جست‌وجوی استاد و پژوهشگر

Constantin Bacutaمشاهده پروفایل

استاد

• Numerical Methods for PDEs
• Finite Element Methods
• Singularly Perturbed Boundary Value Problems
• +۶ مورد دیگر

Constantin Bacuta is a Professor in the Department of Mathematical Sciences at the University of Delaware, College of Arts & Sciences. He holds a Ph.D. in Mathematics from Texas A&M University (2000), an M.S. from Alexandru Ioan Cuza University (Romania), and has held postdoctoral positions at Pennsylvania State University and Lawrence Livermore National Laboratory. His research focuses on numerical methods for PDEs, finite element methods, singularly perturbed problems, iterative methods, and subspace interpolation techniques. His expertise spans advanced numerical discretization techniques, including finite element and finite difference methods for convection-diffusion problems, multigrid methods, and saddle point formulations. He has published extensively in computational mathematics, with over 50 peer-reviewed articles in journals like Computer Methods in Applied Mathematics , SIAM Journal on Numerical Analysis , and Journal of Computational and Applied Mathematics . Bacuta teaches graduate and undergraduate courses in numerical analysis, functional analysis, and computational mathematics, including MATH 817 (Numerical Approximation of PDEs), MATH 611 (Introduction to Numerical Discretization), and MATH 838 (Finite Elements and Boundary Element Methods). His work emphasizes rigorous mathematical foundations alongside computational implementation, with contributions to preconditioning strategies and error analysis in non-conforming discretizations.

Lauri Saviojaمشاهده پروفایل

استاد

• Room Acoustics
• Virtual Reality
• Auditory Displays
• +۵ مورد دیگر

Prof. Lauri Savioja is a full-time Professor and Head of the Department of Computer Science at Aalto University. His research focuses on room acoustics, virtual reality, and auditory displays, conducted within the Aalto Acoustics Lab—a multidisciplinary facility for sound-related research. He holds Fellowships from the Audio Engineering Society and Acoustical Society of America, and is an IEEE Senior Member. His work contributes to UN Sustainable Development Goals through advancements in audio engineering and immersive technologies. Education: Doctoral degree in Engineering and Technology (1999), Helsinki University of Technology Licentiate degree in Engineering and Technology (1995), Helsinki University of Technology Master's degree in Engineering and Technology (1991), Helsinki University of Technology Research Interests: Room acoustics simulation and auralization Acoustic radiance transfer and reverberation modelling Virtual reality audio and spatial perception Neural network applications in wave equation solutions Finite-difference time-domain (FDTD) methods Awards: Fellow of the Audio Engineering Society (2013) Fellow of the Acoustical Society of America (2018) Board of Governors Award, AES (2015) Best Doctoral Thesis Award in Technology (1999) Grants & Advising: Supervised 7 theses and actively participates in editorial boards (e.g., Acta Acustica ). Engages in conference organizing, international collaborations, and academic outreach, including roles in the Finnish Academy of Science and Letters. Labs & Collaborations: Leads the Aalto Acoustics Lab, collaborating globally on projects like hybrid acoustic modelling, GPU-based real-time simulations, and spatial audio systems for virtual environments.

• Distributed computing and systems software
• Data management and data science
• Electronics, sensors and digital hardware
• +۷ مورد دیگر

Assoc. Prof. Ali Yavari is an Associate Professor of Computer Science at Swinburne University of Technology's School of Science, Computing and Emerging Technologies. He also serves as Director of the 6G Research and Innovation Lab and Radiofrequency Lab. His academic journey includes a PhD in Computer Science from RMIT University (Australia) and a Master's in Communication Systems from KTH Royal Institute of Technology (Sweden). His research focuses on IoT, Cyber-Physical Systems (CPS), 5G/6G communication technologies, renewable energy systems, and health informatics. He leads collaborative projects funded by entities like Future Energy Exports CRC, Australian Radiation Protection & Nuclear Safety Agency (ARPANSA), and the Victoria State Government. Notable contributions include developing AI-driven IoT platforms for environmental monitoring (e.g., ArtEMon) and cybersecurity frameworks for Industry 4.0. Key achievements include the Victoria Fellowship in Physical Sciences (2020), Vice-Chancellor’s Research Excellence Awards (2021, 2023), and a Best Paper Award at the Hawaii International Conference on System Sciences. His work spans over 65 publications in top journals/conferences such as IEEE Sensors , Sustainable Energy Technologies and Assessments , and Environmental Research . Professional activities include program committee roles at IEEE conferences and memberships in ACM and IEEE (Senior Member). He actively supervises PhD candidates and teaches courses in IoT programming and advanced computing topics.

Yunhui Heمشاهده پروفایل

استادیار

• Numerical Analysis
• Scientific Computing
• Finite Element Methods
• +۵ مورد دیگر

Yunhui He is an Assistant Professor in the Department of Mathematics at the University of Houston. His research focuses on numerical analysis and scientific computing, with expertise in finite element methods, multigrid methods, and local Fourier analysis. He has held postdoctoral positions at institutions like the University of British Columbia and the University of Waterloo. His work includes contributions to preconditioning techniques, acceleration methods, and the numerical solution of partial differential equations. Education: PhD in Mathematics (2018), Memorial University of Newfoundland MSc in Computational Mathematics (2015), Chinese Academy of Sciences BSc in Mathematics and Applied Mathematics (2012), Capital Normal University Research Interests: Dr. He’s research emphasizes numerical methods for PDEs, multigrid algorithms, and iterative solvers. He explores topics like finite element methods, preconditioning strategies, and local Fourier analysis to enhance computational efficiency in fluid dynamics and optimal control problems. His work bridges theoretical analysis and practical implementation, with applications in engineering and physics. Articles Trends: Recent publications highlight advancements in multigrid relaxation schemes, Anderson acceleration for nonlinear PDEs, and preconditioners for coupled flow systems. His work often integrates local Fourier analysis to optimize solver performance, with applications to Stokes-Darcy equations and optimal control problems. Grants & Awards: He co-organized the 2025 NSF-funded CBMS Conference on Applied Mathematics and Machine Learning (DMS-2430460), demonstrating leadership in academic collaboration. Teaching: Taught courses including Linear Algebra, Partial Differential Equations, and Numerical Analysis at the University of Houston and other institutions. His pedagogical focus aligns with computational mathematics and scientific computing. Lab/Team: Hosts Santolo Leveque as a postdoctoral fellow (2024–present), advancing collaborative research in numerical methods and multigrid theory.

Bongjin Kimمشاهده پروفایل

دانشیار

• Secure Hardware Design
• Machine Learning
• Data Mining
• +۶ مورد دیگر

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 Jiangمشاهده پروفایل

استاد

• Electromagnetics
• Electromagnetic Compatibility (EMC)
• Signal Integrity
• +۵ مورد دیگر

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 Chatrabgounمشاهده پروفایل

استادیار

• Uncertainty Quantification
• Bayesian Machine Learning
• Gaussian Processes
• +۵ مورد دیگر

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.

• Exploration Geophysics
• Electromagnetic Exploration
• Electric Exploration
• +۷ مورد دیگر

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

Mark B. Moldwinمشاهده پروفایل

استاد

• Space Plasma Physics
• Magnetospheric Physics
• Space Weather
• +۵ مورد دیگر

Mark B. Moldwin serves as the Arthur F. Thurnau Professor in the Department of Climate and Space Sciences and Engineering at the University of Michigan's College of Engineering. He directs the NASA Michigan Space Grant Consortium and the M-STEM Academy’s M-Engin Program, with research focused on advancing space plasma physics and magnetospheric phenomena through innovative instrumentation and education initiatives. His educational background includes a B.A. from the University of Alaska – Fairbanks (1987), followed by M.A. (1990) and Ph.D. (1993) degrees from Boston University under advisor Jeff Hughes. This foundation established his expertise in space physics and sensor development. Professor Moldwin's research spans Space Plasma Physics , Magnetospheric Dynamics , and Magnetometer Sensor Development , with significant contributions to understanding geomagnetic disturbances and space weather impacts. His work uniquely bridges technical innovation in spacecraft instrumentation (e.g., WAIC-UP interference removal algorithms and CubeSat magnetometers) with Pre-College Space Science Education outreach, demonstrating a dual commitment to scientific advancement and educational accessibility. Analysis of his 2023-2025 publications reveals three dominant themes: (1) cutting-edge magnetometer technology for small satellites (TorqMag, HyMag-ADCS), (2) computational modeling of geomagnetic disturbances and GICs using FDTD methods, and (3) community-focused research addressing DE&I, mental health, and postdoctoral experiences in Earth sciences. This interdisciplinary approach connects heliophysics with practical societal applications. His scientific recognition includes: AGU Waldo Smith Union Award (2016) UM John F. Ulrich Educational Excellence Award (2017) UM Provost Teaching Innovation Award (2014) UM Harold R. Johnson Diversity Service Award (2014) UM Raymond J. and Monica E. Schultz Outreach Award (2013) As former Editor-in-Chief of Reviews of Geophysics (2009-2017) and AGU Education Section President (2018-2020), he has shaped scientific discourse while directing significant NASA-funded programs. His educational leadership extends to teaching SPACE471 and UARTS250, where he implements award-winning pedagogical innovations. Professor Moldwin's current work centers on the NASA Geospace Dynamics Constellation mission and HERMES payload for Lunar Gateway, developing magnetometer systems that address spacecraft interference challenges in complex orbital environments. His research group actively contributes to multi-institutional space weather monitoring networks and CubeSat instrumentation standards.

• Database Management
• Data Privacy
• Data Science
• +۴ مورد دیگر

Dr. Tianbing Xia is a Lecturer at the School of Computing and Information Technology, University of Wollongong (UOW), where he has been employed since 2021. He holds a PhD in Computer Science from UOW (1997–2000) and has over two decades of experience in tertiary education, research, and the IT industry. Prior to his PhD, he worked in the IT department of China Construction Bank HUBEI Province, contributing to software networking systems that earned a national-level award. His teaching spans a wide range of undergraduate and postgraduate courses, including CSIT115, CSCI 882, and others. Research interests include database management, data privacy, combinatorial code design, and computer security. He has actively supervised four Higher Degree Research students, focusing on topics like data processing optimization and cybersecurity. Dr. Xia’s research contributions span over 50 publications, with notable works in query optimization, parallel data transfer scheduling, and combinatorial matrix constructions. He has received funding for projects like Real-Time Visualisation of Intrusion Detection and Fuzzy-based Cryptography Applications . Notable recognition includes the national Technology and Advanced Development Grand Prize for a software networking system. He is currently available to supervise Masters and PhD students in data science and cybersecurity domains.

Stavros V. Georgakopoulosمشاهده پروفایل

استاد

• Wireless power transfer
• Novel Antennas
• Wearable antennas and body-centric wireless communications
• +۹ مورد دیگر

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 Holtمشاهده پروفایل

پژوهشگر

• Biophysics
• Optical Physics
• Marine Biology
• +۳ مورد دیگر

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
• +۷ مورد دیگر

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.

• Numerical analysis
• Partial differential equations
• Fluid mechanics
• +۳ مورد دیگر

Antonio Miguel Márquez Durán is an Associate Professor in the Department of Economics, Quantitative Methods and Economic History at Universidad Pablo de Olavide in Seville, Spain. His academic career spans over three decades with significant contributions to numerical analysis and partial differential equations. His research focuses on developing and analyzing finite element methods for fluid mechanics, solid mechanics, and fluid-structure interaction problems. PhD from University of Seville (2005) Thesis: Contribution to the study of some models governed by non-autonomous and/or stochastic evolution equations Supervised by Dr. Tomás Caraballo Garrido and Dr. José Real Anguas Professor Márquez Durán's research interests center on numerical methods for partial differential equations , particularly finite element methods for fluid mechanics, solid mechanics, and fluid-structure interaction problems. His work often involves developing mixed formulations, analyzing error estimates, and studying the coupling of different physical models. He has made significant contributions to pseudostress-based formulations, Brinkman models, and non-autonomous/stochastic evolution equations. His research bridges theoretical mathematical analysis with practical computational applications in engineering and physics. His publication record shows a consistent focus on developing robust numerical methods for complex physical systems. Recent work emphasizes mixed-hybrid and discontinuous Galerkin methods for dynamical systems, coupling techniques between different numerical methods (VEM and BEM), and analysis of fluid-solid interaction problems. The research trajectory demonstrates increasing sophistication in handling time-dependent problems, nonlinearity, and multi-physics coupling. Professor Márquez Durán has established productive collaborations with leading researchers in computational mathematics, most notably Gabriel N. Gatica (24 joint publications) and Salim Meddahi (22 joint publications). His work has been cited 815 times across 465 documents, indicating significant impact in his field. He has published in top journals including Computer Methods in Applied Mechanics and Engineering, SIAM Journal on Numerical Analysis, and IMA Journal of Numerical Analysis. His academic activities include extensive research collaboration, with 25 co-authors and 521 co-co-authors. While specific grant information isn't detailed in the provided materials, his sustained publication record suggests successful funding acquisition. Professor Márquez Durán appears to be an active member of the computational mathematics research community, contributing to both theoretical developments and practical applications of numerical methods.

Funda Akleman Yaparمشاهده پروفایل

استاد

• Electromagnetic Engineering
• Microwave Technologies
• Antenna Design
• +۳ مورد دیگر

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.