جست‌وجوی استاد و پژوهشگر

Daniel J. Packمشاهده پروفایل

استاد

• Unmanned Aerial Vehicles
• Intelligent Control
• Automatic Target Recognition
• +۷ مورد دیگر

Daniel J. Pack is the Dean of the School of Engineering and Computer Science at Baylor University, a position he assumed on June 1, 2023. Previously, he served as Dean at the University of Tennessee at Chattanooga (UTC) from 2015, leading departments in civil, chemical, computer, electrical, and mechanical engineering, as well as engineering management and technology. His educational background includes: Bachelor of Science in Electrical Engineering – Arizona State University Master of Science in Engineering Sciences – Harvard University Ph.D. in Electrical Engineering – Purdue University Visiting Scholar – MIT-Lincoln Laboratory Dr. Pack's research focuses on unmanned aerial vehicles, intelligent control, robotics, automatic target recognition, and engineering education . His work emphasizes autonomous systems, cooperative control, and embedded systems design, contributing to both defense and educational applications. He has co-authored seven textbooks and published over 130 technical papers. The most recent articles reflect a strong trend in autonomous systems, multi-vehicle coordination, intelligent control, and educational innovation . Topics span from deep learning in UAV imagery to experiential learning frameworks, indicating a dual focus on cutting-edge robotics and transformative engineering pedagogy. His scientific awards include: Carnegie U.S. Professor of the Year (2005) Frank J. Seiler Research Excellence Award Tau Beta Pi Outstanding Professor Award Academy Educator Award Magoon Award Dr. Pack has advised numerous students and led major research initiatives, particularly in unmanned systems. He directed the Academy Center for Unmanned Aircraft Systems Research at the USAFA and has secured significant research grants. His editorial roles include Associate Editor for IEEE Systems Journal and Editor-at-Large for Journal of Intelligent & Robotic Systems. He is actively involved in professional societies such as IEEE, ASEE, Eta Kappa Nu, and Tau Beta Pi, and is a registered Professional Engineer in Colorado. His leadership fosters experiential learning environments across bachelor’s, master’s, and doctoral engineering programs.

• Aerial Robotics
• Unmanned Aerial Vehicles (UAVs)
• Remote Sensing
• +۱۲ مورد دیگر

João Pedro Matos-Carvalho is an Assistant Professor at Lusófona University in Lisbon, affiliated with the School of Engineering and the Department of Electrical and Computer Engineering. He is also an Integrated Member of the Center of Technology and Systems (CTS) at UNINOVA and COPELABS, Lusófona University, contributing to interdisciplinary research in robotics and intelligent systems. Ph.D. in Electrical and Computer Engineering, FCT NOVA (2021) M.Sc. (Hons.) in Electrical and Computer Engineering, FCT NOVA (2017) His research focuses on aerial robotics, machine learning, remote sensing, and sensor networks, with applications in UAV navigation, precision agriculture, environmental monitoring, and embedded AI. He has made significant contributions to GPS-denied navigation, multispectral imaging, and AI-driven signal processing. The recent publications reflect a strong trend in integrating deep learning with real-world engineering systems, particularly in UAV autonomy, IoT, and human-centric applications like fall detection and online learning analysis. His work spans algorithm design, software development, and practical deployment in complex environments. Best Paper Award at IEEE Conference (2018) Distinguished Paper Award by LASIGE at FCUL (2021) Best Poster Presentation Award at International Complex Systems and Their Applications Conference (2023) He has secured the competitive Scientific Employment Stimulus (CEEC) grant from FCT and has advised or collaborated on multiple research projects. He has guest-edited special issues in journals such as Drones and Frotiers in Computer Science , and serves as a reviewer for leading scientific journals. He leads the development of open-source tools like AutoNAV and Raster Forge, supporting simulation and geospatial analysis. He is actively involved in research teams at CTS-UNINOVA and COPELABS, focusing on intelligent systems, aerial robotics, and data fusion. His lab work emphasizes practical UAV platforms, sensor integration, and AI deployment in real-time systems.

• Robotics
• Machine Learning
• Electrical Engineering
• +۳ مورد دیگر

Xinyu Qin is a Professor at the Department of Electrical and Computer Engineering within the School of Information Engineering at Guangdong University of Technology. His research focuses on advanced robotics, signal processing, and integrated circuit design, contributing to fields like multi-manipulator systems and Delta-Sigma modulators. Education: Affiliated with prestigious institutions through collaborative research Research Interests: Robotics, Machine Learning, Electrical Engineering His recent publications (2023-2025) demonstrate expertise in robotic task allocation, high-speed circuit design, and explainable AI for healthcare. Award-winning work includes Interactive Explainable Deep Survival Analysis (2024) and SVP: Safe and Efficient Speculative Execution Mechanism through Value Prediction (2023). Key collaborations involve Guoxing Wang and Liang Qi across 16 records. Current projects involve optimizing convolutional neural network accelerators, analyzing atmospheric river impacts on Greenland's crustal deformation, and advancing MASH Delta-Sigma modulator architectures. His work bridges theoretical innovation with practical applications in smart energy systems and autonomous robotics.

Yu-Lin Weiمشاهده پروفایل

عضو هیئت علمی

• Audio Signal Processing
• Wireless Communication
• Indoor Positioning Systems
• +۴ مورد دیگر

Yu-Lin Wei is a Teaching Assistant Professor in the Department of Electrical and Computer Engineering at the University of Illinois at Urbana-Champaign (UIUC). He holds a Ph.D. from UIUC (2024), and M.S. and B.S. degrees in Computer Science and Information Engineering from National Taiwan University (2016 and 2014, respectively). His research focuses on audio signal processing, IoT systems, wireless/visible light communication, and indoor positioning. He has been honored with the ECE Rambus Fellowship (2020-2021) and was a Young Researcher at the Heidelberg Laureate Forum (2019). He teaches CS/ECE 438: Communication Networks and CS/ECE 434: Real-World Algorithms for IoT and Data Science . His work spans innovations in acoustic augmented reality (Ear-AR), teeth activity sensing via earphones (EarSense), and positioning systems using polarized light (CELLI). His research group, SiNRG, explores signal processing and IoT applications under the advisement of Romit Roy Choudhury. Key contributions include MobiSys Best Demo Runner-up (2017) for CELLI and advancements in sample-constrained optimization for audio personalization. He has contributed to IEEE standards (e.g., 802.15.7r1) and served as a tutorial speaker at MobiCom and conference co-chair roles.

• Cell Mechanics
• Tissue Dynamics
• Mechanobiology
• +۴ مورد دیگر

Raimon Sunyer Borrell is a Researcher at the Institute for Bioengineering of Catalonia (IBEC), where he leads investigations within the Integrative Cell and Tissue Dynamics group. His work bridges biophysics, bioengineering, and cell biology to decipher how mechanical forces govern cellular and tissue behavior in physiological and pathological contexts. His primary research focuses on mechanobiology, particularly collective cell migration, durotaxis (stiffness-guided migration), and tissue dynamics. He investigates how cells sense mechanical cues through adhesion complexes like E-cadherin, with applications in understanding developmental processes, sleep apnea pathophysiology, and circadian rhythm disruptions. His interdisciplinary approach combines advanced experimental techniques—including atomic force microscopy, microfluidic platforms, and 3D tissue models—with computational modeling to quantify force transmission and tissue remodeling. Analysis of his 15 most recent publications reveals consistent innovation in developing physiomimetic models for disease study (e.g., intermittent hypoxia systems for sleep apnea) and fundamental discoveries about collective cell behaviors. His work demonstrates how mechanical coordination across cell clusters enables optimal migration through complex environments, with implications for regenerative medicine and tissue engineering. Dr. Sunyer actively contributes to IBEC's collaborative ecosystem, working within the Integrative Cell and Tissue Dynamics group that develops cutting-edge tools for probing cellular mechanics. His research directly supports IBEC's mission to translate fundamental discoveries into biomedical applications through interdisciplinary collaboration.

• Human-Computer Interaction
• Tangible Interfaces
• Musical Interaction
• +۵ مورد دیگر

Dr. Sergi Jordà is a Senior Researcher and Associate Professor at the Music Technology Group of Universitat Pompeu Fabra (UPF) in Barcelona. He obtained his B.S. in Fundamental Physics (1986) and PhD in Computer Science and Digital Communication (2005) from UPF. He leads the Music & Advanced Interaction (MAIn) team and teaches courses in Computer Music, Audio Signal Processing, Human-Computer Interaction (HCI), and Interactive Media. In 2011, he joined the tenure-track faculty at UPF. Research Interests Jordà's research focuses on the intersection of Human-Computer Interaction (HCI) and tangible musical interfaces , including applications in education, collaborative music creation, and brain-computer interfaces . His work explores how tabletop interfaces and visual feedback can enhance intuitive instrument design and real-time performance. He is best known for co-inventing the Reactable , a tangible tabletop musical instrument that gained global recognition after being used by Icelandic artist Björk in her 2007-08 world tour. Scientific Awards Prix Ars Electronica Golden Nica (2008) MIDEM Hottest Music Biz Start-Up Award (2008) Yellow Pencil, D&AD Design Awards (2008) Rolling Stone Magazine's Hot Instrument of the Year (2007) Premi Ciutat de Barcelona (1999, 2007) Möbius International Award (2001) Innova Business Ideas Contest (2008) Projects and Grants He has participated in over 30 international scientific committees, including chairing TEI'13 (Tangible, Embedded and Embodied Interaction Conference) . Jordà has secured funding from the European Commission and Spanish government for six research projects, two as Principal Investigator (IP). In 2009, he co-founded the spin-off company Reactable Systems , which launched Reactable Mobile for iOS devices in 2010.

Muhammad Sajjadمشاهده پروفایل

دانشیار

• Computer Vision
• Image Understanding
• Pattern Recognition
• +۱۲ مورد دیگر

Muhammad Sajjad is an Associate Professor at the Department of Computer Science, Islamia College University Peshawar, Pakistan, and an ERCIM Research Fellow at the Norwegian University of Science and Technology (NTNU), Norway. His academic career spans teaching, research leadership, and editorial contributions to international journals. Education: Master’s in Computer Science (2012) from the College of Signals, National University of Sciences and Technology (NUST), Pakistan; Ph.D. in Digital Contents (2015) from Sejong University, South Korea. His research focuses on computer vision , image processing , and deep learning , with applications in medical imaging , fog computing , and autonomous navigation . He leads the Digital Image Processing Laboratory, mentoring students in areas like multi-modal data mining and video analytics . He has authored over 65 peer-reviewed publications and serves as an Associate Editor for IEEE Access and a Guest Editor for IEEE Transactions on Intelligent Transportation Systems .

• Quantum Communications
• Quantum Sensing
• Wireless Communications
• +۷ مورد دیگر

Professor Robert Malaney is a faculty member in the School of Engineering, Department of Electrical Engineering and Telecommunications at the University of New South Wales (UNSW), Sydney, Australia. He has held previous academic positions at the California Institute of Technology (USA), the University of California (USA), the University of Toronto (Canada), and the CSIRO (Australia). Professor Malaney specializes in quantum communications, quantum sensing, wireless communications, optical communications, satellite communications, quantum physics, and astrophysics. His research focuses on developing practical quantum communication systems with particular emphasis on satellite-based applications. He has made significant contributions to quantum key distribution (QKD), quantum networking, and the integration of quantum and classical communication systems. His work addresses critical challenges in quantum communications including atmospheric turbulence compensation, phase estimation, error mitigation, and spatial diversity exploitation. Analysis of Professor Malaney's recent publications (2023-2025) reveals an intensive focus on advancing satellite-to-earth quantum communications. His work demonstrates leadership in developing quantum routing protocols, machine learning applications for quantum systems, and hybrid quantum-classical communication techniques. These publications highlight his commitment to solving practical implementation challenges for global quantum networks, with particular attention to real-world constraints like atmospheric interference and signal degradation in space-to-ground links. Professor Malaney has maintained an extensive collaborative network across multiple institutions and research domains. His work bridges theoretical quantum information science with practical engineering applications, positioning him as a key contributor to the emerging field of quantum communications infrastructure.

Howard J Grittonمشاهده پروفایل

استادیار

• Neuroscience
• Cognitive Neuroscience
• Neuromodulation
• +۵ مورد دیگر

Howard J Gritton serves as Assistant Professor in the Department of Comparative Biosciences at the University of Illinois at Urbana-Champaign's College of Veterinary Medicine, with additional appointments in Bioengineering, the Beckman Institute for Advanced Science and Technology, and the Carl R. Woese Institute for Genomic Biology. His research focuses on neural circuit mechanisms underlying cognition and disease. His educational background includes: B.S. in Biology from University of Utah Ph.D. in Neuroscience from University of Michigan Post-doctoral training at Boston University Dr. Gritton's research investigates how neuromodulators (acetylcholine, dopamine, norepinephrine) regulate brain rhythms that coordinate neural activity across regions during learning and memory. His lab employs calcium/voltage imaging , electrophysiology , and optogenetic/chemogenetic tools in mouse models to study circuit mechanisms in autism and Parkinson's disease, with particular focus on excitatory/inhibitory balance and oscillatory dynamics. His recent publications (2023-2025) demonstrate expertise in neural oscillation analysis, neuromodulation, and in vitro neural platforms, spanning computational modeling, motor neuroscience, and neuroengineering applications. Key themes include theta/gamma rhythms in spatial navigation, cholinergic signaling mechanisms, and beta-frequency stimulation for motor function. Dr. Gritton actively recruits graduate students for his lab, focusing on systems, behavioral, and cognitive neuroscience approaches to understanding neuropsychiatric disorders.

Stefan Brüggenwirthمشاهده پروفایل

استاد

• Cognitive Radar
• Radar Systems
• Machine Learning
• +۵ مورد دیگر

Prof. Dr.-Ing. Stefan Brüggenwirth serves as a Professor at Ruhr University Bochum within the Faculty of Electrical Engineering and Information Technology, specifically leading the Cognitive Sensors department. His institutional address is Cognitive Sensors, Postbox ID 37, Universitätstraße 150, D-44801 Bochum, with departmental contact via sekretariat@est.rub.de. He maintains an active research profile with continuous publications in IEEE journals and major radar conferences, demonstrating his leadership in integrating artificial intelligence with radar technology. Brüggenwirth's research centers on cognitive radar systems, where he pioneers the application of machine learning techniques to enhance radar capabilities. His work spans neural network architectures for SAR target recognition, reinforcement learning for radar resource management, and explainable AI methods for radar applications. He investigates both theoretical foundations and practical implementations, with research addressing military applications, autonomous vehicle navigation, and aerospace systems. His department connects with related research areas including plasma technology and microwave systems within the faculty's ecosystem. Analysis of his publication trends reveals a distinct progression from early cognitive systems for UAVs (2010-2013) to increasingly sophisticated AI-radar integration (2015-present). Recent work emphasizes explainable AI techniques (grad-CAM, LIME, SHAP), neural network robustness, and quality of service frameworks for radar resource management. His 2024 publications demonstrate cutting-edge applications of YOLO and complex-valued networks for target recognition and signal denoising. Brüggenwirth has contributed to significant collaborative projects including SPERI (super-resolution and target identification), PolRad (polarimetric radar technology for European defense), and KI-ROJAL. His special issue contributions in IEEE Aerospace and Electronic Systems Magazine (2020) highlight his role as a thought leader in cognitive radar. While specific grant details aren't provided, his extensive project involvement suggests successful funding acquisition across defense, aerospace, and autonomous systems domains. The Cognitive Sensors department at Ruhr University Bochum serves as his primary research base, with his work intersecting with related groups in Learning Technical Systems, Medical Engineering, and Photonics & Terahertz Technology. His research has practical applications in defense systems, autonomous driving (RADAR SLAM), and aerospace, particularly in hypersonic plasma signature measurement. He maintains connections with international researchers including S. Z. Gurbuz and M. Rangaswamy for collaborative book chapters.

Dov Krugerمشاهده پروفایل

استاد آموزشی

• High Performance Computing
• Network Programming
• 3D Printing
• +۳ مورد دیگر

Dov Kruger is an Associate Teaching Professor in the Department of Electrical Engineering at Rutgers University. He holds a BE in Electrical Engineering, an MS in Computer Science, and a PhD in Ocean Engineering, all from Stevens Institute of Technology. Prior to Rutgers, he spent 10 years as a professor at Stevens. His research focuses on high-performance computing, network programming, 3D printing, and computing education. He explores re-engineering software for efficiency, distributed programming models, and innovations in data compression and secure networking. His work also encompasses underwater acoustics and sensor systems from earlier career phases. Key themes in his recent articles include real-time video processing, federated learning privacy, AI bias mitigation, and blockchain-based systems. His earlier contributions involved underwater robotics and environmental sensor networks in estuaries. Dr. Kruger seeks collaborators in FPGA, network programming, and 3D printing. He has no listed scientific awards but maintains active research in multidisciplinary computer science and engineering education.

Phil Husbandsمشاهده پروفایل

استاد پژوهشی

• Artificial Intelligence
• Evolutionary Robotics
• Artificial Life
• +۱۲ مورد دیگر

Phil Husbands is a Research Professor of Artificial Intelligence in the Department of Informatics at the University of Sussex, School of Engineering and Informatics. He is a co-founder of the Centre for Computational Neuroscience and Robotics (CCNR) and a founding member of the Evolutionary and Adaptive Systems group (now the AI Group), reflecting his deep interdisciplinary engagement across engineering, neuroscience, and computer science. His research interests span artificial life, evolutionary robotics, biologically inspired neural networks, computational neuroscience, machine learning, and the history and philosophy of AI. He has pioneered work on GasNets (neural networks with diffusible modulators), insect-inspired navigation, and bio-inspired optimization algorithms. His work often bridges theory and application, integrating insights from biology into adaptive robotic systems. The recent publications highlight a strong trajectory in bio-inspired computation, including evolutionary swarm algorithms, neuromodulation models, cognitive architectures, and tactile robotics. His work increasingly explores foundational questions in agency, time perception, and autonomy, suggesting a move toward more comprehensive models of artificial cognition. Scientific Awards: No specific awards listed in the provided text. Phil Husbands has been involved in numerous research grants from major funders including the European Union, EPSRC, BBSRC, and Wellcome Trust. He has supervised multiple doctoral students and collaborated widely, notably with Andy Philippides and Michael O’Shea. He is actively engaged in postgraduate research supervision and public dissemination of science through books like Robots: What Everyone Needs to Know . He leads and contributes to interdisciplinary research teams such as the Evolutionary and Adaptive Systems group and the Centre for Computational Neuroscience and Robotics, fostering collaboration between computer scientists, neuroscientists, and roboticists.

• Neuromorphic Computing
• Spiking Neural Networks
• Bio-inspired Artificial Intelligence
• +۸ مورد دیگر

Dr James Knight is a Senior Research Fellow in Informatics at the School of Engineering and Informatics, University of Sussex. He is currently an EPSRC Research Software Engineering Fellow (2022–2026), leading research in neuromorphic computing and spiking neural networks. His work bridges computer science, neuroscience, and robotics, with a focus on bio-inspired artificial intelligence and computational modeling of insect cognition. Education: PhD in Computer Science, University of Manchester (2013–2016) MPhil in Advanced Computer Science, University of Cambridge (2012–2013) BEng in Electronic Engineering, University of Warwick (2003–2006) His research interests center on neuromorphic computing , spiking neural networks , and bio-inspired AI , particularly drawing insights from insect neuroscience to develop efficient and robust machine learning systems. He explores event-based vision, neural hardware acceleration, and computational models of insect navigation and perception. The 15 most recent publications (2024–2025) reflect a strong trend in developing and benchmarking neuromorphic algorithms, including training methods like Eventprop, hardware-software co-design (e.g., FeNN processor), and modeling biological systems such as insect central complex and mushroom bodies. These works span journals like Nature Communications , PLoS Computational Biology , and Neuromorphic Computing and Engineering , as well as IEEE and Springer conferences. Scientific Grants: Unlocking spiking neural networks for machine learning research (EPSRC, 2022–2026) – Principal Investigator ActiveAI – active learning and selective attention for robust, transparent and efficient AI (EPSRC, 2019–2022) – Research Team Member Dr Knight actively collaborates with leading researchers including Thomas Nowotny, Andrew Philippides, and Paul Graham. His work contributes to both theoretical advances in neural computation and practical applications in robotics and AI. He is involved in developing frameworks such as NeuroBench for standardized evaluation of neuromorphic systems. Laboratories and Research Teams: He is part of the neuromorphic computing and computational neuroscience research groups at the University of Sussex, contributing to interdisciplinary projects that integrate software engineering, AI, and biological modeling.

• Biorobotics
• Computational Neuroscience
• Artificial Intelligence
• +۱۲ مورد دیگر

Professor Andy Philippides is a faculty member in the School of Engineering and Informatics at the University of Sussex, where he holds the title of Professor of Biorobotics (Informatics). He has been continuously affiliated with the university since 1995, progressing from an MSc and PhD student to a permanent academic, achieving full professorship in 2017. His work is deeply interdisciplinary, bridging robotics, neuroscience, and artificial intelligence. His research interests focus on the mechanisms of intelligent behavior through the interaction of body, brain, and environment. Key areas include visual navigation in insects and robots, neuromodulation in neural networks (e.g., GasNets), evolutionary robotics, and computer vision. He leads and contributes to high-impact projects such as Brains-on-Board, INSIGHT, and be.AI, funded by EPSRC, BBSRC, MRC, and the European Union. His recent publications (2022–2025) reflect a strong trend in bio-inspired algorithms, particularly in insect navigation, spiking neural networks, and adaptive robotics. These works span journals like PLoS Computational Biology , Frontiers in Physiology , and Biomimetics , emphasizing visual route learning, memory networks, and neuromorphic computing. He has supervised over 50 MSc theses and numerous PhD students, many of whom now hold academic or industry positions. His collaborations include prominent researchers such as Paul Graham, Phil Husbands, and Tom Collett. He is actively involved in grant-funded research, with current projects extending into 2028. Action-based bio-inspired autonomous navigation (Universities UK) Emergent embodied cognition in shallow neural networks (BBSRC) be.AI - biomimetic embodied Artificial Intelligence (Leverhulme Trust) ActiveAI - active learning and selective attention (EPSRC) He teaches courses such as Intelligence in Animals and Machines and Research Methods in Neuroscience, and has previously taught in computational neuroscience and robotics. His lab, part of the Centre for Computational Neuroscience and Robotics (CCNR), fosters interdisciplinary research in biorobotics and neural modelling.

Richard K. Martinمشاهده پروفایل

استاد

• Radio Tomographic Imaging
• Laser Radar (LADAR)
• Signal Processing
• +۷ مورد دیگر

Richard K. Martin is a Professor in the Department of Electrical and Computer Engineering at the Air Force Institute of Technology (AFIT), Wright-Patterson Air Force Base, OH. He has been a faculty member since 2004 and holds a Ph.D. in Electrical and Computer Engineering from Cornell University. Education: Ph.D., Electrical and Computer Engineering, Cornell University, 2004 M.S., Electrical and Computer Engineering, Cornell University, 2001 B.S., Electrical Engineering, University of Maryland, 1999 (Summa Cum Laude) B.S., Physics, University of Maryland, 1999 (Summa Cum Laude) His research focuses on radio tomographic imaging, laser radar (LADAR), signal processing, and engineering education . He has made significant contributions to channel equalization, wireless localization, and polarimetric LiDAR systems. His work bridges theoretical signal processing with practical defense and sensing applications. The recent articles highlight a strong trend in optical remote sensing, spectropolarimetry, and advanced signal processing for defense and surveillance. His work increasingly integrates machine learning, sensor fusion, and real-time imaging under atmospheric distortions. Scientific Awards: 2013 Air Force Outstanding Science and Engineering Educator Award Eta Kappa Nu Instructor of the Year (twice) Instructor of the Quarter (three times) Dr. Martin has led numerous student research initiatives, including the COEUR program to enrich undergraduate research. He has secured research funding in areas such as RF sensing, LADAR, and wireless security. He holds eight patents and has published extensively in IEEE journals and conferences. He leads research in the development of rapid Mueller matrix polarimeters, spectropolarimetric LADAR, and radio tomographic imaging systems , often in collaboration with students and defense labs.