جست‌وجوی استاد و پژوهشگر

• Decision making
• Knowledge engineering
• Knowledge graphs
• +۳ مورد دیگر

Marie-Hélène Abel is a Professor and Director of the Computer Science Department at the University of Technology of Compiègne (UTC), France. She leads the Heudiasyc laboratory (UMR CNRS 7253) and specializes in decision making, knowledge engineering, knowledge graphs, and multi-agent systems. Her work focuses on collaborative systems, organizational learning, and the integration of social data into decision support frameworks. She has been recognized with prestigious awards, including Senior IEEE membership (2017) and the 2017 K2 Trophy for participatory computing innovations. Her research emphasizes the development of systems like the MEMORAe platform, which supports learning ecosystems through collaborative environments and organizational memory. She collaborates internationally with institutions such as the Pontifical Catholic University of Paraná (Brazil) and industry partners including Thales, Alstom Transport, and PSA. Key projects include crisis simulation systems and ontology-based frameworks for Industry 4.0 collaboration. Abel’s academic contributions span over 50 peer-reviewed articles, with recent works addressing context-aware recommender systems, crisis management simulations, and teacher efficacy in digital education. Her leadership roles include directing research projects, overseeing the Computer Engineering Department, and advancing ethical AI practices through initiatives like the Sorbonne.AI network. Education: HDR (Habilitation à Diriger des Recherches) on 'Contribution of Organizational Memories in a Learning Context' (2007) Administrative Roles: Equality Officer, University Antiracism/Anti-Semitism Officer International Collaborations: Brazil, Egypt, and Tunisia

Elmine Meyerمشاهده پروفایل

استادیار

• Antenna Design
• Millimeter Wave Technology
• RF Engineering
• +۳ مورد دیگر

Elmine Meyer is an Assistant Professor in the Electrical Engineering department at Eindhoven University of Technology. Her research focuses on antenna design, millimeter wave technology, and RF engineering. She leads the EM Antenna Systems Lab and EM for Radio Science Lab, contributing to advancements in 5G/6G communication systems and space-based radio astronomy. She holds a PhD in Electrical Engineering from the University of Stellenbosch (2018) and a Bachelor of Engineering from Fairleigh Dickinson University (2013). Meyer's projects include leadership roles in the ANTERRA (6G Non-Terrestrial Networks), INNOSTAR (EM), and MyWave initiatives. She has organized events like the 28th European Microwave Week 2025 and contributed to high-impact research on antenna arrays, 3D-printed RF devices, and pedestal resonators. Her work bridges academic research with industrial applications, emphasizing practical implementations in wireless communication systems. Her research interests span antenna array design, millimeter wave systems, and electromagnetic compatibility. Over 38 citations highlight her contributions to fields like substrate integrated waveguide (SIW) technology and adaptive beamforming. Collaboration networks include institutions globally, particularly in antenna measurement systems and space-based communication technologies.

• Microwave Engineering
• RF Systems Design
• Power Amplifier Design
• +۷ مورد دیگر

Christian Fager is a Full Professor at the Department of Microwave Electronics, Chalmers University of Technology, Sweden. He has been affiliated with Chalmers since completing his Ph.D. there in 2003. As Head of the Microwave Electronics Laboratory, his research focuses on nonlinear transistor modeling, energy-efficient power amplifier architectures, and distributed MIMO systems. He has co-invented 8 patents and published over 250 papers, including a seminal book on Nonlinear Transistor Model Parameter Extraction Techniques (Cambridge University Press, 2011). Dr. Fager holds editorial roles as Associate Editor of IEEE Microwave Magazine and member of the MTT-S Technical Coordination Committee on Wireless Communications. He is a Board Member of the European Microwave Association (EuMA) and has chaired multiple IEEE topical conferences. His awards include the Chalmers Supervisor of the Year (2018), inaugural Area of Advance Award (2010), and IEEE IMS Best Student Paper (2002). He leads research initiatives in distributed antenna systems, digital pre-distortion, and GaN/SiGe-based high-efficiency amplifiers, with projects involving testbed development for 5G/6G applications. His work bridges theoretical modeling and practical implementation in RF/microwave systems, emphasizing thermal and multi-physical simulation integration.

• Environmental Engineering
• Membrane Technology
• Water Treatment Systems
• +۳ مورد دیگر

Tao Chen is an Associate Professor in the Department of Economics at the University of Waterloo. His research focuses on environmental engineering challenges, particularly membrane fouling mechanisms in cold-climate water treatment systems, operational parameter optimization (e.g., temperature, hydraulic retention time), and sustainable wastewater management strategies. He holds cross appointments and is affiliated with groups related to interdisciplinary environmental research. Research interests include membrane technology applications in tertiary treatment, temperature effects on fouling dynamics, and process modeling for biological reactors (e.g., MBBR, IFAS). His work emphasizes practical solutions for energy-efficient and climate-adaptive water systems, particularly in cold regions. Key trends in his publications (2014-2024) highlight advancements in understanding fouling mechanisms, optimizing operational variables, and developing models for sustainable wastewater treatment. Notable topics include ultrafiltration membrane performance under low temperatures, soluble microbial products in activated sludge systems, and partial nitrification-anammox processes. No scientific awards or grants are explicitly listed in the provided text. No advisee students are mentioned, but his research likely involves graduate student collaboration. Lab or team affiliations are not detailed in the available information.

Marjan Firouzniaمشاهده پروفایل

پژوهشگر

• Medical Imaging
• Machine Learning
• Deep Learning
• +۳ مورد دیگر

Marjan Firouznia is a Principal Research Engineer at Linköping University , affiliated with the Division of Diagnostics and Specialist Medicine (DISP) under the Faculty of Medicine and Health Sciences . With a PhD in Electrical Engineering from Amirkabir University of Technology and postdoctoral experience at institutions like Case Western Reserve University, she specializes in advancing machine learning models for precise segmentation of cardiac structures including the left atrium , epicardial fat , and fibrosis using CT and MRI scans. Her work aims to improve diagnostic accuracy and treatment planning in cardiovascular care. Marjan's research focuses on medical imaging , deep learning , and computational anatomy , with recent publications on FractalRG , FK-means , and Poincare-guided UNet for cardiac structure segmentation. Her academic contributions span 15 recent publications , emphasizing fractal geometry , chaos theory , and optimization algorithms in biomedical applications. She actively develops open-source datasets and tools, such as the FK-means codebase , to support reproducibility in medical AI research.

• Deep Learning
• Neural Networks
• Artificial Intelligence
• +۹ مورد دیگر

Elena Mocanu is an Assistant Professor in the Department of Datamanagement & Biometrics and a faculty member of the Digital Society Institute. Her research focuses on advancing neural network architectures, particularly through dynamic sparse training techniques to enhance computational efficiency and model performance. Key areas include deep reinforcement learning applications in building energy optimization, federated learning for collaborative data environments, and sparse connectivity models that reduce resource usage without sacrificing accuracy. She has contributed to frameworks like the Digital Twin for autonomous driving and energy systems, emphasizing sustainability and scalability. Her work bridges theoretical advancements and practical implementations, addressing challenges in energy-efficient AI, robust noise filtering in reinforcement learning, and feature selection for medical imaging tasks. She actively organizes conferences such as ICLR workshops on sparsity in neural networks and IJCAI events, fostering interdisciplinary collaboration in artificial intelligence. Awards : Best Paper Award at AAMAS 2022 Workshop, ICML 2022 Outstanding Reviewer Award Conference Leadership : Organized ICLR 2023 Sparsity Workshop, EPIA 2023/2022 Conferences Research highlights include scalable training methods inspired by network science, energy optimization in smart buildings, and sparse ensembling techniques that achieve efficiency gains without overhead. Her contributions span foundational machine learning theory to applied domains like smart grids and autonomous systems.

Georgios Portokalidisمشاهده پروفایل

استاد پژوهشی

• Systems Security
• Binary Analysis
• Software Hardening
• +۱ مورد دیگر

Georgios Portokalidis is an Associate Research Professor at IMDEA Software Institute and Visiting Research Professor at Stevens Institute of Technology. He leads research in software systems security with focus on binary analysis, software hardening, and operating system security. His research develops practical defenses against software vulnerabilities through techniques like binary debloating, system call filtering, and hardware-assisted security. Current projects explore Rust language security, processor-assisted protection mechanisms, and vulnerability mitigation through code reduction. Publication trends show evolution from foundational binary analysis to applied security hardening, with recent emphasis on Rust security, hardware-assisted defenses, and real-world system protection. Work demonstrates consistent focus on practical, deployable security solutions. He has supervised numerous PhD students and postdocs, currently mentoring researchers at IMDEA. His group investigates binary analysis, software debloating, and system hardening techniques. Major grants include DARPA YFA (2021-2023) and ONR funding (2017-2022) supporting adaptive binary debloating research. Leads the systems security research group at IMDEA Software Institute, collaborating with international partners. Maintains active research partnerships and regularly contributes to top security conferences as program committee member.

Hedayat Zarkoobمشاهده پروفایل

پژوهشگر

• AI in Education
• Educational Technology
• Machine Learning Applications
• +۳ مورد دیگر

Hedayat Zarkoob is a Researcher in the Department of Computer Science at the University of British Columbia (UBC), where he completed his PhD under Prof. Kevin Leyton-Brown. His work focuses on AI applications in education, particularly in peer grading systems, active learning, and large-scale classroom engagement. He is actively involved in teaching within UBC's Master of Data Science (MDS) program and the Computer Science department, leading courses on privacy, algorithms, communication, and societal impacts of technology. Education: PhD in Computer Science, UBC (supervised by Kevin Leyton-Brown) MSc in Computer Science, Simon Fraser University (supervised by Andrei Bulatov) Research Interests: Zarkoob's research bridges AI and education, with emphasis on scalable assessment tools (e.g., Mechanical TA 2), classroom engagement platforms (Agora), and AI-driven conference review systems. His work combines algorithm design, educational technology, and human-AI collaboration. Recent Projects: Agora, an open-source tool for student participation in large courses; Mechanical TA 2, a peer-grading system with algorithmic support; and AAAI 2021 workflow innovations. Teaching Roles: Upcoming courses include DSCI 541, 553, 542, 512, and CPSC 430. He has co-taught CPSC 430 (Computers and Society) since 2023.

• Computer Vision
• 3D Reconstruction
• Perceptual Information Processing
• +۷ مورد دیگر

SATO Jun holds the position of Professor at the Department of Information Engineering (メディア情報分野) within the Faculty of Engineering at Nagoya Institute of Technology. He received his Ph.D. in Information Engineering from the University of Cambridge (1993–1996) and previously served as a Research Assistant at Cambridge (1996–1998). His research focuses on perceptual information processing and intelligent informatics, with specializations in computer vision, 3D reconstruction, and optical engineering applications. He has authored influential books like Computer Vision - Geometry of Vision (1999) and Computer Graphics (2017), and contributed to international publications such as Springer's Computer Vision: A Reference Guide (2020). Key professional roles include serving as President of the IEEE Nagoya Branch since 2023, Associate Editor of the International Journal of Computer Vision (Springer, 2010–present), and committee member for various organizations including Japan's Ministry of Education (2015–present) and the Nagoya City Business Potential Evaluation Committee (2008–2015). He has been recognized with prestigious awards including the BMVC Best Science Paper Prize (1994, 1997) and ITE Niwa-Takayanagi Prize (2015). His research extends to industrial collaborations, evidenced by patents like the "3D Information Presentation Device" (2014–2017) and "Position Detecting Device" (2016–2019). Recent work emphasizes applications in automotive safety, occluded object reconstruction, and novel imaging systems using advanced optical configurations and neural networks.

José PICHERALمشاهده پروفایل

استاد

• Signal Processing
• Acoustic Imaging
• Array Processing
• +۵ مورد دیگر

José Picheral is a Professor at CentraleSupélec, affiliated with the Laboratory of Signals and Systems (L2S). He holds a PhD (2003) and HDR (2017) in high-resolution signal processing methods and inverse problems. His research focuses on array processing, source localization, acoustic imaging, and vibration analysis, with applications in aeroacoustics, automotive systems, and industrial monitoring. He has supervised multiple PhD students and contributed to projects like Valeo’s smartphone-based car key replacement system. Education: Engineering Degree: Supélec (1999) and Politecnico di Milano (1999, Erasmus-TIME) PhD: Paris Sud University (2003) Habilitation (HDR): Université Paris Sud (2017) Research Interests: High-resolution methods for distributed sources, sparse signal processing, acoustic imaging, asynchronous measurements, and sensor array design. Current projects include spatial source covariance estimation, EEG spectrum analysis, and automotive applications using smartphone localization. Key Contributions: Over 50 publications in top journals/conferences (e.g., IEEE Transactions, ICASSP). Notable work on MUSIC algorithm robustness, DAMAS optimization, and sparse approaches for tip-timing signals. Advising & Collaboration: Supervised 7 PhD students. Collaborations with SAFRAN, Valeo, and academic teams in Bayesian inference and inverse problems. Active in L2S’s Inverse Problems Group and SYCOMORE team. Labs/Teams: Member of L2S’s Signal Processing and Statistics group, leading research in systems and control, telecommunications, and energy systems.

Viji Ahanathapillaiمشاهده پروفایل

استادیار

• Biomedical Signal and Image Processing
• Wearable Technology for Health Monitoring
• Women's Health
• +۳ مورد دیگر

Dr. Viji Ahanathapillai is an Assistant Professor in Biomedical Engineering at the University of Warwick's School of Engineering, specializing in the Systems and Information Engineering stream. She holds a PhD in biomedical signal and image processing from the University of Strathclyde and has extensive industry experience in roles such as Image Processing Algorithms Engineer at Lucid Software Ltd and Development Scientist at Malvern Panalytical Ltd. Her academic career includes post-doctoral research at Warwick's Institute of Digital Healthcare and a Senior Lecturer position at Birmingham City University. Education: B.Eng (India) → PhD (University of Strathclyde). Research focuses on Biomedical Signal/Image Processing , Wearable Health Monitoring , Women's Health , and AI in Healthcare . Recent work includes developing algorithms for venous dislodgement detection, AI-driven healthcare data analysis, and wearable devices for real-time health monitoring. Teaching: Course leader for MSc Diagnostics Data and Digital Health, and module leader for Research Project modules. Provides weekly math support to first-year students. Labs/Teams: Active contributor to the Systems & Information Engineering team and the Institute of Digital Healthcare at Warwick. Editor of IET Healthcare Technology Letters.

• Computer Vision
• Machine Learning
• Deep Learning
• +۵ مورد دیگر

Dr. Nathanael L. Baisa is a Lecturer in Artificial Intelligence at De Montfort University (DMU), part of the Computing, Engineering and Media faculty within the School of Computer Science and Informatics. His academic career includes roles as a senior research associate at Lancaster University, researcher at AnyVision, and research fellow at the University of Lincoln, focusing on computer vision and machine learning projects funded by ERC, EPSRC, and Innovate UK. Education: PhD in Electrical Engineering (Computer Vision/ML - Heriot-Watt University, 2018) MSc in Computer Vision and Robotics (Erasmus Mundus program, 2013) Research focuses on computer vision applications including object detection, scene understanding, autonomous systems, and biometrics. He leads work on deep learning for visual tracking, hand-based person identification, and robotic perception. He teaches courses like Introduction to Computer Vision and Deep Learning frameworks. His recent publications emphasize vision-language models, multi-object tracking algorithms, and geoscience machine learning applications. He collaborates with the Institute of Artificial Intelligence (IAI) and contributes to interdisciplinary projects in robotics and energy exploration.

Jason R. Bloughمشاهده پروفایل

استاد

• Noise, Vibration, and Harshness (NVH) Analysis
• Digital Signal Processing
• Vibrations
• +۵ مورد دیگر

Jason R. Blough is a Professor and Chair of Mechanical and Aerospace Engineering at Michigan Technological University (MTU), affiliated with the Great Lakes Research Center (GLRC). He holds a PhD from the University of Cincinnati. His research focuses on dynamic measurement problems, digital signal processing for NVH (Noise, Vibration, Harshness) analysis, and improving NVH characteristics in machinery across diverse applications—from turbine blades to snowmobiles and passenger vehicles. He leads the Clean Snowmobile Team and has pioneered order tracking algorithms for rotating machinery, commercially licensed. His work spans experimental techniques like modal analysis, transfer path analysis, and Kalman Filter development for automotive applications. Education: PhD in Mechanical Engineering, University of Cincinnati Research Highlights: Dr. Blough specializes in vibration and acoustic measurement systems, sound quality jury studies, and active noise control. His innovations include wireless microwave telemetry for rotating components and methodologies for quantifying environmental effects on noise testing (e.g., snowmobiles). He regularly teaches advanced NVH techniques in academic and industrial settings. Advising & Grants: Advisor to the Clean Snowmobile Team (MTU), focusing on sustainable vehicle design. His grants and projects address automotive NVH, powertrain dynamics, and environmental acoustics. Labs & Teams: Directs the GLRC’s NVH research initiatives, collaborating with industry partners on noise mitigation and signal processing applications.

Rashid Aliمشاهده پروفایل

استادیار

• Autonomous Systems
• Control Theory
• Aircraft Design
• +۴ مورد دیگر

Rashid Ali is an Assistant Professor at CEES School of Engineering, specializing in Autonomous Systems and Control Theory with a focus on Unmanned Aerial Vehicles (UAVs). His research integrates advanced control systems, energy storage solutions, and aerodynamics to enhance UAV performance and safety. He holds a Doctorate in Aeronautical Engineering from Loughborough University and a Postgraduate Certificate in Teaching from the University of Hertfordshire. Education/Academic Qualifications: Doctorate in Aeronautical Engineering (1983–1987), Loughborough University Postgraduate Certificate in Teaching & Learning (2006), University of Hertfordshire Bachelor's in Aeronautical Engineering (1978–1982), Loughborough University Research Interests include: Autonomous Systems and UAV Flight Control Propulsion and Energy Storage for Unmanned Aircraft Advanced Kalman Filter Applications in DSP Aerodynamics of Sniper Bullets and Wind Turbines His work emphasizes interdisciplinary collaboration across propulsion, avionics, and structural engineering to advance autonomous aviation technology. Key Research Trends: Recent articles focus on high-altitude UAV fuel systems, parametric cost models for aircraft design, and multi-point angle-of-attack sensing for flight safety. Collaborations span energy storage, environmental impact analysis, and mobile technology for rural applications. Scientific Awards: 2018 Faculty of Engineering and Computing & Maths Intellectual Property Competition Advising & Grants: Currently accepting PhD students and leading projects like the Skyfarer IUK Project (2020) on UAV technology. Active in the IMechE UAS Steering Committee, promoting standards for unmanned aerial systems. Labs/Teams: Engaged in cross-disciplinary research groups focusing on UAV design, control systems, and renewable energy integration. His work bridges academic innovation with industry applications in aerospace and energy sectors.

Gao Huijunمشاهده پروفایل

استاد

• Networked Control Systems
• Signal Processing
• Image Processing
• +۷ مورد دیگر

Prof. Gao Huijun is a Full Professor at the School of Aeronautics and Astronautics, Harbin Institute of Technology (HIT), where he also serves as Director of the Research Institute of Intelligent Control and Systems. He holds honorary positions at The University of Hong Kong and the University of Alberta. His research focuses on networked control systems, robotics, and signal processing, with over 380 SCI publications and an H-index of 120. Positions: Director of Interdisciplinary Science Research Center (2019–present), Dean of School of Science (2015–2019), and Honorary Professor at The University of Hong Kong (2009–present). Education: Ph.D. in Control Science and Engineering from HIT (2005), postdoc at University of Alberta (2005–2007). Research interests span networked control systems, multi-agent systems, and opto-mechanical integration. His work has led to 100+ patents and prestigious awards like the IEEE Fellow (2013) and National Natural Science Award (2014). Editorial roles include Co-Editor-in-Chief of IEEE Transactions on Industrial Electronics and Senior Editor roles in multiple journals. He has advised over 30 doctoral students, many of whom hold academic or industry leadership roles. Key Awards: National Natural Science Award (2014), China Youth May Fourth Medal (2011), Highly Cited Researcher (2014–2020). Grants: Chief Scientist of National Key R&D Programs, Director of China Postdoctoral Science Foundation. Labs/Teams: Leads the Research Institute of Intelligent Control and Systems, focusing on interdisciplinary projects like AOI systems and industrial robotics.