جستجوی استاد راهنمای دانشگاهی

Olivier Chadebecمشاهده پروفایل

استاد پژوهش

• Computational Electromagnetics
• Electrical Energy Conversion
• Numerical Modeling
• +۶ مورد دیگر

Olivier Chadebec is a CNRS Research Director at G2Elab, the power electrical engineering research department of Université Grenoble Alpes in France. He leads the 'Models, Methods and Methodologies Applied to Electrical Engineering' research team (MAGE group) and the ERT-CMF (Low Magnetic Fields Technological Research Group) at G2Elab. He was involved in creating the International Laboratory 'James Clerk Maxwell' in collaboration with the University of Lyon and Brazilian universities. Chadebec received his engineer and Ph.D. degrees in Electrical Engineering from the Grenoble Institute of Technology in 1997 and 2001. After a post-doctorate with Schneider Electric, he joined CNRS in 2003 as a Research Associate. He received his 'Habilitation à Diriger les Recherches' in 2011 and became a Research Director in 2015. He also spent a year in 2012 as a research associate at the Federal University of Santa Catarina in Brazil. His research focuses on computational electromagnetics applied to electrical energy conversion, developing numerical models, algorithms, and simulation tools for electromagnetic device analysis. His key research areas include finite element methods, integral methods, inverse problems, and low magnetic field metrology. He actively contributes to the development of the MIPSE platform commercialized by Altair Engineering via Flux software. His recent publications (2023-2025) show a strong focus on advanced computational methods for electromagnetic problems, including multiscale modeling, tensor compression techniques, FEM-BEM coupling for magnetoelectric effects, and optimization algorithms for electrical machine design and fuel cell diagnostics. His work demonstrates a consistent progression toward more efficient computational approaches for complex electromagnetic problems. Chadebec has supervised over 30 PhD students since 2006, with thesis topics spanning computational electromagnetics, inverse problems, fuel cell diagnostics, and submarine magnetic signature analysis. His research has significant applications in electrical machine design, fuel cell technology, submarine degaussing, and electromagnetic compatibility. He leads the MAGE research team and the ERT-CMF (Low Magnetic Fields Technological Research Group) at G2Elab, and has been instrumental in developing the MIPSE simulation platform used in industry through collaboration with Altair Engineering.

Aydın Buluçمشاهده پروفایل

استاد مدعو

• High-performance graph analysis
• Parallel sparse matrix computations
• Communication-avoiding algorithms
• +۳ مورد دیگر

Aydın Buluç is a Senior Scientist at the Lawrence Berkeley National Lab (LBNL) in the Applied Mathematics and Computational Research Division and an Adjunct Professor in the Electrical Engineering and Computer Sciences (EECS) department at UC Berkeley. At LBNL, he leads the Performance and Algorithms group, and at UC Berkeley, he is part of the SLICE lab. He also serves as the Director of Sparsitute, a DOE Mathematical Multifaceted Integrated Capability Center (MMICC) focused on sparse computations. Dr. Buluç's research focuses on high-performance graph analysis, parallel sparse matrix computations, and communication-avoiding algorithms with applications in machine learning and computational genomics. His work bridges theoretical computer science with practical applications in scientific computing, particularly in bioinformatics and large-scale data analysis. He has made significant contributions to the development of parallel algorithms for sparse linear algebra operations, which form the foundation for many graph analytics frameworks. His recent publications demonstrate a strong trend toward optimizing sparse computations for modern hardware architectures, particularly GPUs and distributed systems. The research spans theoretical algorithm design, practical implementation challenges, and applications in computational biology. A notable pattern is the increasing focus on communication-avoiding techniques for distributed graph neural network training and large-scale genomic analysis. Dr. Buluç has been actively involved in numerous professional activities, serving on program committees for major conferences including EuroSys (2026), ALENEX (2019, 2026), SPAA (2025), and IPDPS (2013-2019, 2021-2022, 2025). He has also served on the SIAM George Pólya Prize for Mathematical Exposition Selection Committee (2025) and as Founding Associate Editor for ACM Transactions on Parallel Computing (2013-2020). He leads the PASSION Lab research group, which focuses on parallel algorithms and systems for irregular numerical workloads. The lab develops several important open-source software packages including Combinatorial BLAS, HipMCL, PASTIS, CAGNET, and BELLA. These tools address challenges in large-scale graph analysis, protein sequence alignment, and distributed machine learning.

• Statistical Signal Processing
• Pattern Recognition
• Machine Learning
• +۳ مورد دیگر

Dr. Miroslaw Pawlak is a Professor in the Department of Electrical and Computer Engineering at the University of Manitoba’s Price Faculty of Engineering. He holds a Ph.D. and D.Sc. in Computer Engineering from Wrocław University of Technology, Poland. As a Professional Engineer registered in Manitoba, he has held visiting positions at multiple institutions worldwide, including the University of Ulm and University of Göttingen as an Alexander von Humboldt Foundation Fellow. His research focuses on statistical signal processing, machine learning, nonparametric modeling, and system identification. He authored/co-authored influential books like Nonparametric System Identification (Cambridge University Press, 2010) and over 100 peer-reviewed publications. Dr. Pawlak has served as an Associate Editor for journals such as Pattern Recognition and IEEE Transactions on Information Theory , and was recognized in Stanford University’s World’s Top 2% Scientists list. Education: 1985: Ph.D. in Computer Engineering, Wrocław University of Technology 1999: D.Sc. in Computer Engineering, Wrocław University of Technology Research Interests: Dr. Pawlak specializes in advanced signal processing techniques, including nonparametric system identification, statistical analysis of stochastic signals, and machine learning applications in engineering systems. His work bridges theoretical foundations (e.g., operator theory with Hermite polynomials) and practical implementations (e.g., wind farm modeling and power system stability prediction). Publications: His recent work emphasizes nonparametric methods for system testing (e.g., Hammerstein systems) and interdisciplinary applications like power grid oscillation prediction using LASSO algorithms. He frequently collaborates with international researchers to advance signal processing theory and energy systems modeling. Awards: World’s Top 2% Scientists (Stanford University, 2021/2022) Professional Contributions: Dr. Pawlak’s editorial roles and visiting fellowships demonstrate his global influence. He has advised numerous graduate students and contributed to key textbooks shaping the field of system identification.

Nenad N. Cvetkovicمشاهده پروفایل

استاد

• Theoretical Electrical Engineering
• Electromagnetics
• Bioelectromagnetics
• +۳ مورد دیگر

Nenad N. Cvetkovic is a Full Professor at the Faculty of Electronics, University of Niš, specializing in Theoretical Electrical Engineering. He earned his PhD (2009), MSc (2002), and BSc (1995) from the same institution. His research focuses on electromagnetic field interactions with biological tissues, grounding system design, and numerical modeling of geoelectrical phenomena. Key areas include mobile phone radiation effects on human tissues, SAR distribution in anatomical models, and innovative approaches to multi-layered soil grounding analysis. He has contributed over 19 peer-reviewed articles in high-impact journals, addressing topics like dental implant EM interactions, orthodontic brace SAR profiles, and optimizations for grounding systems. His work bridges theoretical rigor with practical applications in electrical safety, biomedical engineering, and environmental geoelectrics. Prof. Cvetkovic is actively engaged in national/international research projects and speaks English and German fluently. His laboratory activities include finite element method (FEM) simulations, experimental validation of grounding models, and collaborations on standards for non-ionizing radiation exposure assessment.

Anastasia Sofroniouمشاهده پروفایل

استاد

• Nonlinear Dynamics
• Chaos Theory
• Mathematics Education
• +۴ مورد دیگر

Professor Anastasia Sofroniou is a Professor of Mathematics and Course Leader for the BSc (Hons) and MSc Mathematics and Statistics programs at the School of Computing and Engineering, University of West London. She also serves as Lead of Professional Engagement within the institution. Her academic career spans multiple disciplines, with publications ranging from pure mathematics to educational research. Dr. Sofroniou completed her BSc Mathematics with Economics from University College London, followed by an Interdisciplinary MSc in Mathematics from Kings College London and Imperial College London. She furthered her education with a certificate course in Data Analysis for Management from London School of Economics and Political Science and earned her PhD in Applied Mathematics from University College London. Her research interests have evolved significantly over her career. Initially focused on Nonlinear Dynamics and Chaos within applied mathematics, she has more recently expanded her work into Educational Mathematics, with numerous publications examining teaching methods, student satisfaction, and computational thinking in mathematics education. Her work demonstrates a clear transition from theoretical mathematical research to practical educational applications. Her recent publications (2023-2025) show a strong focus on two main areas: mathematical analysis of the swing equation (related to power systems stability) and educational research in mathematics teaching. The swing equation papers demonstrate her continued engagement with nonlinear dynamics, while her educational research reflects her commitment to improving mathematics pedagogy. Professor Sofroniou has received notable recognition for her research, including the Andrew Rosen Prize for research excellence in Applied Mathematics and the Lighthill Scholarship Award in Mathematics (awarded twice). She holds prestigious professional affiliations including Principal Fellow of the Higher Education Academy (PFHEA), Fellow of the Institute of Mathematics and its Applications (FIMA), and membership in both the London Mathematical Society and The Mathematical Association. Her teaching responsibilities span numerous programs across mathematics, engineering, and computer science disciplines at the University of West London.

Raúl Ordóñezمشاهده پروفایل

استاد

• Nonlinear Control
• Adaptive Control
• Extremum-Seeking Control
• +۴ مورد دیگر

Raúl Ordóñez is a full professor and Director of Graduate Programs in the Department of Electrical and Computer Engineering at the University of Dayton’s School of Engineering. He holds a Ph.D. and M.S. in Electrical Engineering from The Ohio State University (2001 and 1996) and a B.E. from Monterrey Institute of Technology. His research focuses on nonlinear control, adaptive systems, extremum-seeking control, and applications in aerospace, robotics, and power systems. Professional highlights include serving as Associate Editor for Automatica since 2006, co-authoring textbooks on adaptive control and extremum-seeking techniques, and holding editorial roles for IEEE conferences. Awards include the Boeing Welliver Faculty Fellowship (2008) and AFRL Summer Faculty Fellowship (2014). He has conducted research collaborations at institutions like Université de Picardie Jules Verne (France) and TU Wien (Austria). Key research areas include control of hypersonic vehicles, industrial robots, scramjets, and power generators. His work integrates advanced control methodologies with practical systems, emphasizing real-time optimization and robustness. Courses taught span control systems, nonlinear dynamics, and adaptive control. Education: Ph.D./M.S. (Ohio State), B.E. (Monterrey Tech) Professional Activities: IEEE Control Systems Society, CCCS Collaborative Center Recent Awards: AFRL (2014), Boeing (2008) Labs/Teams: Collaborates with robotics and aerospace teams at UD and international institutions

Antonio Ciconeمشاهده پروفایل

استاد

• Numerical Analysis
• Signal Processing
• Applied Mathematics
• +۵ مورد دیگر

Antonio Cicone is a Professor of Numerical Analysis at the University of L'Aquila, Italy. He holds the position of Research Associate at the Istituto di Astrofisica e Planetologia Spaziali (INAF) and Istituto Nazionale di Geofisica e Vulcanologia (Rome). His research focuses on signal processing, numerical linear algebra, and their applications in geophysics, astrophysics, medicine, and economics. He leads projects funded by the Italian Ministry and coordinates international initiatives like the MaSAG and NoSAG summer schools. He serves as an editor for journals such as Applied and Computational Harmonic Analysis and Frontiers in Applied Mathematics. His work includes developing algorithms like Fast Iterative Filtering (FIF) and the IMFogram for nonstationary signal analysis. Key collaborations involve universities and institutions worldwide, addressing challenges in plasma dynamics, GNSS signals, and cultural heritage preservation. Education: Holds an Abilitazione Scientifica Nazionale (ASN) for Full Professor in Numerical Analysis (2023) and Associate Professor (2020). Member of the Ph.D. program in Computer Science and Mathematics at the University of Insubria. Extensive teaching in signal processing and numerical analysis. Research Interests: Signal decomposition, time-frequency analysis, applications in geophysics/astrophysics, circular economy through signal processing, and interdisciplinary collaborations. His methods are applied to biomedical signals, optical fringe patterns, and environmental data analysis. Grants & Leadership: PI of the PRIN PNRR 2023 project on circular economy. Organized multiple international conferences and summer schools. Editorships and advisory roles in academic journals highlight his leadership in computational mathematics and signal processing. Labs/Teams: Involved with the Mathematics for Signal Processing group at the University of L'Aquila and collaborates with global institutions like Duke University and Georgia Tech.

Ulaş BELDEKمشاهده پروفایل

استادیار

• Control Theory and Applications
• Mechatronics
• Artificial Intelligence
• +۳ مورد دیگر

Dr. Ulaş BELDEK is an Assistant Professor at the Department of Mechatronics Engineering, Faculty of Engineering, Çankaya Üniversitesi. He holds a Ph.D. in Electrical and Electronics Engineering from Middle East Technical University (2009) and has been a full-time faculty member since 2002. His research focuses on control theory, mechatronics, artificial intelligence, and renewable energy systems. He has advised 14 master’s theses and contributed to numerous projects, including the development of a central control unit for renewable energy systems. Education: Ph.D., Electrical and Electronics Engineering, Middle East Technical University (2004–2009) M.Sc., Electrical and Electronics Engineering, Middle East Technical University (1999–2001) B.Sc., Electrical and Electronics Engineering, Middle East Technical University (1995–1999) Research Interests: Control systems design and optimization Robotics and autonomous navigation Machine learning applications in energy systems Evolutionary algorithms and optimization techniques Renewable energy systems integration Projects: Development of a Central Control Unit for Renewable Energy Systems Trios Car Electric Vehicle Production

• Theoretical Physics
• Computational Physics
• Biological Physics
• +۷ مورد دیگر

Nicolae-Viorel Buchete is an Associate Professor of Theoretical & Computational Nano-Bio Physics at University College Dublin's School of Physics within the College of Science. He currently serves as Vice Principal for Graduate Studies for the College of Science and Director of the UCD MSc in Computational Physics Programme. His academic journey includes postgraduate degrees from Boston University (USA) and institutions in the EU (Al. I. Cuza University of Iasi, Romania, and the University of Patras, Greece), with a PhD from Boston University and research fellowships at the National Institutes of Health. His educational background includes: PhD from Boston University Research Fellowships at National Institutes of Health (Bethesda, MD, USA) Postgraduate degrees from Boston University, Al. I. Cuza University of Iasi (Romania), and University of Patras (Greece) Buchete's research focuses on theoretical and computational approaches to understanding biomolecular systems. His work spans theoretical and computational biological physics, chemical physics, and nanoscience , with specific emphasis on statistical mechanics and molecular dynamics of biomolecular systems, systems biology, structural bioinformatics, and multiscale modeling of biomolecules and complex fluids. His group employs advanced computational techniques including Markov State Models, Milestoning, and replica exchange molecular dynamics to study protein conformational dynamics, amyloid formation, and molecular mechanisms relevant to diseases like cancer and Alzheimer's. His research output reveals a progression from fundamental biophysics toward increasingly translational applications. Early work focused on protein conformational dynamics, while more recent publications demonstrate expansion into nanomedicine applications, computational toxicology of nanomaterials, and physics-based modeling frameworks for drug delivery systems. A significant portion of his research involves studying conformational transitions in proteins relevant to cancer (such as K-Ras4B and Abl kinase) and neurodegenerative diseases (particularly amyloid systems), with growing emphasis on computational approaches to nanosafety and sustainability. His scientific contributions have been recognized with numerous awards: Certificate of Appreciation from the American Chemical Society Publications Division (2012) Top 20 JCP Reviewer for 2010 from the American Institute of Physics NIH Fellows Award for Research Excellence (FARE) in 2006 and 2007 ACS Chemical Computing Group Excellence Award (2003) Multiple teaching and research awards from Boston University including the Outstanding Teaching Fellow Award (1998) and Feldman Award (2001) Buchete has mentored numerous graduate students through their MSc and PhD research, with students successfully defending theses on computational physics and biomolecular modeling topics. His teaching philosophy emphasizes "research-oriented teaching," integrating research experiences into undergraduate and taught Master's level education. He has secured research funding including the UCD OBRSS Research Support Scheme (2016-2023) and has directed multiple educational programs including the UCD International Pre-Masters Programme (2013-2022) and served as School Head of Teaching and Learning (2021-2022). His research group is affiliated with the UCD Complex & Adaptive Systems Laboratory (CASL), where they develop and apply advanced computational methods to study complex biomolecular systems. The group has organized multiple CECAM workshops on biomolecular modeling and simulations, demonstrating leadership in the computational biophysics community. They collaborate extensively across disciplines, working with experimentalists to validate computational findings and address challenging problems in biophysics and nanomedicine.

• Computer Engineering
• Augmented Reality
• Virtual Reality
• +۷ مورد دیگر

Karthik Ramani is the Donald W. Feddersen Distinguished Professor in Mechanical Engineering and Professor of Electrical and Computer Engineering at Purdue University. He holds dual appointments in the Elmore Family School of Electrical and Computer Engineering and the Department of Mechanical Engineering within the College of Engineering. His research focuses on advanced topics in augmented reality (AR), virtual reality (VR), human-computer interaction, artificial intelligence, and robotics, with emphasis on tangible user interfaces, design automation, and immersive learning technologies. His work bridges theory and application, addressing challenges in interactive systems, IoT education, and embodied AI. Key research areas include AR/VR platform development, generative AI for design, and systems enabling bidirectional interaction between digital and physical objects. His contributions span technical innovations like the DuNN method for solving partial differential equations, the pARametric tool for parametric modeling, and collaborative AR platforms for educational and industrial use. He has authored numerous patents and articles on topics ranging from hand-object interaction to large language model visualization. Ramani’s work emphasizes practical applications in fields like manufacturing education, IoT skill development, and immersive training. His systems address challenges such as real-time AR binding with physical toys, causal reasoning visualization in mixed reality, and human-robot collaborative task authoring. His research often integrates hardware innovation with software solutions, as seen in flexible touch sensing systems and stretch-based interaction methods for wearable devices.

Baoyun Geمشاهده پروفایل

استادیار

• Electric Motors and Generators
• Power Electronics Controls
• Multiphysics Synthesis
• +۳ مورد دیگر

Baoyun Ge is an Assistant Professor at Georgia Institute of Technology's School of Electrical and Computer Engineering, part of the College of Engineering. Previously, he served as an Assistant Professor at the University of Florida (2022–2024) and worked at C-Motive Technologies, Inc., a startup focused on electrostatic machine commercialization. His expertise bridges academia and industry in energy systems and multiphysics design. Education: B.E. in Electrical Engineering, Southeast University (2012) Ph.D. in Electrical and Computer Engineering, University of Wisconsin-Madison (2018) Dr. Ge's research emphasizes multiphysics synthesis, leveraging advanced mathematical tools to transcend traditional design methods. Key areas include electrostatic/magnetostatic machine duality, high-performance computational modeling, and energy conversion systems. His work integrates physics-based insights with topology optimization and finite element analysis. His recent publications (2019–2023) focus on electrostatic machine design, topology optimization, and multiphysics finite element analysis. These contributions highlight advancements in energy-efficient systems and algorithmic approaches for complex engineering problems. Awards: NSF CAREER Award (2024) Harold A. Peterson Distinguished Dissertation Award (2019) IEEE IAS First Prize Paper (2017) Dr. Ge’s advising and grant activities are integral to his academic role, though specific grants or student names are not detailed here. His research group likely focuses on experimental and computational studies in multiphysics systems. No dedicated lab or team name is explicitly mentioned in available records.

• Power Electronics
• Wireless Power Transfer
• Electric Vehicle Technology
• +۴ مورد دیگر

Nikolay Dimitrov Madzharov is a Professor at the Department of Electronics, Faculty of Electrical Engineering and Electronics, Technical University of Gabrovo. His work focuses on power electronics, wireless power transfer systems, and electric vehicle charging infrastructure. He has led and participated in numerous international and national projects, including modernization of educational institutions and development of energy-efficient systems. Research Interests: Wireless power transfer, inductive resonance systems, electric vehicle technology, energy storage systems, and control systems in energy. Projects: Over 7 projects, including 'Optimal Design and Management of Electrical Energy Storage Systems' and 'Intelligent Mechatronic, Eco- and Energy-Saving Systems and Technologies.' His research emphasizes practical applications, such as contactless charging stations and high-efficiency energy converters. Madzharov has authored 4 books and over 96 publications, including journal articles and conference papers on topics like resonant inverters and battery management systems. He has advised 6 doctoral students, contributing to advancements in power electronics and energy systems. His work has been presented at international conferences such as PCIM, ICEST, and SIELA, showcasing innovations in wireless energy transfer and system reliability.

• Sustainable Energy Systems
• Numerical Optimization
• Deep Learning
• +۳ مورد دیگر

Dr. Manuel Dahmen serves as Head of Department at the Institute of Climate and Energy Systems (ICE-1) within the Research Center Jülich. His research focuses on designing sustainable and cost-efficient energy systems through numerical optimization and deep learning techniques. He leads efforts in advancing energy system technology, particularly in optimizing renewable energy integration, process network analysis, and the co-design of fuels and engines. His work emphasizes innovative applications of machine learning, such as physics-informed neural networks and reinforcement learning, to address challenges in energy system design and operation. Key areas include reducing greenhouse gas emissions in industrial processes, optimizing energy networks, and developing data-driven models for dynamic process control. Dr. Dahmen’s contributions span algorithm development (e.g., MUSE-BB decomposition algorithms), energy system scenario generation, and robust design methodologies under uncertainty. His research bridges computational methods with practical energy solutions, aiming to achieve decarbonization in industries like copper production and transportation. Publications highlight advancements in renewable energy integration, fuel design for spark-ignition engines, and the application of graph neural networks for molecular property prediction. His interdisciplinary approach fosters collaboration across chemical engineering, computer science, and energy economics to tackle global sustainability challenges.

Ying Liangمشاهده پروفایل

استادیار

• Inverse problems
• Mathematical imaging
• Scattering theory
• +۳ مورد دیگر

Ying Liang is a Phillip Griffiths Assistant Research Professor of Mathematics at Duke University, affiliated with the Department of Mathematics within Trinity College of Arts & Sciences. She holds a Ph.D. in Mathematics from The Chinese University of Hong Kong (2021) and a BSc from Wuhan University (2016). Her research focuses on inverse problems, mathematical imaging, scattering theory, and scientific machine learning. She has contributed to theoretical and numerical studies of inverse source problems, wave equations, and electromagnetic diffraction. Her work combines mathematical rigor with computational techniques to address challenges in applied mathematics and engineering. Liang has taught courses such as MATH 563 (Applied Computational Analysis) and MATH 561 (Numerical Linear Algebra) at Duke, and previously instructed multiple courses at Purdue University and The Chinese University of Hong Kong. Her academic journey includes roles as a Golomb Visiting Assistant Professor (Purdue, 2021–2024) and a Research Assistant (CUHK, 2016–2021). Her publications span topics like stability analysis of inverse problems, electromagnetic diffraction theory, and numerical methods for partial differential equations. She actively participates in conferences and workshops, presenting on neural network approaches to inverse problems and scientific computing innovations.

Mark Everettمشاهده پروفایل

استاد

• Near-surface Applied Geophysics
• Ground-penetrating Radar Imaging
• Electrical Resistivity Tomography
• +۵ مورد دیگر

Mark Everett is a Professor of Geophysics at Texas A&M University, holding the Howard Karren Professorship. His primary research focuses on near-surface applied geophysics, with expertise in ground-penetrating radar (GPR), electrical resistivity tomography, and controlled-source electromagnetics. He explores applications in environmental monitoring, geotechnical engineering, archaeology, and agricultural sciences. Research interests include karst aquifer dynamics, coastal transition zones, and subsurface imaging for infrastructure assessment. Teaches courses like GEOP 313 (Geophysical Field Methods) and GEOP 413 (Near-Surface Applied Geophysics). Education background: BSc and MSc in Physics from York University (Canada), followed by a PhD in Geophysics from the University of Toronto. Research highlights: Developed the SWAN CSEM system for offshore groundwater mapping. Advanced GPR techniques for unmarked grave detection and crop biomass estimation. Led studies on sinkhole formation mechanisms and coastal aquifer connectivity. Publications emphasize hydrogeological processes, geophysical instrumentation, and interdisciplinary applications in agriculture and archaeology. Collaborates globally on projects like the Texas Water Observatory, focusing on climate-land use interactions in water cycle dynamics.