جست‌وجوی استاد و پژوهشگر

Huazhe Xuمشاهده پروفایل

استادیار

• Embodied AI
• Reinforcement Learning
• Robotics
• +۲ مورد دیگر

Huazhe Xu is a Tenure-Track Assistant Professor at the Institute for Interdisciplinary Information Sciences (IIIS), Tsinghua University, where he leads the Tsinghua Embodied AI Lab (TEA Lab) . His research focuses on Embodied AI with applications in Robotics , Reinforcement Learning , and Computer Vision/Tactile Sensing . Education: Ph.D. in Berkeley AI Research (BAIR) under Trevor Darrell, postdoctoral work at Stanford Vision and Learning Lab with Jiajun Wu, and B.S. in Electrical Engineering with minor in Management at Tsinghua University. Research Trends: His work emphasizes world dynamics modeling, human priors for policy learning, sample-efficient algorithms, generalization to unseen scenarios, and complex real-robot applications using deep learning and reinforcement learning . Scientific Awards: Best Student Paper Finalist at RSS'25 Best Paper at ICRA'25 Beyond Pick and Place Workshop Best Long Paper at CVPR'25 Syn4CV Workshop Yunfan 'Brilliant Star' Award, World Artificial Intelligence Conference 2024 Best System Paper at CoRL'23 Outstanding Paper in LangRob Workshop at CoRL'23 Lab Leadership: TEA Lab develops robots and embodied intelligence systems, with active hiring for postdocs, PhD students, and interns in Beijing/Shanghai.

Danfei Xuمشاهده پروفایل

استادیار

• Robotics
• Machine Learning
• Robot Learning
• +۳ مورد دیگر

Danfei Xu is an Assistant Professor at the School of Interactive Computing, College of Computing, Georgia Institute of Technology, and a part-time Research Scientist at NVIDIA AI. He leads the Robot Learning and Reasoning Lab (RL2), focusing on developing adaptable robot intelligence through machine learning approaches. His research spans robot learning from human data, long-horizon reasoning with generative models, and full-stack robot learning systems. Education: Ph.D. in Computer Science, Stanford University (2015-2021) B.S. from Columbia University (SEAS'15) Research interests center on creating robots that learn from human demonstrations using wearable devices, developing compositional generative models for long-horizon planning, and building open-source robotic systems. His work integrates neuro-symbolic methods with deep learning to enable flexible task execution in diverse environments like homes, factories, and healthcare settings. Publications demonstrate strong focus on imitation learning (38%), generative models (25%), and robotic systems development (20%), with applications spanning manipulation (42%), planning (33%), and human-robot interaction (17%). Key trends include diffusion models for planning, neural fields for representation, and multi-task learning frameworks. Awards: NSF CAREER Award (2025) IEEE RA-L Best Paper Honorable Mention (2023) ICRA Best Conference Paper (2024) CoRL Best Paper Finalist (2023) CoRL Best Systems Paper Finalist (2023) Leads RL2 lab with 21 members (11 PhD, 7 MS, 3 undergraduates). Secured research funding from NSF (CAREER, generative models), Meta (human data research), Autodesk (manipulation), and Samsung (home robots). Lab maintains multiple robotic platforms including Unitree G1, Franka arms, and custom EVE system.

Sanja Dogramadziمشاهده پروفایل

استاد

• Medical Robotics
• Human-Robot Interaction
• Tactile Sensing
• +۳ مورد دیگر

Professor Sanja Dogramadzi is a faculty member at the School of Electrical and Electronic Engineering, University of Sheffield. Her research focuses on medical robotics, particularly in robot-assisted surgery, tactile sensing, and human-robot interaction for rehabilitation applications. Research Themes: Surgical robotics, wearable tactile devices, image-guided systems, and adaptive control mechanisms for minimally invasive procedures. Collaborations: Work with institutions like the Hamlyn Symposium on Medical Robotics and researchers including Caleb-Solly, Jevtić, and Torras. Publications: 15 recent works span AI-driven surgical systems, tactile motion intent recognition, and bioinspired robotic designs. Teaching: Leads robotics education in courses like ACS329 Robotics.

• Autonomous Systems
• Biologically Inspired Robotics
• Machine Vision
• +۶ مورد دیگر

Russell Brinkworth is an Associate Professor in Autonomous Systems at Flinders University's College of Science and Engineering. With over a decade of postdoctoral research, teaching and administration experience, he focuses on bringing robotics out of the lab and into real-world applications. His work bridges the gap between neuroscience, medicine, engineering, biochemistry and physiology through Systems Biology approaches. His educational background includes: Graduate Certificate in Education from the University of Adelaide (2008) PhD in Physiology from the University of Adelaide (2004) Bachelor of Engineering (Biomedical) with First Class Honours from Flinders University (2000) Bachelor of Science from Flinders University (1999) Professor Brinkworth's research interests span multiple disciplines with a focus on creating adaptable robotic systems that can function in diverse environments without requiring environmental modifications. His work in biologically inspired robotics draws heavily from neuroscience to develop more flexible and accessible robotic platforms. He has developed expertise in autonomous systems, machine vision, signal processing, and control systems, with applications ranging from defense engineering to wildlife conservation. His publication record shows significant contributions across computer vision, robotics, and biologically inspired algorithms, with recent work focusing on DNA profiling techniques, koala detection systems, underwater vehicle operations, and smart PCR thermocyclers. His research demonstrates a consistent pattern of applying biological principles to solve engineering challenges across diverse domains. Professor Brinkworth has received recognition through an h-index of 17 with 1058 citations, indicating substantial impact in his fields of research. His work has been picked up by multiple news outlets and has attracted attention from researchers worldwide. As an educator, he teaches advanced courses including: ENGR7711 Advanced Control Systems ENGR9721 Control Systems GE ENGR7712 Autonomous Systems ENGR3711 Control Systems He serves as a media expert in Defence Engineering, Neuroscience, Autonomous Systems, Biologically Inspired Robotics, Machine Vision, and Signal Processing, providing commentary on technological developments in these areas.

Ahmet Can Ertenمشاهده پروفایل

استادیار

• Biomedical Engineering
• MEMS and Microsystem Technologies
• Optics
• +۱ مورد دیگر

Assistant Professor Ahmet Can Erten is affiliated with Istanbul Technical University's Department of Electronics and Communication Engineering. His research focuses on biomedical engineering, MEMS, microsystem technologies, optics, and photonics, with applications in microfluidic devices and capsule endoscopy. PhD - University of California MS - University of California, San Diego BS - University of California, San Diego Research interests include: Biomedical microdevices Magnetic actuation systems Microfluidic sensors Optofluidic components Viscosity measurement technologies 3D cell culture platforms Recent publications show trends in magnetic actuation for endoscopic devices, optical sensing in microfluidics, and computational approaches to fluid dynamics. His work spans electrochemical biosensors, microvalve control systems, and machine learning applications in healthcare diagnostics. Member of IEEE (2000-present) Member of Tau Beta Pi (2000-present) Member of Kappa Nu (2002-present) ACS Member (2011-present) He has advised 9 thesis students focusing on topics like: Micropillar waveguide viscosity sensors Magnetic actuator design FFT-based fluid analysis Polydimethylsiloxane characterization Microstructure movement detection Magnetically actuated cell sorters Current projects include a microfluidics-based refreshable Braille display and various TUBITAK/BAP-funded studies on biomedical microsystems.

• Neuroinformatics
• Cognitive Robotics
• Tactile Sensing
• +۴ مورد دیگر

Prof. Dr. Helge Ritter is a distinguished Professor at the University of Bielefeld, holding multiple key positions across several departments and research centers. He is primarily affiliated with the Faculty of Engineering as part of the Neuroinformatics Group, and also serves as a CITEC Coordinator at the Center for Cognitive Interaction Technology. His work spans the Faculty of Psychology and Sport Science in the Department of Psychology (Unit 01 - Neurocognitive Psychology), and he contributes to the Joint Research Center on Cooperative and Cognition-enabled AI. His academic journey has positioned him at the forefront of interdisciplinary research that bridges engineering, cognitive science, and robotics. As a member of the Habilitation Committee and serving as Personal Deputy for Prof. Dr.-Ing. Ulrich Rückert on the Examination Boards for Biomechatronics (Master), he plays a significant role in academic governance and curriculum development. Research Interests Prof. Ritter's research spans the cutting-edge intersection of neuroinformatics, robotics, and artificial intelligence. His work focuses on cognitive robotics , tactile sensing systems , and human-robot interaction , with particular emphasis on how machines can perceive and interact with the physical world through touch and movement. His investigations into modular neural architectures and biologically inspired learning systems have significant implications for both theoretical neuroscience and practical robotics applications. His current research trajectory demonstrates a strong focus on transfer learning between simulation and reality , multi-fingered manipulation , and adaptive kinematic modeling . These efforts contribute to the broader Socio-Technical World research area at Bielefeld University, which 'researches capabilities and mechanisms that enable agents such as humans, robots and AI to act, communicate and learn in complex environments.' Academic Contributions Coordinator at the Center for Cognitive Interaction Technology (CITEC) Member of the Habilitation Committee in the Faculty of Engineering Personal Deputy for Examination Boards in Biomechatronics (Master) Contributor to the Joint Research Center on Cooperative and Cognition-enabled AI Prof. Ritter's work exemplifies Bielefeld University's commitment to 'Transcending Boundaries' between disciplines, people, and science and society. His research bridges theoretical neuroscience with practical robotics applications, creating innovative solutions for human-robot collaboration and cognitive systems.

Mike Y Chenمشاهده پروفایل

استاد

• Human-Computer Interaction
• Virtual Reality
• Augmented Reality
• +۵ مورد دیگر

Mike Y Chen is a full Professor in the Department of Computer Science and Information Engineering at National Taiwan University (NTU), where he leads the Mobile Human-Computer Interface Laboratory (NTU HCI Lab). He holds a PhD in Computer Science from UC Berkeley and a Certificate in Management of Technology from the Haas School of Business, UC Berkeley. His research sits at the intersection of human-computer interaction, AI, design, psychology, and mobile/wearable/VR/AR systems . Education PhD in Computer Science, UC Berkeley Certificate in Management of Technology, Haas School of Business, UC Berkeley Research Interests Professor Chen’s group explores future user interfaces that seamlessly blend digital and physical experiences. Core themes include: Advanced haptic feedback systems for VR/AR, using air jets, EMS, and novel actuators to create realistic sensations. Mobile and wearable interaction , including smart glasses, on-body sensors, and handheld devices. AI-driven design tools that leverage generative models to support creative workflows. Accessibility & ergonomics , crafting personalized and inclusive interactions. Publication Trends His recent work (2020-2025) focuses on haptics in VR/AR and AI-assisted design . Notable contributions include award-winning papers on air-propelled force feedback (AirRacket) , EMS-based haptics (Paired-EMS) , and generative-AI interior design tools (RoomDreaming) . The lab consistently publishes at top venues—ACM CHI, UIST, DIS, SIGGRAPH—demonstrating leadership in both technical innovation and user experience. Scientific Awards & Honors ACM CHI Best Paper Awards (2020, 2022) ACM CHI Honorable Mention Awards (2020, 2021, 2023) ACM DIS 2024 Best Paper Award UIST Best Talk Award 科技部吳大猷研究獎 Outstanding Young Researcher Award Google & Microsoft rank NTU HCI Lab in top 25 of 2000 NTU research groups Academic Service & Outreach Professor Chen has served as Journals Chair for CHI 2025, Sub-committee Chair for CHI 2020 & 2021, and Program Co-chair for MobileHCI 2019. He actively mentors students through the university research+culture summer internship program , guiding them toward top graduate schools and Silicon Valley careers. Labs & Teams He directs the Mobile Human-Computer Interface Laboratory (R336, NTU), an interdisciplinary group that integrates design thinking, AI, psychology, and hardware-software co-design to create next-generation interactive systems.

Lorenzo Rosascoمشاهده پروفایل

استاد

• Machine Learning
• Artificial Intelligence
• Robotics
• +۵ مورد دیگر

Lorenzo Rosasco is a Full Professor at the Department of Computer Science, Bioengineering, Robotics and Systems Engineering (DIBRIS) at the University of Genoa. He holds roles including University contact for the thematic area "Artificial Intelligence" and membership on the Department Board. His research focuses on machine learning theory, kernel methods, optimization, robotics, and their applications in control systems, domain adaptation, and interdisciplinary fields like biomedical engineering. His educational background includes advanced expertise in mathematical foundations of machine learning, though specific academic credentials are not detailed here. Teaching responsibilities include courses such as MACHINE LEARNING, SEQUENTIAL PREDICTION AND REINFORCEMENT LEARNING, and INFORMATION THEORY AND INFERENCE at both undergraduate and graduate levels. Research interests revolve around developing efficient algorithms for large-scale machine learning, including iterative regularization, transfer learning, and control systems using Koopman operator theory. Notable contributions include work on fast kernel methods, optimization in neural networks, and applications in robotics for tasks like humanoid locomotion and tactile sensing. Recent publications explore topics such as double descent phenomena, sim-to-real transfer learning, and adaptive control strategies. His work bridges theoretical insights with practical applications, emphasizing computational efficiency and interdisciplinary impact.

• Computer Vision
• Generative Modeling
• Multimodal Foundation Models
• +۴ مورد دیگر

Jiankang Deng is a Lecturer in the Department of Computing at Imperial College London, within the Faculty of Engineering. His research focuses on multi-modality foundation models, generative modeling of physical entities, and computer vision applications. He leads projects such as InsightFace.ai for facial analysis and synthesis. Previously, he earned his PhD (2020) from Imperial College under Prof. Stefanos Zafeiriou, focusing on deep face analysis and modeling. Education: PhD in Computing (2016-2020) from Imperial College London. Research interests include photorealistic facial reconstruction, generative adversarial networks, and multimodal learning. His work bridges computer vision with practical technologies for societal impact. Publications reflect expertise in 3D reconstruction, diffusion models, and cross-modal systems. Notable areas include hand motion analysis, face reflectance estimation, and tactile robotics. His work emphasizes scalability and real-world applicability. No awards listed explicitly, but his research contributions are evident through active publications and industry collaborations. Advising and lab work involve the IBUG research group, focusing on facial recognition and generative AI systems. Labs/Teams: Part of the Imaging and Biomedical Engineering Group (IBUG), collaborating on projects like FaceMAE for privacy-preserving recognition and MogFace for advanced face detection systems.

• Neuroscience Nursing
• Biomimetics
• Wound Care
• +۳ مورد دیگر

Andrea Shepherd is a Senior Lecturer and Head of the School of Nursing and Paramedic Science at Ulster University, specializing in neuroscience nursing, biomimetics, and interprofessional education. She works at the Derry~Londonderry campus and contributes to the Institute of Nursing and Health Research. Role: Senior Lecturer, Head of School of Nursing and Paramedic Science Institution: Ulster University Location: Derry~Londonderry campus, Londonderry, United Kingdom Contact: a.shepherd@ulster.ac.uk, +44 28 7167 5197 Her research explores neurological assessment tools, such as the Glasgow Coma Scale, and biomimetic technologies for vital sign monitoring. She investigates brain-computer interfaces for disorders of consciousness and family experiences in critical care. Key trends in her recent publications include advancements in neuroscience nursing, interprofessional education models, wound care innovations, and tactile sensing technologies for clinical diagnostics. Collaborative international research features prominently. Notable Work: International standardization of neurological assessments Technologies: Biomimetic fingertip sensors for pulse and capillary refill time measurement Educational Contributions: COIL initiatives to enhance interprofessional learning She organizes academic events like the Interprofessional Education (IPE) Festival, fostering interdisciplinary collaboration. Her work aligns with UN Sustainable Development Goals in global health and education equity.

Ferat Sahinمشاهده پروفایل

استاد

• Collaborative Robotics
• Human Compliant Robotics Systems
• Deep Learning
• +۸ مورد دیگر

Dr. Ferat Sahin is a Professor and Department Head of Electrical and Microelectronic Engineering at the Kate Gleason College of Engineering, Rochester Institute of Technology (RIT). He directs the Multi Agent Bio-Robotics Laboratory and Century Mold Collaborative Robotics Laboratory. His research focuses on collaborative robotics, machine learning, and system of systems engineering. He has over 140 publications, co-authored two books, and secured over $2 million in research funding. Dr. Sahin is a senior member of IEEE, holding leadership roles such as Deputy Editor-in-Chief of International Journal of Computers and Electrical Engineering and former Secretary of IEEE SMC Society. He received the Outstanding Contribution Award in 2007 and 2015 for his service. Education: Bachelor’s degree from Istanbul Technical University Master’s and Ph.D. from Virginia Polytechnic Institute and State University Research Interests: Dr. Sahin’s work spans collaborative robotics , human-compliant systems , deep learning for biosignals , and fault analysis . His labs develop advanced robotics solutions with applications in manufacturing and healthcare. Recent projects include human comfort index estimation and emotion-aware human-robot collaboration frameworks. Grants & Funding: Key grants include support from MKS ENI Inc. ($29,907–$48,674) and NYSTAR ($60k–$64k) for robotics and materials research. He also secured industry partnerships through RoboCamps and company gifts. Labs & Teams: Directs two robotics labs at RIT, fostering interdisciplinary projects with students and industry. Current initiatives include multi-agent systems and tactile sensing for industrial robots.

Eelke Folmerمشاهده پروفایل

استاد

• Human-Computer Interaction (HCI)
• Virtual Reality
• Accessibility Technology
• +۵ مورد دیگر

Eelke Folmer is a Professor and Chair in the Department of Computer Science & Engineering at the University of Nevada, Reno (UNR), part of the College of Engineering. He leads the HCI Lab, which focuses on human-computer interaction, virtual reality (VR), and accessibility technologies. His research addresses challenges such as VR-induced sickness, spatial navigation, and neurovestibular perception in collaboration with UNR's Neuroscience department. Research interests include virtual locomotion, accessibility for visually impaired users, eye-tracking applications, and sensory substitution systems. His work is supported by grants from the National Science Foundation (NSF), Google, Mozilla Foundation, and UNR. Key projects include developing low-cost VR positional tracking (StereoTrack), studying gender differences in VR experiences, and creating navigation aids for blind users. Notable contributions include the design of accessible exergames for children with visual impairments and the development of Haptic Target Acquisition systems. His lab also explores underwater VR systems for neutral buoyancy training and has published extensively on telepresence, tactile feedback, and non-visual interfaces. Advising highlights include mentoring Nathan in VR locomotion research. Collaborations span interdisciplinary teams in computer science, neuroscience, and engineering. The lab's work emphasizes real-world applications, such as drone-guided navigation for athletes and inclusive gaming interfaces.

Seongkook Heoمشاهده پروفایل

استادیار

• Human-Computer Interaction
• Haptics
• Sensing Technologies
• +۳ مورد دیگر

Seongkook Heo is the Alfred Weaver Career Enhancement Assistant Professor in the Department of Computer Science at the University of Virginia. His primary research focuses on Human-Computer Interaction (HCI), with an emphasis on developing novel sensing techniques, haptic feedback systems, and interactive technologies. He directs the Ultimate User Interface Lab, aiming to bridge physical and digital worlds through advanced interaction methods. He holds a Ph.D. in Computer Science from KAIST (2017), supervised by Prof. Geehyuk Lee. Prior roles include postdoctoral research at the University of Toronto's DGP Lab under Prof. Daniel Wigdor and industry internships at Samsung Advanced Institute of Technology, Microsoft Research, and Autodesk Research. Key research areas include tactile interfaces, gesture recognition, and assistive technologies. His work has been recognized with awards such as the ACM CHI Best Paper Award, ACM MobileCHI Best Paper Award, and the Meta Research Award. He teaches courses on HCI and interactive technologies at UVA. His Ultimate User Interface Lab explores cutting-edge projects like MoiréTag for tangible interactions, Thing2Reality for XR communication, and Take My Hand for visually impaired navigation. Collaborative tools like Openmic and ThingShare enhance remote collaboration through spatial and object-sharing innovations.

Abhinav Guptaمشاهده پروفایل

استاد

• Computer Vision
• Machine Learning
• Artificial Intelligence
• +۵ مورد دیگر

Abhinav Gupta is a Professor at Carnegie Mellon University's Robotics Institute, specializing in Computer Vision, Machine Learning, and Robotics. His research focuses on scene understanding, human-centric vision, and language-vision interactions. He leads projects like NEIL and has developed tactile skins like ReSkin. His work emphasizes self-supervised learning, robot manipulation, and visual learning. Education & Positions: PhD from CMU, postdoc at CMU, former affiliations with UMD and UPenn. Current roles include teaching courses like Visual Learning and Recognition. Research Interests: 3D scene representation, affordances, visual-language links, and robotics applications. His lab explores topics like tactile sensing, robot exploration, and generalizable manipulation through projects such as Track2act and Gen2act. Awards & Recognition: Includes the JK Aggarwal Prize (2020), ONR Young Investigator Award (2018), and Okawa Grant. His work on NEIL earned CNN's Top 10 Ideas of 2013. Students & Collaborations: Advised over 20 PhD/Master's students and postdocs. Notable former advisees include David Fouhey, Xiaolong Wang, and Lerrel Pinto. Collaborations with institutions like Meta AI and UIUC. Key Projects: NEIL (Never Ending Image Learner), Curious Robot, and ReSkin tactile skins. His research bridges theory and practice, with applications in robotics, computer vision, and AI systems.

Mark Cutkoskyمشاهده پروفایل

استاد

• Robotics
• Biomimetics
• Tactile Sensing
• +۵ مورد دیگر

Mark Cutkosky is the Fletcher Jones Professor in the School of Engineering at Stanford University. His research focuses on bioinspired robotics, tactile sensing, and advanced manufacturing. He leads the Biomimetics and Dexterous Manipulation Lab, developing innovative robotic systems for applications in healthcare, space exploration, and industrial automation. Education: PhD in Mechanical Engineering, Carnegie Mellon University (1985) Research Interests: Cutkosky designs robots and sensors inspired by biological systems, such as gecko-inspired adhesives and whisker-like tactile sensors. His work emphasizes practical applications, including MRI-compatible teleoperators for medical procedures, miniature implantable sensors for cardiac monitoring, and robots for Martian cave exploration. He also explores soft robotics, haptic interfaces, and rapid prototyping tools. Key Projects: ReachBot: A compact robot for extreme environments like Martian lava tubes Gecko-inspired adhesives for space and industrial gripping VITALS: Implantable sensor networks for post-surgical cardiac care Grants & Labs: His lab has pioneered tactile sensor networks and bioinspired design frameworks. Current work includes collaborative projects on surgical robotics, biomedical devices, and materials science.