جست‌وجوی استاد و پژوهشگر

Christian Holzمشاهده پروفایل

دانشیار

• Human-Computer Interaction
• Wearable Technologies
• Mixed Reality
• +۴ مورد دیگر

Prof. Christian Holz is an Associate Professor at the Department of Computer Science and Deputy Head of the Institute of Intelligent Interactive Systems at ETH Zürich. His work focuses on advancing human-computer interaction through innovations in wearable technologies, mixed reality systems, and sensor-driven applications. Key research areas include motion capture, physiological signal processing, and adaptive user interfaces. Holz leads the SIPLab (siplab.ethz.ch), producing influential work at the intersection of computer science and biomedical engineering. His research explores cutting-edge topics such as egocentric vision systems, wearable health monitoring devices, and VR/AR applications. Recent studies investigate cybersickness detection via EEG, heart rate estimation from eye-tracking cameras, and scalable motion capture using inertial/UWB sensors. Holz's work emphasizes practical applications in healthcare, education, and human-centered computing. Publications reflect a strong focus on interdisciplinary solutions, combining machine learning with sensor data analysis. Notable contributions include the EgoSim multi-view simulator, WildPPG biomedical dataset, and MiBOT cardiovascular modulation device. His research bridges theoretical advancements with real-world usability in domains like emergency response training, chronic disease monitoring, and immersive education.

Shreyas Senمشاهده پروفایل

دانشیار

• VLSI and Circuit Design
• Human Body Communication (HBC)
• Hardware Security
• +۵ مورد دیگر

Shreyas Sen is the Elmore Associate Professor of Electrical and Computer Engineering at Purdue University, jointly affiliated with the School of Biomedical Engineering. He directs the Center for Internet of Bodies (C-IoB) and leads the SPARC Lab, focusing on circuits/systems for secure, energy-efficient body-centric communication and biomedical applications. Education: B.E. (Jadavpur University, 2006), M.S. & Ph.D. (Georgia Tech, 2009-2011). His research spans Human Body Communication (HBC), hardware security, IoT/IoB systems, and low-power sensing. Notable innovations include Electro-Quasistatic HBC (EQS-HBC) technology, which enables covert body-wire communication with 100x lower energy than conventional methods. Research Themes: Secure communication for medical wearables Physical layer security in IoT Ultra-low-power biosensors Side-channel attack mitigation in cryptographic ICs Publications: Over 200 papers in top venues (ISSCC, DAC, CICC, HOST) with focus on HBC systems, electromagnetic security, and biomedical circuits. Recent work explores EQS-HBC privacy properties (Nature Scientific Reports, 2019) and 350x current-domain signature attenuation for AES security (ISSCC 2020). Awards: NSF CAREER Award (2020) AFOSR Young Investigator (2016) MIT TR35 India (2018) 9 Best Paper Awards Intel Outstanding Researcher (2020) He advises over 20 students and leads industry collaborations through Ixana Inc. (founded 2020), commercializing EQS-HBC technology. Current efforts include EQS-based authentication systems and radiation dosimetry wearables.

• Computer Vision
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Andrew Zisserman is a Royal Society Research Professor at the University of Oxford's Department of Engineering Science, affiliated with the Visual Geometry Group (VGG). His research focuses on computer vision, artificial intelligence, and neural networks, with significant contributions to multimodal learning, video understanding, and 3D scene analysis. He leads projects exploring visual-language models, audio-visual synchronization, and clinical imaging applications. Key research areas include: Video analysis and temporal modeling Multimodal systems for sign language translation and action recognition 3D shape estimation and physical property inference Foundation models and cross-modal retrieval Recent work highlights: Developed Flamingo and Tapir models for video-language tasks Advancements in spinal MRI analysis and clinical imaging Leadership in EGO4D and VoxCeleb challenges Honors include Fellowship of the Royal Society (FRS) and the ISSLS Prize in Clinical Science 2023 for spinal analysis innovations. His lab collaborates globally, emphasizing real-world applications in healthcare and autonomous systems.

Ram Vasudevanمشاهده پروفایل

دانشیار

• Optimization and control of nonlinear systems
• Legged robot locomotion
• Autonomous systems safety
• +۴ مورد دیگر

Ram Vasudevan is an Associate Professor and Associate Chair of Graduate Studies in the Department of Robotics at the University of Michigan. His research focuses on developing tools for safe and robust deployment of robotic systems, emphasizing optimization, nonlinear control, and real-world applications. Key areas include legged robot locomotion, shared control systems, and safety-critical autonomous systems. Research Interests: Optimization and control of nonlinear systems, locomotion of legged robots, shared control active safety systems, and automation of diagnostic/rehabilitative tasks. His ROAHM Lab prioritizes mathematical guarantees for robotic performance, with applications in medical robotics, autonomous vehicles, and soft robotics. Recent work emphasizes trajectory optimization, sensor fusion, and safety-aware control strategies. He has contributed to benchmarks for autonomous vehicle perception and novel methods in thermal image restoration using neural radiance fields. Awards: None explicitly listed in provided text. Labs/Teams: Directs the ROAHM Lab, collaborating on projects like robotic tail mechanics, real-time motion planning, and sensor data analysis. Active in academic conferences including RSS and ICRA.

• Integrated Circuit Design
• Biomedical Microsystems
• Low-Power Sensor Interfaces
• +۳ مورد دیگر

Dr. Jiamin Li is an Associate Professor at the School of Microelectronics, Southern University of Science and Technology (SUSTech), Shenzhen, China. She holds a Ph.D. and B.Eng. in Electrical and Computer Engineering from the National University of Singapore (NUS). Her research focuses on biomedical integrated circuits, energy harvesting, and wireless body-area networks. Education: Ph.D. and B.Eng. in Electrical and Computer Engineering from NUS Employment: Associate Professor (2024–Present), Assistant Professor (2022–2024) at SUSTech; Research Fellow at NUS Dr. Li's research addresses wireless body area powering , low-power biosignal interfaces , and intelligent biosignal processors . Her work leverages microsystem design for applications in biomedical engineering , particularly in energy-autonomous medical devices and human body-coupled communication . Her recent publications highlight advancements in concurrent power/data transmission , subharmonic pulse injection , and triboelectric energy harvesting for biomedical systems. Key venues include IEEE JSSC , Nature Electronics , and conferences like ISSCC and BioCAS. Awards: IEEE SSCS Predoctoral Achievement Award, ISSCC Best Demo Award, ASSCC SDC Best Design Award Committees: IEEE SSCS Women-in-Circuit (WiC) Committee, ISSCC Student Research Preview Committee Opportunities: Positions available for Ph.D., Master's, Postdoctoral Fellows, and Visiting Scholars

• Low-power Integrated Circuits
• Bioelectronics
• Hardware Security
• +۳ مورد دیگر

Kaiyuan Yang is an Associate Professor in the Department of Electrical and Computer Engineering at Rice University, leading the Secure and Intelligent Micro-Systems (SIMS) Lab. His research focuses on low-power integrated circuits and bioelectronic implants for applications like the Internet of Everything and medical devices. He holds a B.S. from Tsinghua University (2012) and M.S./Ph.D. degrees from the University of Michigan (2017). Research Interests: Low-power digital/analog/mixed-signal systems Bioelectronics and implantable devices Hardware security and PUF design Mixed-signal computing and emerging materials Recent work emphasizes magnetoelectric-powered implants, secure backscatter communication, and in-memory computing architectures. His publications span top venues like IEEE ISSCC, IEDM, and ACM MobiCom. Awards: 2022 NSF CAREER Award 2022 IEEE Top Picks in Hardware Security 2016 IEEE SSCS Predoctoral Achievement Award Dr. Yang serves on editorial boards for IEEE TVLSI and program committees for ISSCC/CICC. His lab develops miniature, secure, and energy-efficient systems for healthcare and IoT applications.

David Wentzloffمشاهده پروفایل

استاد

• RF integrated circuits
• Ultra-low power design
• Wireless communication
• +۴ مورد دیگر

David Wentzloff is a Professor of Electrical Engineering and Computer Science at the University of Michigan, where he has been on faculty since 2007. He directs the Wireless Integrated Circuits and Systems (WICS) group and serves as Director of the Michigan Integrated Circuits Laboratory (MICL). Wentzloff received his B.S.E. from the University of Michigan in 1999 and his S.M. and Ph.D. from MIT in 2002 and 2007. Wentzloff's research focuses on low-power integrated circuits for wireless communication in energy-constrained and volume-constrained applications. His work spans three primary areas: Synthesizable all-digital radios and radio building blocks Wireless body sensor networks (channel modeling, radios, and antennas) Radios and interfaces for millimeter-scale computing devices His innovations have significantly reduced power consumption in wireless communication for IoT devices, impacting standards including Bluetooth, WiFi, and 5G/6G. Analysis of his publication record reveals a consistent focus on ultra-low power wireless communication, with recent work emphasizing back-channel communication techniques that achieve 500x power reduction compared to conventional approaches. His research bridges theoretical circuit design with practical applications in healthcare, industrial monitoring, and consumer electronics. Wentzloff's scientific recognition includes: 2024 University of Michigan Faculty Recognition Award NSF CAREER Award (2012) DARPA Young Faculty Award (2009) Multiple best paper awards Two-time recipient of the Eta Kappa Nu Professor of the Year Award As an educator and mentor, Wentzloff has graduated 21 doctoral students and mentored dozens of master's and undergraduate researchers. He has taught courses ranging from introductory circuits to advanced graduate topics in analog and RF design. His entrepreneurial impact includes co-founding three successful companies: Everactive (formerly PsiKick), Movellus, and CubeWorks, which commercialize technologies developed in his research lab. Wentzloff leads the WICS research group, which operates within the Michigan Integrated Circuits Laboratory. His team develops cutting-edge technologies for batteryless sensing systems, millimeter-scale computing platforms, and ultra-low power wireless communication solutions that enable the next generation of Internet of Things applications.

Alexey Gorshkovمشاهده پروفایل

استاد مدعو

• Quantum Optics
• Quantum Information Science
• Condensed Matter Physics
• +۶ مورد دیگر

Alexey Gorshkov is an Adjunct Professor at the University of Maryland (UMD) affiliated with the Joint Quantum Institute (JQI) and the Quantum Information and Computer Science Laboratory (QuICS). His primary academic role is in theoretical physics, focusing on quantum optics, quantum information science, and condensed matter physics. He leads a research group exploring quantum magnetism with alkaline-earth atoms, driven-dissipative systems, topological matter, and strongly interacting photons. His work bridges AMO (atomic, molecular, and optical) systems with high-energy and condensed matter physics, emphasizing quantum simulation and novel quantum technologies like precise clocks and quantum computers. Education details are not explicitly listed, but his research collaborations with institutions like JQI and UMD suggest advanced academic training in theoretical physics. His research interests revolve around understanding and controlling quantum many-body systems, particularly in far-from-equilibrium scenarios, entanglement dynamics, and dissipation effects. He has contributed to studies on Rydberg atoms, quantum routing protocols, and error mitigation in quantum simulators. Recent articles highlight his work on quantum protocols for verifying speedups, time-independent information flow, and entanglement dynamics. His group's achievements include demonstrating one-dimensional anyons and developing methods for correlated noise estimation with quantum sensors. Awards and grants are not explicitly mentioned in the provided text, but his prolific publication record indicates sustained research impact. Labs and teams associated with him include the JQI and QuICS, where he collaborates on experimental and theoretical projects. Graduate student and postdoc positions are available in his group, focusing on areas like quantum magnetism and topological systems. His work often involves close ties with experimental groups, emphasizing practical applications of theoretical breakthroughs.

Wei Zhangمشاهده پروفایل

استاد

• Control Theory
• Optimization Theory
• Machine Learning
• +۵ مورد دیگر

Wei Zhang is a tenured Professor at the Southern University of Science and Technology (SUSTech) , Shenzhen, China, and a Senior Member of IEEE. He serves as Associate Editor for IEEE Transactions on Control System Technology and leads the CLEAR Lab (Control & Learning for Robotics and Autonomy) within the School of Automation and Intelligent Manufacturing (AiM). His career spans institutions including the University of California, Berkeley (postdoc), and The Ohio State University (Assistant/Associate Professor). Education: PhD in Electrical Engineering from Purdue University (2009), MS in Electrical and Computer Engineering from University of Kentucky (2005), BS in Automation from University of Science and Technology of China (2003) Research Interests focus on integrating control theory, optimization, and machine learning to develop intelligent systems. Key areas include: Legged Robots: Dynamic locomotion control, bio-inspired gait design, and push recovery mechanisms Autonomous Systems: Real-time motion planning, obstacle avoidance, and safe navigation in adversarial environments Smart Grids: Distributed control for energy systems and transactive energy optimization Machine Learning: Reinforcement learning for robotics, Q-learning convergence analysis, and hybrid control-learning frameworks Publication Trends highlight interdisciplinary work at the intersection of robotics and control systems. His recent 2024 papers address: Whole-body control for wheeled-quadrupedal robots Geometric object pose refinement in computer vision Task-space Riccati feedback for underactuated systems Teacher-student reinforcement learning architectures Scientific Awards include: 2016 : NSF CAREER Award 2015 : Lumley Research Award (Ohio State University) 2013 : AFOSR Summer Faculty Fellowship 2018 : National Distinguished Expert (Young, China) 2019 : International Underwater Robot Competition 2nd Prize (team advisor) Academic Leadership involves editorial roles at IEEE Transactions on Control System Technology and IEEE Transactions on Power Systems. His lab provides state-of-the-art robotics platforms including quadruped robots, Kuka manipulators, and UAVs for algorithm validation. Research collaborators span The Ohio State University , UC Berkeley , CMU , and The University of Hong Kong .

Jiaqi Gongمشاهده پروفایل

دانشیار

• Artificial Intelligence
• Smart and Connected Health
• Cyber-Physical Systems
• +۱۳ مورد دیگر

Dr. Jiaqi Gong serves as Associate Professor in Computer Science and Adjunct Associate Professor in Mechanical Engineering at The University of Alabama's College of Engineering, while directing the Alabama Center for the Advancement of Artificial Intelligence. His academic foundation includes: B.S. in Engineering, China University of Geoscience (2004) Ph.D. in Engineering, Huazhong University of Science and Technology (2010) Dr. Gong's research pioneers human-AI convergence through cyber-physical systems and smart health technologies, developing mobile/wearable platforms to enhance human perceptual, cognitive, and physical capabilities. His work spans artificial intelligence, machine learning, computer vision, and IoT with applications in healthcare, environmental monitoring, and education. The Sensor-Accelerated Intelligent Learning (SAIL) laboratory he founded drives innovation in behavior change interventions, human movement modeling, and educational data mining. Recent publications reveal strong interdisciplinary trends: healthcare AI dominates with medication adherence prediction and surgical classification systems, while environmental applications feature flood-risk communication and drought analysis. His work increasingly integrates generative AI and LLMs across domains, demonstrating methodological innovation in federated learning, knowledge graphs, and explainable storytelling frameworks. Notable recognitions include: Best Student Paper Award, IEEE/ACM Connected Health Conference (2022) Best Student Paper Award, Body Sensor Networks Conference (2019) Data Challenge Win, IEEE Biomedical Health Informatics (2018) Best Paper Award, Body Area Networks Conference (2014) Best Demonstration Award, IEEE Wireless Health Conference (2014) Dr. Gong leads significant funded projects including a $2M CDC/NIOSH grant for first responder safety and $3M NSF funding for hydrologic research. As SAIL laboratory director, he mentors students in developing clinically deployed technologies for multiple sclerosis, dementia, and mental health. Future work focuses on scaling AI applications in chronic disease management and climate resilience through the Alabama AI Center. The SAIL laboratory (founded 2017) operates as a multidisciplinary hub developing wearable/mobile systems for health applications, with active collaborations across medical clinics and engineering departments for real-world deployment of behavior change interventions and movement analysis tools.

Wenyao Xuمشاهده پروفایل

استاد

• Embedded Systems
• Cyber-Physical Systems
• Body Sensor Networks
• +۳ مورد دیگر

Wenyao Xu is a Professor and Associate Department Chair in the Department of Computer Science and Engineering at the University at Buffalo, School of Engineering and Applied Sciences. His research focuses on embedded systems, body sensor networks, biomedical signal analytics, telemedicine, and human-computer interaction. He leads the Embedded Sensing and Computing (ESC) Lab, pioneering innovations in wearable health monitoring and non-invasive medical technologies. Dr. Xu holds a PhD in Electrical and Electronics Engineering from UCLA (2013), an MEng in Embedded Systems from Zhejiang University (2008), and a BEng in Electrical Engineering from Zhejiang University (2006). He has received multiple accolades, including the UB Exceptional Scholar—Sustained Achievement Award (2021) and SEAS Senior Career Researcher of the Year (2020). His research spans cutting-edge areas like mmWave-based sensing for health monitoring, mHealth applications for behavioral interventions (e.g., Sense2Quit app for smoking cessation), and wearable devices for gait analysis and vital sign detection. Recent work includes advancements in through-clothing wound monitoring, voice- and gesture-based authentication systems, and AI-enhanced medical imaging. Publications reflect his interdisciplinary impact, with over 150 peer-reviewed papers in top venues. His lab collaborates closely with clinical partners to translate technologies into practical healthcare solutions. Dr. Xu also emphasizes mentorship, having been honored with the President Emeritus and Mrs. Meyerson Award for teaching excellence (2020).

Nabil Alshurafaمشاهده پروفایل

دانشیار

• Health Informatics
• Body Sensor Networks
• Behavioral Science
• +۷ مورد دیگر

Nabil Alshurafa is an Associate Professor at Northwestern University, holding joint appointments in the McCormick School of Engineering (Computer Science and Electrical and Computer Engineering) and the Feinberg School of Medicine (Preventive Medicine). He directs the HABits Lab, which focuses on developing mHealth systems to address health behaviors such as overeating, stress, and UV exposure. His work integrates wearable sensors, machine learning, and behavioral science to create passive sensing solutions. Education: PhD in Computer Science and Wireless Health (UCLA), MS and BS in Computer Science (UCLA). Research Interests: Body sensor networks, activity recognition, embedded systems, and health informatics. His lab designs wearable devices (e.g., neck-worn sensors, UV patches) and AI frameworks to detect behaviors like eating patterns and stress levels. Collaborations include domain experts in medicine and engineering to translate technical innovations into clinical interventions. Recent Projects: Developing systems for stress monitoring via ECG-PPG patches, UV exposure tracking, and just-in-time interventions for overeating. The lab emphasizes ethical design, privacy preservation, and user-centered technology. Students and Lab Team: Supervises PhD, MS, and undergraduate researchers in areas like machine learning, embedded systems, and health data analytics. Notable advisees include Rawan Alharbi (PhD candidate), Shibo Zhang (PhD student), and Wilson Wang (MS student). Labs/Teams: HABits Lab collaborates with experts in Preventive Medicine, Psychiatry, and Dermatology to advance interdisciplinary health research. Current projects include predictive analytics for weight loss and interventions targeting maternal stress during pregnancy.

Benjamin C.K. Teeمشاهده پروفایل

دانشیار

• Flexible Electronics
• Self-Healing Materials
• Electronic Skin (E-Skin)
• +۴ مورد دیگر

Dr. Benjamin C.K. Tee is an Associate Professor at the National University of Singapore (NUS), affiliated with the College of Engineering and the Department of Materials Science and Engineering. He leads the Sensors.AI Labs, focusing on transforming materials science, mechanics, and biology into cutting-edge technologies for robotics and healthcare in the AI era. His research explores novel materials and fabrication techniques to develop flexible, stretchable electronic sensors. These innovations enable applications in human-machine interfaces, biomedical devices, and AI-driven robotic systems. Key areas include self-healing materials, large-scale tactile sensing, and wireless health monitoring. His work has garnered international acclaim, including the James Dyson Foundation Prize (International Winner, 2021), MIT TR35 Innovator (2015), and recognition as a World Economic Forum Young Scientist (2019). His inventions have been commercialized through co-founded startups Privi Medical (acquired in 2021) and Hannah Life Technologies. Scientific Awards: National Research Foundation Fellowship (2017) MIT TR35 Innovator (Global) (2015) World Economic Forum Young Scientist (2019) James Dyson Foundation Prize - International Winner (2021) IES Prestigious Engineering Award (2020) Stanford University Top 2% Scientists (2021)

Adam Khalifaمشاهده پروفایل

استادیار

• Low-Power Electronics
• Biomedical Engineering
• Neural Engineering
• +۴ مورد دیگر

Adam Khalifa is an Assistant Professor in the Department of Electrical & Computer Engineering at the University of Florida. His research focuses on low-power analog/RF/Mixed-mode ASIC design, miniaturization of biomedical devices, wireless powering solutions, and neural stimulation/recording techniques in animal models. He holds a PhD from Johns Hopkins University and degrees from The Hong Kong University of Science and Technology. His work emphasizes implant packaging, electrode microfabrication, and coil design for medical applications. Key research areas include developing energy-efficient wireless systems for implanted devices, such as magnetoelectric antennas and galvanic body-coupled powering. He has pioneered advancements in miniaturized implantable devices, including the 'Microbead' stimulator. His NIH T32 Fellowship (2019) and Ferdinand H. Fellowship (2018) reflect his impactful contributions. Publications highlight innovations in wireless power transfer, metamaterials for biomedical implants, and injectable microdevice fabrication. His work spans from circuit-level modeling to in vivo validation, emphasizing both technical and biological integration challenges. Collaborative efforts address challenges like implant migration tracking via MRI and energy harvesting for battery-free systems.

• Machine Learning
• Computer Vision
• Robotics
• +۷ مورد دیگر

Raquel Urtasun is a Full Professor in the Department of Computer Science at the University of Toronto and a co-founder of the Vector Institute for AI. She is also the Founder and CEO of Waabi, an autonomous vehicle company. Previously, she was Chief Scientist and Head of R&D at Uber ATG (2017–2021) and held faculty positions at the Toyota Technological Institute at Chicago (TTIC) and as a visiting professor at ETH Zurich. Her research spans machine learning, computer vision, robotics, and AI with a strong focus on autonomous driving and 3D perception. Education: Bachelor's degree, Universidad Pública de Navarra, 2000 Ph.D., Computer Science, École Polytechnique Fédérale de Lausanne (EPFL), 2006 Postdoctoral studies, MIT and UC Berkeley Raquel Urtasun's research focuses on developing AI systems for self-driving cars, emphasizing efficient perception using minimal sensors. Her work includes 3D scene understanding, stereo vision, optical flow, semantic segmentation, and object detection. She has developed the KITTI benchmark suite, widely used in autonomous driving research. Her lab is an NVIDIA NVAIL lab, reflecting its leadership in AI innovation. Her recent publications show a consistent trend in deep learning for visual perception, particularly in stereo matching, optical flow, 3D object detection, and semantic segmentation. These works integrate deep neural networks with structured models like CRFs and MRFs, pushing the boundaries of accuracy and efficiency in scene understanding for autonomous systems. Scientific Awards: NSERC E.W.R. Steacie Fellowship NVIDIA Pioneers of AI Award Google Faculty Research Awards (multiple) Amazon Faculty Research Award Connaught New Researcher Award Fallona Family Research Award Best Paper Runner Up at CVPR 2013 and 2017 UPNA Alumni Award Chatelaine 2018 Woman of the Year Adweek 2018 Toronto's Top Influencers Urtasun has advised numerous PhD and Master’s students, many of whom now hold faculty or research scientist positions at institutions like UIUC, NYU, UBC, MIT, and companies including Google, Amazon, NVIDIA, and Apple. She has secured significant research grants from NSERC, Google, Amazon, and NVIDIA. Her leadership extends to organizing workshops and serving as Area Chair and Program Chair at top conferences like CVPR, ICML, and NeurIPS. Labs and Teams: She leads a research group at the University of Toronto focused on AI for autonomous systems. Her team has been recognized as an NVIDIA NVAIL lab, and she continues to mentor students and postdocs working on cutting-edge problems in robotics and machine learning, both at UofT and through her company Waabi.