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Bongjin KimView profile

Associate Professor

• Secure Hardware Design
• Machine Learning
• Data Mining
• +6 more

Prof. Bongjin Kim is an Associate Professor in the School of Electrical Engineering at KAIST. Previously, he held a position as Assistant Professor at UCSB. His research focuses on secure hardware design, machine learning, and alternative computing architectures, including Ising machines and processing-in-memory systems. He leads the Kim Circuit Research Lab, which designs novel VLSI circuits for AI, robotics, and optimization problems. Education: PhD, University of Minnesota (ECE); MS, Pohang University of Science and Technology (ECE). He has advised over 20 graduate and undergraduate students, with notable advisees including Dr. Jooyoung Bae (PhD 2025) and Dr. Yihao Wu (PhD 2025). His work has been recognized with awards such as the NSF CAREER Award (2023) and the NRF Outstanding Young Scientist Grant (2025). Recent research includes developing a 28nm Ising machine for combinatorial optimization (A-SSCC 2024), a scalable bit-serial accelerator for PDEs (TCAS-I 2024), and a reconfigurable compute-in-memory macro (JSSC 2024). He serves on technical committees for ISSCC, A-SSCC, and ESSERC, and chairs sessions at ESSERC 2025 and A-SSCC 2025. Lab activities include the Basic Research Lab (NRF-funded) for Ising Foundation Model development and the C2 research project on ML ASIC accelerators. His group collaborates with institutions like SLAC, IME (A*STAR), and KAIST, fabricating over 30 test chips using 28nm/65nm processes.

Lijun JiangView profile

Professor

• Electromagnetics
• Electromagnetic Compatibility (EMC)
• Signal Integrity
• +5 more

Dr. Lijun Jiang is the Kummer Endowed Professor at the Department of Electrical and Computer Engineering, Missouri University of Science and Technology. He holds a Ph.D. from the University of Illinois at Urbana-Champaign (2004) and has extensive industry and academic experience. He is an IEEE Fellow and ACES Fellow, recognized with awards including the IEEE Technical Achievement Award and IBM Research Technical Achievement Award. Education: Ph.D. in Electrical and Computer Engineering, University of Illinois at Urbana-Champaign, USA M.S. in Electrical Engineering, Tsinghua University, China B.S. in Electrical Engineering, Beijing University of Aeronautics and Astronautics, China Research interests focus on electromagnetic modeling, high-speed electronic design, machine learning for signal/power integrity, microwave materials, and optics. His work bridges theoretical advancements with practical applications in antenna engineering and EDA solutions. Awards include IEEE Fellow (2019), ACES Fellow (2019), and the World’s Top 1% Scholar by ESI (2018). His recent research explores data-driven frameworks for electromagnetic near-field scanning and MIMO channel sounding. Key contributions include patents in antenna design and methodologies for electromagnetic compatibility. He has authored books on electromagnetic modeling and contributed chapters on metamaterials and angular momentum engineering.

Omid ChatrabgounView profile

Assistant Professor

• Uncertainty Quantification
• Bayesian Machine Learning
• Gaussian Processes
• +5 more

Dr. Omid Chatrabgoun serves as an Assistant Professor in Data Science and AI at the CEES School of Science, holding a PhD in Data Science from Shahid Chamran University (Iran, 2015). Previously affiliated with Malayer University, he teaches undergraduate and postgraduate courses including Statistical Learning, Data Science, and Machine Learning while actively supervising PhD students. His research focuses on uncertainty quantification and Bayesian machine learning for complex systems. Education: PhD in Data Science, Shahid Chamran University, Iran (2015) Dr. Chatrabgoun specializes in Modelling, Optimization, and Uncertainty Quantification (UQ) using (Deep) Gaussian processes, with applications spanning bioinformatics (Gene Regulatory Networks, Protein-Protein Interactions) and environmental engineering (coastal protection, flood modeling). He develops novel approaches for machine learning of linear operational equations to quantify uncertainty in highly complex systems, emphasizing computational efficiency through sparse approximations and kernel methods. His work bridges theoretical statistics with practical implementations in healthcare, environmental science, and industrial applications. Analysis of his 29 publications (2016-2025) reveals a consistent trajectory in Gaussian process methodologies, evolving from foundational graphical models to advanced deep Gaussian processes and probabilistic surrogate modeling. Key thematic clusters include bioinformatics network inference, environmental risk assessment, and computational optimization techniques, demonstrating interdisciplinary impact across computer science, statistics, and domain-specific applications. Dr. Chatrabgoun has secured research funding and conducted consultancy projects with the Iran National Science Foundation (INSF) and Research Institute for Grapes and Raisin (RIGR). His collaborative network spans international institutions, as evidenced by co-authorships across civil engineering, bioinformatics, and environmental science domains. Current projects involve developing machine learning frameworks for linear differential operators and expanding applications of pair-copula Bayesian models in high-dimensional data analysis. His research group actively explores uncertainty propagation in PDE-based models and spatio-temporal environmental simulations, maintaining strong industry-academia partnerships for knowledge exchange in data-driven decision systems.

Stavros V. GeorgakopoulosView profile

Professor

• Wireless power transfer
• Novel Antennas
• Wearable antennas and body-centric wireless communications
• +9 more

Stavros V. Georgakopoulos is a Professor in the Department of Electrical & Computer Engineering at Florida International University (FIU), part of the College of Engineering. His research focuses on antennas, wireless systems, and computational electromagnetics, with particular expertise in reconfigurable antennas, RFID, and aerospace applications. Education: Ph.D. in Electrical Engineering, Arizona State University (2001) M.S. in Electrical Engineering, Arizona State University (1998) B.S. in Electrical Engineering, University of Patras, Greece (1996) Teaching: Courses include Antennas for Wireless Communication Systems, RF Circuit Design, Digital Communication Systems, and Wireless Communication with Multimedia Applications. Research Interests: Stavros specializes in novel antenna designs, wearable antennas, computational electromagnetics, and electromagnetic compatibility. His work addresses challenges in aerospace systems, wearable technology, and high-frequency antenna applications. Labs & Affiliations: He leads the Transforming Antennas Center, advancing innovations in antenna technology for modern communication systems. His research integrates advanced simulation techniques like FDTD with practical measurement validations.

Amanda HoltView profile

Researcher

• Biophysics
• Optical Physics
• Marine Biology
• +3 more

Amanda Holt is an Associate Research Scientist in Alison Sweeney’s lab at Yale University’s Department of Physics. She holds a B.A. in Physics and Music from Bard College and a Ph.D. in Physics from the University of California, Santa Cruz. Her research focuses on biophysics and optical systems in marine organisms, particularly studying light interactions with biological structures in squids, giant clams, and deep-sea creatures. She employs experimental and computational methods such as Monte Carlo modeling, micro-probe radiometry, and finite-difference time-domain simulations to analyze optical phenomena in natural systems. Key research contributions include modeling light reflectance in squid eyes, optimizing photon transport in giant clams, and designing bio-inspired light-guiding systems. Holt’s work bridges marine biology, optics, and materials science, with applications in renewable energy and biomimetic engineering. She has published extensively on topics like symbiotic solar flux optimization, midwater camouflage mechanisms, and photonic structures in marine animals. Her awards include the GAANN Fellowship (2005-2007) and Excellence at Equal Cost Scholarship (1997-2001). Beyond academia, Holt champions science education through her role as lead coordinator for Brook Knoll Elementary’s science fair, emphasizing inclusivity for underrepresented students. She regularly engages with K-12 classrooms as a guest speaker, integrating her research to inspire future scientists. Holt collaborates closely with multidisciplinary teams, advancing understanding of biological optical systems while addressing broader societal needs like sustainable energy solutions. Her current projects focus on refining Monte Carlo models for cellular light scattering and developing experimental techniques to quantify optical properties in marine tissues.

• Microwave Imaging
• Biomedical Engineering
• Computational Electromagnetics
• +7 more

Moein Movafagh is an Hourly Paid Lecturer in the Department of Electrical and Electronic Engineering at the University of Bradford, Faculty of Engineering and Informatics. He completed his PhD in Electrical and Electronic Engineering in 2023 and continues to contribute actively to research in microwave imaging and biomedical signal processing. His research focuses on the integration of electromagnetic principles—particularly Huygens’ Principle—and advanced computational methods such as the Finite-Difference Time-Domain (FDTD) technique, combined with deep learning, to develop non-invasive stroke detection systems. His work lies at the intersection of electrical engineering, medical diagnostics, and artificial intelligence. The recent publications highlight a strong trend toward radar-based brain imaging, leveraging synthetic aperture radar (SAR) and FMCW technologies enhanced by neural networks for accurate classification of strokes. These efforts aim to provide low-cost, portable, and rapid diagnostic tools for emergency healthcare settings. Contributor to UN Sustainable Development Goals (specific goals not listed) Movafagh has co-authored multiple peer-reviewed articles and conference papers, primarily in collaboration with researchers including M. Ghavami, G. Tiberi, and S. Dudley-McEvoy. While no formal advising or grant information is available, his active publication record suggests ongoing research engagement. His work is associated with the Bioscience and Bioengineering Research Centre at the university.

Funda Akleman YaparView profile

Professor

• Electromagnetic Engineering
• Microwave Technologies
• Antenna Design
• +3 more

Prof. Dr. Funda Akleman Yapar is a faculty member at the Department of Electronics and Communication Engineering , Istanbul Technical University , holding the Professor rank. She currently serves as Vice Dean (2023–2026) and previously held administrative roles including Deputy Head of Department (2020–2023). Her academic career spans 25 years at the same institution, starting as a Research Assistant in 1997. PhD in Electronics and Communication Engineering (1998–2002), Istanbul Technical University Her research focuses on electromagnetic engineering , microwave technologies , and antenna systems , with recent work on: 6G high-altitude platform antenna design Microwave metamaterials for solar cells Waveguide filter synthesis via inverse problems Radio propagation analysis in solar-affected stratospheric channels She has 50+ research outputs, including journal articles and conference papers, and leads projects like Three-Dimensional Radio Wave Propagation Analysis on Perfect Conductor Rough and Smooth Terrain (2014–2020). Her methodological expertise includes finite-difference time-domain (FDTD), parabolic equation (PE) modeling, and generalized scattering matrix techniques.

Peter D. MinevView profile

Professor

• Computational Fluid Dynamics
• Numerical Analysis
• Fluid-Structure Interaction
• +4 more

Peter D. Minev is a Professor in the Department of Mathematical and Statistical Sciences at the University of Alberta, Canada. His research specializes in computational fluid dynamics, numerical methods for partial differential equations (PDEs), and large-scale simulations for scientific and engineering problems. He develops advanced algorithms for incompressible Navier-Stokes equations, fluid-structure interaction, multiphase flows, and magnetohydrodynamics (MHD). Education: MSc and PhD from Sofia University, Bulgaria. Research Focus: Minev's work spans: High-order time-stepping schemes and splitting methods for complex PDEs Fictitious domain approaches for fluid-structure interaction Parallel algorithms for supercomputing applications Modeling of multiphysics phenomena (e.g., porous media flows, phase-field equations) He has created benchmark results for 3D lid-driven cavity flows and simulations of particle sedimentation/bubble dynamics. Publications: His recent articles (2014–2021) focus on: Efficient splitting schemes for stress/vorticity formulations High-order adaptive time integration Algorithms for spherical/heterogeneous geometries Applications in fuel cells, geophysics, and biomechanics A consistent theme is minimizing computational complexity while maintaining accuracy.

Stuart PorterView profile

Senior Lecturer

• Antennas
• Computational Electromagnetics
• Electromagnetic Compatibility
• +5 more

Dr. Stuart Porter is a Senior Lecturer in the Department of Electronic Engineering at the University of York. He holds roles including Chair of the Staff Student Liaison Committee and co-ordinator for SWENG and 3rd-year projects. His research focuses on computational electromagnetics, antenna design, electromagnetic compatibility (EMC), and the application of evolutionary algorithms to engineering problems. Education: BSc (Hons), DPhil (PhD). Research interests span antennas, computational electromagnetics, EMC design tools, and health effects of electronic equipment. He has contributed to projects such as optimizing antenna designs, modeling electromagnetic fields in enclosures, and assessing RF exposure from mobile devices. Publications emphasize advancements in numerical methods (e.g., FDTD, TLM), antenna engineering, and EMC simulation tools. His work bridges theoretical models with practical applications in aerospace and telecommunications.

• Machine Learning
• Computer Vision
• Signal Processing
• +3 more

Chenguang Liu is a researcher at Institut Polytechnique de Paris , France, with a focus on computational methods, machine learning, and control systems. His work bridges theoretical and applied research across multiple domains including computer vision, signal processing, and operations research. Key research areas: Machine Learning, Computer Vision, Computational Physics, Control Theory Notable publication trends: Develops novel algorithms for parallel computing, peridynamic modeling, and real-time systems Recent contributions include Bayesian neural networks for gas-bearing prediction, multi-agent reinforcement learning for UAV swarms, and domain adaptation techniques in object detection. He collaborates extensively with researchers in electrical engineering and applied mathematics disciplines.

Marlis HochbruckView profile

Professor

• Numerical Analysis
• Time Integration of PDEs
• Numerical Methods for Differential Equations
• +6 more

Professor Marlis Hochbruck is a distinguished faculty member at the Karlsruhe Institute of Technology (KIT), where she serves as Head of the Numerical Analysis Working Group within the Faculty of Mathematics and the Institute for Applied and Numerical Mathematics. Her office is located at Englerstraße 2, 76131 Karlsruhe, Germany, in the Kollegiengebäude Mathematik (20.30), room 3.001. She is actively involved in teaching and research, with courses scheduled through Summer Semester 2025. Her research interests span a wide range of topics in numerical analysis, with a particular focus on time integration methods for partial differential equations , wave equations , Maxwell's equations , and exponential integrators . Her work bridges theoretical numerical analysis with practical computational methods, addressing challenges in computational mathematics and scientific computing. Professor Hochbruck has developed and analyzed numerous numerical schemes that maintain stability and accuracy for complex wave phenomena and electromagnetic simulations. Professor Hochbruck's publications demonstrate a consistent focus on advancing numerical methodologies for time-dependent PDEs. Her recent work shows increasing attention to specialized applications including quantum mechanics (Schrödinger equation), electromagnetic scattering, and nonlinear wave phenomena. She frequently collaborates with researchers across multiple institutions, particularly within the CRC 1173 framework at KIT, which focuses on wave phenomena. Professor Hochbruck has supervised numerous doctoral students who have completed dissertations on topics related to numerical methods for wave equations, exponential integrators, and time integration schemes. Her academic lineage includes researchers who have made significant contributions to computational mathematics. Her teaching portfolio is extensive and consistent, covering core numerical mathematics courses as well as specialized seminars on numerical methods for differential equations, time integration, and wave phenomena. She has taught continuously from Winter Semester 2010/11 through Summer Semester 2025, demonstrating sustained academic engagement.

• Electromagnetic Fields
• Wireless Communication Systems
• Quantum Computing Applications
• +3 more

Prof. Franco Moglie is an Associate Professor at the Department of Information Engineering of the University of Marche Polytechnic (UNIVPM). His research focuses on electromagnetic field theory, wireless communication systems, quantum computing applications, and bioelectromagnetics. He leads projects on reverberation chamber analysis, reconfigurable intelligent surfaces, and FDTD simulations. His work spans topics like 5G signal propagation, quantum optimization for wireless networks, and electromagnetic shielding materials. He actively contributes to IEEE standards for stochastic radiator characterization and has pioneered chaotic chamber designs for enhanced testing environments. Research interests include advanced FDTD simulations for complex cavities, time-reversal techniques for biomedical applications, and the development of composite materials for electromagnetic shielding. He collaborates with industry and academia on projects involving 5G infrastructure testing, quantum computing for electromagnetic problems, and bioelectromagnetic safety assessments. Recent publications highlight innovations in quantum algorithms for waveguide simulations, experimental validations of 5G systems in reverberation chambers, and statistical analysis of shielding effectiveness. His work bridges theoretical electromagnetics with practical applications in telecommunications and medical engineering.

• Exploration Geophysics
• Electromagnetic Exploration
• Electric Exploration
• +7 more

Takumi Ueda is a Professor at Waseda University 's School of Creative Science and Engineering , affiliated with the Waseda Research Institute for Science and Engineering (2024-2026). He holds a Ph.D. in Geophysics (2007) from the University of Utah and an M.Eng. in Electrical Exploration (2002) from Waseda University. Education: Ph.D. (Geophysics) - University of Utah (2007) M.Eng. (Engineering) - Waseda University (2002) B.Eng. (Science and Engineering) - Waseda University (2000) His research focuses on Exploration Geophysics and Electromagnetic (EM) Methods , particularly for marine and UAV-based geophysical surveys . Key contributions include: Developing drone-borne EM systems for buried object detection Advancing 3D holographic imaging techniques in marine CSEM Optimizing continuous wavelet transforms for MT data processing Innovating vertical electrode configurations for sub-seafloor resistivity sensing His 15 most recent publications (2006-2023) demonstrate expertise in electromagnetic exploration , inverse problem solving , and UAV applications for geophysical monitoring. Collaborative work spans institutions including the National Institute of Advanced Industrial Science and Technology (2002-2017) and the University of Utah . Professional engagements include: Leadership roles in the Physical Exploration Society (2010-present) Membership in the Society of Exploration Geophysicists and Japan Society of Computational Methods in Engineering Participation in technical committees for CCS monitoring and geophysical software development

Piet DemeesterView profile

Professor

• Optical Communication Networks
• Wireless Communication Systems
• Networked Intelligence
• +3 more

Piet Demeester is a Full Professor at the Faculty of Engineering and Architecture, Ghent University, and serves as Director of the IDLab-Department (imec/UGent/UA). His research spans optical and wireless communication networks, networked intelligence, and electromagnetic field exposure analysis. Key affiliations: Ghent University, University of Antwerp, imec Labs: IDLab (350+ researchers focusing on optical/wireless networks, cloud infrastructures, AI for robotics) His work includes foundational contributions to ultra-high-capacity wireless networking under the ERC Advanced Grant "ATTO." Scientific awards include IEEE Fellowship (2009). Publications demonstrate technical leadership in 5G/6G architectures, analog radio-over-fiber systems, and human EMF exposure modeling. Major research themes Optical/Wireless Network Integration Millimeter-Wave Communication Exposure Assessment Methodologies Photonic Antenna Systems Notable collaborations include leadership in European testbed federations like Fed4fire and co-development of standards for networked intelligence.

George A. GravvanisView profile

Professor

• Computational Methods
• Mathematical Modeling
• Parallel Computing
• +10 more

Dr. George A. Gravvanis is a Professor of Applied Mathematics and Numerical Computations at the Department of Physics and Applied Mathematics, Democritus University of Thrace. He also serves as Coordinator and SEP Member for Thematic Units at the Hellenic Open University. B.Sc. (1982) in Science (Joint Honours), University of Salford B.A. (1986), Mathematics, National and Kapodistrian University of Athens M.Sc. (1984), Numerical Analysis, Brunel University PhD (1992), Computer Science, Athens University of Economics and Business His research focuses on computational and numerical methods, including Mathematical Modeling , Parallel Algorithmic Design , Numerical Algorithms , Sparse Matrix Techniques , and PDE Solvers . He integrates these into Mathematical Software and Computer Science Mathematics . Recent article trends highlight his work in Sparse Regression for data imputation, Hybrid Multi-Projection Methods for distributed systems, and Unified Transform Techniques for PDEs. Subfields span High-dimensional Data , GPU Clusters , and Self-Organizing Clouds . He has taught undergraduate courses in Mathematical Software , Applied Numerical Analysis , and Scientific Calculations . He has coordinated research projects such as the CloudLightning initiative under Horizon 2020. His editorial contributions include roles on international journal boards and special edition editing. Dr. Gravvanis has reviewed for major academic organizations and journals, including ACM Computing Reviews and Mathematical Reviews (AMS) . His career spans academic roles and technical positions in national and EU social security informatics.