling. Materials Today Energy, Accepted.

Han, Jufeng*, Symbolic–neural hybrid framework for enhanced interpretability and accuracy in perovskite bandgap prediction. Institute of Semiconductors, Chinese Academy of Sciences, In production.

Han, Jufeng, AI-driven modeling approaches for semiconductor and optoelectronic material discovery. AI for Science Research Series, Under review.

Dr. Swarup Ghosh | Energy Harvesting & Self-Powered Systems | Best Researcher Award

Published on by Electrical Engineering

Dr. Swarup Ghosh | Energy Harvesting & Self-Powered Systems | Best Researcher Award

Assistant Professor | SR University | India

Dr. Swarup Ghosh is an Assistant Professor and Assistant Dean (Research) at the School of Computer Science and Artificial Intelligence, SR University, specializing in computational materials science, condensed matter physics, and AI-driven materials discovery. He earned his Ph.D. in Science from Jadavpur University with a focus on first-principles calculations, following an M.Sc. in Physical Sciences and a B.Sc. in Physics. Dr. Ghosh previously served as a Postdoctoral Research Associate at Jadavpur University and as a faculty member at Sammilani Mahavidyalaya, contributing to advanced computational materials research and student mentorship. His work spans density functional theory, molecular dynamics, many-body perturbation theory, electronic structure simulations, and machine-learning-enabled materials design, resulting in publications in high-impact journals and presentations at prestigious scientific forums. His research includes breakthroughs in 2D and nanomaterials, thermoelectrics, photovoltaics, spintronics, and catalytic systems, emphasizing data-centric scientific innovation. He has been honored with national research fellowships, merit-based academic distinctions, and awards for research excellence, while also serving as a reviewer for reputed international journals and participating in professional training programs and conferences. He maintains a strong scholarly impact, demonstrated by 245 citations, an h-index of 9, and an i10-index of 9, underscoring his growing influence in computational materials science and interdisciplinary research.

Profile: Google Scholar

Featured Publications

Swarup Ghosh*, Predicting photovoltaic efficiency of two-dimensional Janus materials for solar energy harvesting: A combined first-principles and machine learning study. Solar Energy Materials and Solar Cells, Accepted.

Swarup Ghosh*, First-principles study on structural, electronic, optical and photovoltaic properties of Sc₂C-based Janus MXenes for solar cell applications. Materials Today Communications, Accepted.

Swarup Ghosh, Predicting band gaps of ABN₃ perovskites: An account from machine learning and first-principles DFT studies. RSC Advances, Accepted.