جست‌وجوی استاد و پژوهشگر

Hafiz Malikمشاهده پروفایل

استاد

• Automotive Cybersecurity
• Deepfake Detection
• Sensor Security
• +۶ مورد دیگر

Hafiz Malik is a Professor in the Department of Electrical and Computer Engineering at the University of Michigan - Dearborn within the College of Engineering and Computer Science . His research focuses on automotive cybersecurity, deepfakes, sensor security, IoT security, and multimedia forensics, with funding from the National Science Foundation, National Academies, Ford Motor Company, and Marelli, Inc. Ph.D., Electrical and Computer Engineering, University of Illinois at Chicago (2006) M.S., Electrical and Computer Engineering, University of Illinois at Chicago (2004) B.S., Electronics and Communication Engineering, University of Engineering and Technology, Lahore, Pakistan (1999) His research interests span Computing and Networks , Cybersecurity , Data Science , Machine Learning , and Robotics . He has published over 150 articles in peer-reviewed journals and conferences. His recent work trends include automotive cybersecurity , deepfake detection , and sensor security , reflecting his expertise in cyber-physical systems and information fusion . UM-Dearborn 2022 Distinguished Research Award College of Engineering and Computer Science 2020 Excellence in Research Award Malik also leads the Information Systems, Security, and Forensics (ISSF) Laboratory and is involved in organizational leadership for the Dearborn Artificial Intelligence Research Center and the Global Foundation for Cyber Studies and Research .

Alireza Mohammadiمشاهده پروفایل

دانشیار

• Robotics
• Control Systems
• Cyber-Physical Systems
• +۵ مورد دیگر

Dr. Alireza Mohammadi is an Associate Professor in the Electrical and Computer Engineering Department at the University of Michigan–Dearborn. He directs the MSE-Robotics Engineering program and leads the Robotic Motion Intelligence (RMI) Lab, established in 2018. Ph.D., Electrical and Computer Engineering, University of Toronto (2016) M.Sc., Electrical and Computer Engineering, University of Alberta (2011) B.Sc., Electrical Engineering, Sharif University of Technology His research focuses on robotics, control systems, and cyber-physical systems, with funding from NSF, Ford, NASA, ASEE, and the Lemelson Foundation. Key projects include cybersecurity for autonomous vehicles, protein folding algorithms, and collaborative robotic car-painting. Scientific recognitions include PEF Fellow (University of Michigan) Best Paper Runner-Up (AutoSec@NDSS22) Automatica Editor's Choice (2021) AUVSI XCELLENCE in Academic Research Finalist Dr. Mohammadi advises students in robotics and control systems, including Calvin Cheung, Waqas Manzoor, Amal Kacem, and Khalil Zbiss. His lab collaborates with Ford Motor Company, NASA, and academic institutions on motion control and cybersecurity challenges.

Robert Geiseمشاهده پروفایل

استاد

• Electromagnetic Compatibility
• Navigation Systems
• Antenna Design
• +۲ مورد دیگر

Prof. Dr. Robert Geise is a Professor at HTWK Leipzig's Faculty of Digital Transformation, where he serves as Vice Dean, Research Officer, and Officer for International Relations. His academic roles include teaching courses such as Navigation and Communication Systems, Antennas, Measurement Techniques, and Radio Frequency Technology. Geise leads cutting-edge research projects, including BMWK-funded 'Navant-NG' (drone-based navigation inspections) and DFG-funded 'AppFun' (electromagnetic interference analysis). His research focuses on electromagnetic compatibility (EMC) , navigation system integrity, antenna design, and advanced measurement methodologies. Publications emphasize aviation safety, signal propagation, and regulatory frameworks, with applications in drone technology and renewable energy policy. Geise's work bridges engineering precision with legal compliance, particularly in aviation and wind energy contexts. He actively contributes to projects like 'min-VOR-Win' (wind turbine navigation compatibility) and develops scalable measurement systems for industrial and aviation applications. No awards or advised students are documented in available sources.

Erik Vilain Thomsenمشاهده پروفایل

استاد

• Ultrasonics
• Biomechanics
• Microelectromechanical Systems
• +۵ مورد دیگر

Erik Vilain Thomsen is a Professor at the Department of Health Technology at the Technical University of Denmark (DTU). He leads research in ultrasound imaging , transducer engineering , and microelectromechanical systems (MEMS) , focusing on advancing 3D ultrasound technologies and biomechanical applications through the MEMS Applied Sensors Group. Key Research Areas: Ultrasonics, Biomechanics, MEMS, Transducer Design, Medical Imaging, Silicon Material Science. His recent publications highlight breakthroughs in 3D ultrasound beamforming , polymer acoustic lens optimization , and super-resolution imaging using erythrocytes. He actively supervises PhD candidates in projects like Anodic Bonded CMUTs and Micromachined 2D Transducers , emphasizing medical imaging quality and cost-effective healthcare solutions . Supervision & Collaboration: As a main supervisor, he guides students in ultrasound transducer development and participates in long-term projects like Silicon Germanium HBT's since 1992. He engages in peer review (e.g., IEEE International Ultrasonics Symposium) and collaborates internationally on ultrasonic imaging advancements. Labs/Groups: MEMS Applied Sensors Group, DTU Health Technology.

Daniel Haugård Olesenمشاهده پروفایل

دانشیار

• Geodesy
• Earth Observation
• GNSS (Global Navigation Satellite Systems)
• +۱۳ مورد دیگر

Daniel Haugård Olesen is an Associate Professor at DTU Space, Technical University of Denmark, within the Department of Space Research and Technology, specializing in Geodesy and Earth Observation. He leads the GNSS research group, which focuses on advanced navigation technologies, including interference detection, precise positioning, and sensor fusion for drones and robots. Institution: Technical University of Denmark (DTU) School: DTU Space Department: Department of Space Research and Technology Research Division: Geodesy and Earth Observation (GEO) Role: Associate Professor and Head of GNSS Research Group His research interests span GNSS signal integrity, space weather impacts, RTK/PPP positioning, multi-sensor fusion, and applications in environmental monitoring using unmanned systems. He actively contributes to hydrological studies through drone-based river monitoring, leveraging LiDAR, sonar, radar, and GNSS-R techniques. The recent publication trends reflect a strong focus on applying UAS and GNSS technologies to solve real-world environmental challenges, particularly in river hydraulics, surface water dynamics, and soil moisture sensing. His work integrates space-based observation with autonomous platforms, emphasizing reliability, precision, and scalability. Keywords across articles include Earth Observation, Remote Sensing, Hydrology, Navigation, and Signal Processing, with specific subfields such as GNSS interference mitigation, Doppler radar velocimetry, and ionospheric scintillation analysis. Daniel Olesen supervises several PhD projects, indicating an active mentoring role in training next-generation researchers. Notable projects include GNSS-R from UAS, semi-autonomous navigation for river monitoring, and ionospheric effects on GNSS signals. While no specific scientific awards are listed in the provided text, his sustained research output and leadership in key projects suggest recognition within the scientific community. GNSS Reflectometry (GNSS-R) from Unmanned Aerial Systems (2024–2027) Semi-autonomous navigation of UAS for river monitoring (2023–2026) Ionospheric effects on GNSS signals (2020–2024) GNSS Jamming Detection and Localization (2019–2024) Relative positioning and attitude from UAVs (2017–2021) He leads the GNSS research group at DTU Space, which operates multiple state-of-the-art GNSS CORS networks and develops cutting-edge methods for reliable positioning in challenging environments. The team works at the intersection of geodesy, space science, and robotics, fostering interdisciplinary collaboration to advance autonomous navigation and Earth observation capabilities.

Minsung Kimمشاهده پروفایل

استادیار

• Quantum Computing
• Wireless Communications
• Artificial Intelligence
• +۳ مورد دیگر

Minsung Kim is an Assistant Professor at the Department of Computer Science and WINLAB at Rutgers University , where he leads the EXceL: NextG Wireless and Emerging Computing Systems Laboratory . He previously served as a Postdoctoral Associate at Yale University and earned his Ph.D. in Computer Science from Princeton University , supported by the Siebel Scholars Fellowship and Qualcomm Innovation Fellowship . Research Focus: Quantum and quantum-inspired computing systems for next-generation wireless networks, particularly accelerating baseband processing via quantum optimization techniques. His work bridges wireless communication, AI, and emerging computational paradigms like Ising machines and MIMO systems. Scientific Awards: Prof. Chin Ok Lee & Ms. Kwanghee Kim Early Career Award (2025) Siebel Scholars Fellowship (2024) KOCSEA Moon-Jung Chung Scholarship (2023) Qualcomm Innovation Fellowship (2021) Advising: Mentors Ph.D. students Shuo Huang and Zeqiao Zhou , and postdoc Byungjun Kim . Previously advised visiting students at Yale and Princeton.

Wei Yuمشاهده پروفایل

استاد

• Network Information Theory
• Wireless Communications
• Optimization
• +۶ مورد دیگر

Professor Wei Yu is a Canada Research Chair (Tier 1) in Information Theory and Wireless Communications at the University of Toronto , Department of Electrical and Computer Engineering. He received his Ph.D. in Electrical Engineering from Stanford University (2002) and B.A.Sc. in Computer Engineering and Mathematics from University of Waterloo (1997). Key roles: IEEE Fellow, Fellow of Canadian Academy of Engineering, Member of Royal Society of Canada Editorial leadership: IEEE Transactions on Wireless Communications, IEEE Transactions on Information Theory Research Interests span network information theory, convex optimization, wireless communications, and broadband access networks. His work focuses on multiuser information theory, MIMO systems, and 5G/6G network optimization. Publications reflect expertise in reconfigurable intelligent surfaces (RIS), covariance-based activity detection, and fractional programming for signal processing. Scientific Recognition includes multiple IEEE Best Paper Awards (2008, 2017, 2021), NSERC Steacie Fellowship (2015), and the 2024 IEEE Joint Communications/Information Theory Society Paper Award. He is a Clarivate Highly Cited Researcher. Teaching Contributions include ECE1502 (Information Theory), ECE431 (Digital Signal Processing), and ECE1505 (Convex Optimization), with a focus on mathematical foundations and practical applications in communications.

Raviraj Adveمشاهده پروفایل

استاد

• Wireless Communications
• Radar Signal Processing
• Cooperative Networks
• +۷ مورد دیگر

Professor Raviraj Adve is affiliated with the University of Toronto , working in the Department of Electrical and Computer Engineering and cross-listed with the Electromagnetics Group . He holds a PhD in Electrical Engineering from Syracuse University (1996) and previously worked at Research Associates for Defense Conversion Inc. (1997–2000). Education: B.Tech, Indian Institute of Technology Bombay (1990) PhD, Syracuse University (1996) Research Interests span two main areas: Wireless Communications (heterogeneous networks, massive MIMO, cooperative communication, resource allocation) and Radar Signal Processing (waveform diversity, space-time adaptive processing, HF radar systems). His work emphasizes practical algorithm development for real-world constraints. Scientific Contributions include 15 recent articles covering cooperative networks , radar clutter modeling , low-complexity MIMO algorithms , and molecular communication . Notable awards: IEEE Fellow (2017), Young Radar Engineer of the Year (2009), and multiple teaching awards. Leadership Roles: Vice-chair of IEEE Radar Systems Panel, Associate Editor for IEEE Trans. on Aerospace and Electronic Systems , and editorial board member for IET Trans. on Radar, Sonar and Navigation .

Mostafa Kavehمشاهده پروفایل

استاد

• Statistical Signal Processing
• Wireless Communications
• Image Processing
• +۳ مورد دیگر

Mostafa Kaveh is a Professor in the Department of Electrical and Computer Engineering at the University of Minnesota, College of Science and Engineering. His research spans statistical signal processing, wireless communications, image processing, and biomedical ultrasound imaging. He has held leadership roles including Department Head (1990-2005), Associate Dean for Research and Planning (2005-2018), and Dean of the College of Science and Engineering (2018-2022). His academic credentials include a B.S. and Ph.D. from Purdue University (1969, 1974) and an M.S. from UC Berkeley (1970). Kaveh’s research focuses on: Statistical signal processing for antenna arrays and mobile localization Wireless communication systems with multiple antennas and collaborative transmission Image restoration algorithms based on partial differential equations Medical image processing for tomography and reconstruction Signal processing applications in genomics and biotechnology Google Scholar publications highlight trends in array signal processing, direction-of-arrival estimation, wireless channel modeling, and medical imaging techniques. His work has influenced GRAPPA algorithms for MRI, space-time interference-canceling receivers, and genomic data analysis.

Wendy Chenمشاهده پروفایل

مدرس ارشد

• AI Acceleration with Photonic Computing and Communication
• Resource Optimization in Computer Systems/Networks/Architectures
• Parallel and Distributed Computing
• +۵ مورد دیگر

Dr. Yawen (Wendy) Chen is a Senior Lecturer at the University of New South Wales (UNSW Canberra campus) , affiliated with the School of Systems & Computing . She holds a PhD in Computer Science from the University of Adelaide and focuses on interdisciplinary research at the intersection of photonic computing, AI acceleration, and network optimization. Education: PhD in Computer Science (University of Adelaide) Her research spans computer networks/systems , parallel/distributed computing , photonic computing/communication , and AI-related education . Recent publications highlight advancements in optical network-on-chips (ONoC), energy-efficient protocols for WBANs, and hybrid electrical-photonic computing architectures. Dr. Chen actively recruits PhD and Master’s students with expertise in photonic computing, AI accelerators, and network optimization. She offers scholarships of $37,684 (AUD) for eligible candidates.

Venkat Arunمشاهده پروفایل

استادیار

• Networked systems
• Formal methods
• Internet congestion control
• +۴ مورد دیگر

Venkat Arun is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin, College of Natural Sciences. His research focuses on making networked systems robust and performant through the application of formal methods. Previously, he completed his PhD at MIT and undergraduate studies at IIT Guwahati. He co-leads the UT Networked Systems Lab (UTNS) and has developed algorithms deployed at Meta. His research interests center around networked systems and formal methods, with a focus on developing conceptual, mathematical, and automated tools to design provably performant networked systems. Arun's work spans internet congestion control, video streaming, privacy-preserving computation, wireless networks, and mobile systems. A common theme across his research is using theoretical ideas to gain insights into real-world systems that would be difficult to discover otherwise. His recent publications demonstrate a strong focus on performance verification and synthesis for networked systems, with significant contributions to congestion control algorithms. His work bridges theoretical foundations with practical implementations, as evidenced by the deployment of his algorithms at Meta. The research spans formal verification techniques, network protocol design, and performance analysis across various networked applications. Scientific Awards: MIT EECS G. M. Sprowls PhD Thesis Award in Computer Science (2024) ACM SIGCOMM Doctoral Dissertation Award Runner-Up (2024) Marconi Society Young Scholar Award (2023) ACM SIGCOMM best student paper award (2022) ACM SIGCOMM best paper award (2017) MIT Jacobs Presidential Fellowship (2017) President of India Gold Medal - IIT Guwahati (2017) KVPY Government of India Scholarship (2013) Venkat Arun currently advises three PhD students: Haoyu Li (co-advised with Aditya Akella), Tony (Jia) Pan (co-advised with Isil Dillig), and Saarth Deshpande (co-advised with Neeraja Yadwadkar). His research group is funded by NSF grants including "Nets: Medium: An End-To-End Framework For Network" (2024) and "FMitF: Performance Verification for Networked Systems" (2024), as well as a generous gift from Mibura (2024). The group is managed by Destiny Turner. He leads several major research projects including Performance Verification and Synthesis, "Solving" Congestion Control, and Metasurfaces with Thousands of Antennas. Arun teaches CS 395T: Performance Analysis of Networked Systems and CS 356: Computer Networks at UT Austin.

Alfonso de Hoyos Fernández de Córdovaمشاهده پروفایل

پژوهشگر

• Transport Engineering
• Automotive Engineering
• Neuroscience
• +۷ مورد دیگر

Alfonso de Hoyos Fernández de Córdova is affiliated with the Higher Polytechnic School at Antonio de Nebrija University , specializing in Transport Engineering and Infrastructure within the GREEN Research Group on Automotive Engineering . He holds dual PhDs: one in Neuroscience (2011, Complutense University of Madrid) for work on Synchronization and coherence in brain activity , and another in Automotive Engineering (2025, Universidad Antonio de Nebrija) for research on Non-invasive methodology for vehicle suspension parameter identification . Education: PhD in Neuroscience, Complutense University of Madrid (2011) PhD in Automotive Engineering, Universidad Antonio de Nebrija (2025) His research spans Transport Engineering , Automotive Systems , Cardiology , and Biomedical Imaging , focusing on hemodynamic assessment of coronary circulation , non-destructive testing of magnetic materials , computational fluid dynamics , and magnetoencephalography . He has pioneered methodologies for intracoronary pressure and flow velocity analysis and microvascular conductance evaluation , integrating CFD simulations with clinical diagnostics to improve cardiovascular interventions. Email: ahoyos@nebrija.es

Reinhold Häb-Umbachمشاهده پروفایل

استاد

• Statistical Signal Processing
• Machine Learning
• Speech Processing
• +۷ مورد دیگر

Reinhold Häb-Umbach is a distinguished Professor in the Communications Engineering Department at the University of Paderborn, leading the Heinz Nixdorf Institute's Speech and Communications group. His work spans statistical signal processing and machine learning for speech and audio applications , with a focus on robustness and real-world deployment. His research integrates probabilistic models with deep learning , addressing challenges in speech separation , noise suppression , and acoustic distance estimation . Recent projects include WestAI , SAIL , and TRR 318 , emphasizing AI-driven solutions for sociotechnical systems. 2020: IEEE Fellow 2015: ISCA Fellow 2021-2023: ISCA Distinguished Lecturer Over 300 peer-reviewed publications He has received multiple best student paper awards at venues like IWAENC , Interspeech , and ASRU , and has contributed to 15 competitive DFG grants . His leadership roles include Technical Program Committee Chair for Interspeech 2024 and editorial roles in IEEE journals.

• Neuroscience
• Neuroimaging
• EEG
• +۳ مورد دیگر

Sean Fitzgibbon is a Postdoctoral Researcher at the Nuffield Department of Clinical Neurosciences , University of Oxford, affiliated with the FMRIB Analysis Group and the Developing Human Connectome Project . His research focuses on neuroimaging methodology, particularly in EEG and fMRI data analysis, with an emphasis on artifact removal, functional connectivity, and automated processing pipelines for neonatal brain imaging.

Joanna Tomasikمشاهده پروفایل

پژوهشگر

• Discrete optimization
• Algorithms
• Complexity theory
• +۱ مورد دیگر

Joanna Tomasik is a researcher affiliated with the Interdisciplinary Laboratory of Digital Sciences. Her work focuses on discrete optimization, algorithms, complexity theory, and performance evaluation. Research interests include network optimization, quantum computing applications, cloud energy efficiency, and combinatorial problem-solving. She has contributed to areas like simulated annealing, Latin hypercube designs, and optical network performance. Her publications reveal a trend toward algorithmic innovation, particularly in wireless and ad hoc networks, cloud computing, and quantum annealing. Topics span resource allocation, congestion control, and energy-aware scheduling.