جست‌وجوی استاد و پژوهشگر

Christopher Yee WONGمشاهده پروفایل

استادیار

• Human-Robot Interaction
• Robot Kinematics
• Machine Learning
• +۶ مورد دیگر

Dr. Christopher Yee WONG is an Assistant Professor in the Department of Mechanical, Industrial and Aerospace Engineering at Concordia University, Montreal, Canada. He leads the Living with Assistive and Interactive Robots (LAIR) Lab, focusing on human-robot interaction (HRI), robot kinematics, and multimodal sensing. His research aims to develop safe and intuitive robotic systems for healthcare, retail, and manufacturing environments. He holds a Ph.D. (2017) from the University of Toronto and M.Eng. (2014) and B.Eng. (2011) from McGill University. His education includes advanced robotics training, with a Ph.D. in Robotics from the University of Toronto and a B.Eng./M.Eng. in Mechanical Engineering from McGill University. His work spans physical and social HRI, including robot-to-human grasping, sensor observability analysis, and virtual reality applications. He also focuses on ethics in robotics education and has contributed to K-12 roboethics modules. Dr. Wong’s research projects include robots in retail spaces for visually impaired users, VR environments for HRI studies, and foundational work on sensor observability metrics for robotic mechanisms. His recent publications emphasize practical applications in assistive robotics and ethical considerations in technology deployment. As an educator, he employs evidence-based teaching methods, emphasizing student engagement and problem-solving. He has taught courses at Concordia and McGill, including Dynamics, Automated Manufacturing, and Control Systems, with consistently high student ratings. His teaching philosophy prioritizes guiding students to reconstruct knowledge through active learning.

Tian Chenمشاهده پروفایل

استادیار

• Mechanics
• Computational Design
• Materials Science
• +۳ مورد دیگر

Dr. Tian Chen is the Kamel Salama Endowed Assistant Professor of Mechanical & Aerospace Engineering at the University of Houston, leading the Architected Intelligent Matter (A.I.M.) Laboratory. His research focuses on programmable matter, combining mechanics, computational design, and materials science to create adaptive materials. He holds a Ph.D. from ETH Zurich, an M.S. from Delft University of Technology, and a B.A.Sc. from the University of Toronto. Education: Ph.D., Swiss Federal Institute of Technology in Zurich (ETH Zurich) M.S., Delft University of Technology B.A.Sc., University of Toronto Research Interests: Dr. Chen’s work explores programmable shape transformation of surfaces and mechanical behavior of architected materials. His lab develops materials with digitally controlled functionalities, such as temperature-responsive architectures and self-reconfigurable systems. Applications span aerospace, robotics, and biomedical engineering. Awards & Honors: Haythornthwaite Foundation Research Initiation Grant Swiss National Science Foundation Post-Doc Mobility Fellowship ETH Medal for Outstanding Doctoral Thesis Cum Laude, Delft University of Technology Grants & Advising: His research is funded by NSF, NASA, and the Haythornthwaite Foundation. He advises students in mechanical engineering and collaborates on projects involving 4D printing, metamaterials, and smart structures. Labs & Teams: The A.I.M. Lab at UH focuses on interdisciplinary research in intelligent matter, with ongoing collaborations in computational design and materials science.

Aishwari Talhanمشاهده پروفایل

استاد پژوهشی

• Haptics
• Wearable Technology
• Extended Reality
• +۴ مورد دیگر

Dr. Aishwari Talhan is an Affiliated Faculty member in the Department of Electrical and Computer Engineering at the College of Nanotechnology, Science, and Engineering, University at Albany. With a PhD in Computer Engineering from Kyung Hee University, she serves as a Research Scientist in the Office of the Vice President for Research. Her international experience includes postdoctoral positions at McGill University and Kyung Hee University, along with industry experience as a software developer in Bengaluru. Her research explores the intersection of haptics, wearables, and human-computer interaction, with applications in extended reality (XR), artificial intelligence, rehabilitation engineering, and medical simulation. Key investigations include tactile feedback systems, soft robotics interfaces, and immersive training technologies for medical procedures. Publications demonstrate consistent focus on multisensory interaction design, with recent work emphasizing pneumatic actuation systems, wearable haptic devices, and virtual training environments. Research trends show progressive refinement of soft robotics techniques for tactile augmentation across healthcare and education domains. Professional affiliations include memberships in ACM and IEEE. Education history includes: Post Doctoral Researcher, McGill University Postdoctoral Researcher, Kyung Hee University PhD Computer Engineering, Kyung Hee University ME Embedded Systems, Nagpur University BE Information Technology, Nagpur University

Russell Tedrakeمشاهده پروفایل

استاد

• Robotics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Russell Tedrake is the Toyota Professor at MIT, holding joint appointments in the Departments of Electrical Engineering and Computer Science, Aeronautics and Astronautics, and Mechanical Engineering. He serves as Director of the Center for Robotics at CSAIL and leads MIT's DARPA Robotics Challenge team. Additionally, he is Senior Vice President of Robotics Research at the Toyota Research Institute. Research focuses on merging systems theory with machine learning for robotic manipulation, particularly through non-smooth mechanics and optimization. His work bridges dynamical systems control with AI for autonomous vehicles, industrial machines, and dexterous robotics. Developed Drake toolbox for nonlinear system analysis Innovated PhysicsGen simulation pipeline Created tactile perception systems using proprioceptive sensors His research has produced impactful publications in robotics and machine learning, emphasizing stability guarantees and physical interaction modeling. Awards include multiple MIT teaching honors, NSF CAREER Award, and Microsoft Research New Faculty Fellow. Education: B.S.E. from University of Michigan (1999), Ph.D. from MIT (2004) Labs: Robot Locomotion Group at CSAIL

Pulkit Agrawalمشاهده پروفایل

دانشیار

• Robotics
• Artificial Intelligence
• Machine Learning
• +۳ مورد دیگر

Pulkit Agrawal is an Associate Professor at the Massachusetts Institute of Technology (MIT), holding dual appointments in the departments of Artificial Intelligence and Decision-making (AI+D), Computer Science (CS), and Electrical Engineering (EE) within the School of Engineering. He is a core member of the Embodied Intelligence Community of Research, focusing on advancing intelligent systems that interact with the physical world through robotics, AI, and machine learning. His work emphasizes bridging simulation and real-world applications in robotics, human-robot interaction, and medical technology. Key research areas include reinforcement learning for robotic manipulation, simulation-to-real transfer, and embodied intelligence. Notable projects include developing methods for robust home robot training using real-to-sim-to-real approaches, tactile-driven object retrieval systems, and AI-driven glucose control models for post-surgical care. He also explores ethical AI in healthcare and assistive technologies for cognitive impairment monitoring. Dr. Agrawal’s contributions span robotics hardware design (e.g., DEXOS hand exoskeleton), neuro-inspired algorithms (e.g., grid cell-based map building), and scalable robot learning via crowdsourced environments. His work often integrates interdisciplinary methods from control theory, computer vision, and biomedical engineering. He leads the MIT CSAIL Embodied Intelligence group and collaborates on projects like OpenEQA for embodied question answering and DexHub for large-scale robot data collection. His research has been recognized through promotions within EECS and featured in outlets like MIT News for innovations in home robotics and AI-driven medical solutions. He advises on grants related to intelligent systems and maintains active collaborations across academia and industry.

Rika Antonovaمشاهده پروفایل

دانشیار

• Robotics
• Reinforcement Learning
• Machine Learning
• +۷ مورد دیگر

Dr. Rika Antonova is an Associate Professor at the Department of Computer Science and Technology, University of Cambridge , UK. Her research focuses on robot learning , data-efficient reinforcement learning , and simulation-to-reality transfer . She offers fully funded PhD positions in robot learning, novel robot hardware design, and reinforcement learning (RL) at Cambridge, where she also teaches an RL course. Educational Background: PhD in Robotics from KTH Royal Institute of Technology, Sweden (advisor: Danica Kragic). MSc in Robotics from Carnegie Mellon University (advisor: Emma Brunskill). Research Interests: Antonova's work bridges Bayesian optimization , deformable object manipulation , and multimodal sensor design . Her recent projects include equivariant diffusion policies and GPU-accelerated control frameworks . She has contributed to data-efficient RL algorithms and topological representations for deformable objects . Recent Publications: Antonova's 2024 articles on EquiBot (CoRL) and Runtime Monitoring (CoRL) highlight her focus on generalizable policies and safe AI. Earlier works include DiffCloud (IROS 2022) for real-to-sim rendering and Bayesian Optimization in Variational Latent Spaces (CoRL 2020). Scientific Awards: NSF/CRA Computing Innovation Fellowship (postdoctoral). Research Community Involvement: Antonova serves on the Board of Directors of the Robot Learning Foundation and has been an Associate Editor for ICRA (2024), Chair for CoRL Demos (2024), and reviewer for JMLR, Nature Machine Intelligence, and top robotics conferences.

• Nanotechnology
• Biomedical Engineering
• Drug Delivery Systems
• +۱ مورد دیگر

Professor Ken Tye Yong is Associate Dean (External Engagement) for the Faculty of Engineering and Professor in the School of Biomedical Engineering at the University of Sydney. His research spans nanotechnology, biomedical imaging, drug delivery systems, and biophotonics, with emphasis on nanoparticle-based therapies and diagnostic platforms. He leads initiatives in external engagement through the Warren Centre and oversees research on nanomaterial applications in healthcare. Current projects include neuromorphic imaging cytometry, SERS-based cellular monitoring, and biomimetic tissue scaffolds. Publications demonstrate consistent focus on interdisciplinary approaches combining nanomaterials engineering with clinical applications. Research outputs frequently involve microfluidic systems, targeted drug delivery, and advanced imaging techniques. Recent work emphasizes neuroprotective therapies, wearable biosensors, and mRNA vaccine delivery platforms.

Rebecca Friesenمشاهده پروفایل

استادیار

• Surface Haptic Displays
• Haptic Wearables
• Tactile Perception
• +۲ مورد دیگر

Dr. Rebecca Friesen is Assistant Professor of Mechanical Engineering at Texas A&M, leading research on haptic interfaces for enhanced virtual interactions. Her lab develops surface haptic displays, wearable tactile devices, and refreshable braille systems that replicate complex tactile sensations. Current projects investigate: 1) Friction-modulating touchscreens for realistic texture rendering, 2) Wearable vibrotactile displays for virtual reality, 3) Refreshable pin arrays for tactile graphics, and 4) Medical palpation simulation using haptic feedback. Research combines psychophysical studies with engineering design to create efficient tactile displays leveraging perceptual phenomena.

Ville Kyrkiمشاهده پروفایل

استاد

• Intelligent Robotic Systems
• Computer Vision
• Robotics Manipulation
• +۷ مورد دیگر

Professor Ville Kyrki is a Full Professor at Aalto University's School of Electrical Engineering, leading the Intelligent Robotics research group. His work focuses on intelligent robotic systems, particularly addressing challenges in imperfect knowledge and uncertain sensory data. Key research areas include computer vision, tactile sensing, robotic manipulation, and machine learning applications in robotics. Education details are not explicitly provided in the text, but his academic trajectory includes a progression from Associate Professor (appointed 2012) to Full Professor at Aalto University. Research interests span feature extraction, visual servoing, sensor fusion, and planning under uncertainty. He has pioneered methods for deformable object manipulation, including data-driven grasp synthesis and imitation learning approaches for dynamic tasks like cloth folding. His work integrates reinforcement learning with domain adaptation techniques to bridge simulation-to-real gaps. Awards include the 2022 Best Paper Award and a 2024 nomination for the Best Safety, Security, and Rescue Robotics Paper. His contributions address critical challenges in robotics such as safe human-robot collaboration and autonomous decision-making in dynamic environments. Lab activities center on the Intelligent Robotics group, which develops advanced systems for industrial automation, autonomous navigation, and human-centric robotics. Current research emphasizes scalable solutions for UAV localization, multi-agent coordination, and robust policy learning in uncertain conditions.

• Physics Education
• Didactics of Physics
• Science Teaching and Learning
• +۷ مورد دیگر

Bianca Watzka is a Professor of Physics and Technology Education at RWTH Aachen University, affiliated with the Department of Physics within the Faculty of Mathematics, Computer Science and Natural Sciences. She conducts research and teaching in the didactics of physics, focusing on innovative pedagogical methods and technology integration. Her research interests include: Physics Education and Didactics Context-Based and Phenomenon-Based Learning Cognitive Load Theory in Instruction Educational Technology and Multimedia Learning Teacher Education and Diagnostic Competence Use of Sensors and Digital Tools (Arduino, H5P) in Science Classrooms Eye-Tracking in Learning Environments Her recent publications (2023–2025) reflect a strong focus on enhancing physics instruction through multimedia cues, cognitive load optimization, interactive tasks, context-rich problems, and teacher training. She investigates how auditory and visual supports, VR annotations, force diagrams, and real-world contexts like wind and thermodynamics improve learning outcomes. Her work increasingly integrates technology for formative assessment and reflective teaching. Scientific contributions include: Development of context-oriented physics modules Application of eye-tracking in educational diagnostics Promotion of inquiry-based methods like the Mystery method Integration of Cornell Notes and H5P in teacher education Use of authentic contexts such as CO2 sensors, LEDs, and bionics in teaching She advises pre-service physics teachers and contributes to improving teaching quality through student feedback and structured learning tools. Her work bridges theoretical research with practical classroom applications, particularly in secondary and higher education settings. While no formal lab or team is mentioned, her research implies collaboration in educational technology and teacher training projects.

Alexander Achbergerمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Virtual Reality
• Haptics
• +۳ مورد دیگر

Dr. Alexander Achberger is a Research Associate at the Visualization Institute of the University of Stuttgart (VISUS) , affiliated with the Sedlmair Working Group . His research focuses on Human-Computer Interaction , Virtual Reality , and Haptics , particularly in Automotive Engineering contexts. He has published extensively on haptic feedback devices and immersive visualization tools since 2018. Current position: Research Associate at VISUS Affiliation: Sedlmair Working Group Location: Allmandring 19, Stuttgart, Germany (Room: 01.031) His work explores force feedback systems like PropellerHand , STROE , and STRIVE for automotive VR applications. He also investigates sitting posture recognition and motion guidance memorability in extended reality environments. Recent publications examine multi-type haptic feedback and upper limb representations in VR.

Timo Klein-Soetebierمشاهده پروفایل

پژوهشگر

• Table Tennis
• Motor Control
• Sports Cognition
• +۵ مورد دیگر

Timo Klein-Soetebier is a researcher at the Institute of Exercise Training and Sport Informatics at the German Sport University Cologne, specializing in Cognition in Team Sports. With 66 publications and 11 research projects to his name, he focuses primarily on table tennis, motor control, and perception training in sports contexts. His research interests span across several key areas including table tennis technique analysis, motor learning, sports cognition, and perception training. Klein-Soetebier has made significant contributions to understanding gender differences in table tennis techniques, perception training methods, and the application of table tennis in therapeutic contexts such as Parkinson's disease rehabilitation. The 15 most recent publications reveal a consistent focus on practical applications of sports science, particularly in table tennis pedagogy, sports informatics, and motor learning principles. His work bridges theoretical sports science with practical applications in training, education, and health contexts, demonstrating a strong commitment to translating research into real-world impact. Klein-Soetebier actively collaborates with colleagues across multiple departments at the German Sport University Cologne, particularly with researchers in sports informatics, cognition, and sports games research. His work has generated significant media attention, particularly regarding the therapeutic applications of table tennis for Parkinson's disease patients. His current research projects include investigations into learning curves in table tennis skill acquisition, XR-based training methods in golf, and perception training in table tennis, demonstrating both depth in his primary area of expertise and breadth across different sports contexts. He maintains an active presence in both academic and public spheres, with 8 media appearances discussing the benefits of table tennis for health and performance, particularly highlighting its applications for neurological rehabilitation.

Xinli Duمشاهده پروفایل

دانشیار

• Robotic Surgery
• Biomedical Engineering
• Control Systems
• +۴ مورد دیگر

Dr. Xinli Du is a Reader (equivalent to Associate Professor) in Robotics & Autonomous Systems at Brunel University London, within the Department of Mechanical and Aerospace Engineering in the College of Engineering, Design and Physical Sciences. He joined the Brunel Institute for Bioengineering as a Research Lecturer in August 2010, bringing expertise from his PhD at Loughborough University (2008) and a Research Associate position at Aston University. His educational background includes a PhD in Control Systems from Loughborough University (2008). Prior to Brunel, he worked as a Research Associate at Aston University. Dr. Du's research centers on biomedical engineering with a focus on robotic surgery, particularly for cochlear implantation and prosthetics. He has developed innovative smart surgical tools including a robotic micro-drill for cochleostomy and tactile sensing systems for stroke rehabilitation. His work integrates advanced control systems, robotics, and multi-sensor technologies to enhance surgical precision and patient rehabilitation outcomes. Analysis of his recent publications (2021-2025) shows a dominant focus on robotic cochlear implant surgery, featuring real-time impedance-based electrode array tracking, machine learning for trajectory correction, and 6-DOF parallel manipulators for atraumatic insertion. Significant parallel work in prosthetics utilizes 3D motion capture and smartphone photogrammetry for socket fitting assessment. Additional contributions span PEM fuel cell control and optical shape sensing for continuum robotics in minimally invasive surgery. Dr. Du has not been documented as receiving specific scientific awards in the provided materials. He supervises PhD students in Robotic Surgery and Control System Design. His research is supported by major grants from The Royal National Institute for Deaf People (2024-2027), The Royal Society (2024-2026), EPSRC (2023-2025), Innovate UK (2021-2023), and magAssist inc. (2020-2023). Current projects include innovative cochlear implant placement techniques, smart myocardial infarction detection devices, and hybrid mock circulatory systems for cardiac research. Dr. Du is an active member of the Brunel Institute for Bioengineering (BIB) and the Institute of Energy Futures and Health Sciences (IEHS). He collaborates extensively with researchers including Dr. Nikolaos Boulgouris, Dr. Amir Mohagheghi, and Dr. Yohan Noh on surgical robotics and biomedical sensing projects, contributing to Brunel's leadership in medical technology innovation.

• Drone Control Systems
• Reinforcement Learning
• Digital Twin Technology
• +۳ مورد دیگر

Robert McMurray is a Lecturer at the School of Engineering, Ulster University, with active research contributions in drone control systems, reinforcement learning, and engineering education. He is based at the Belfast campus and serves as a key member of the Engineering Research group. Recent research focuses on applying digital twin technology and AI-driven control strategies to unmanned aerial vehicles (UAVs), particularly the MADNI drone platform. His work explores hybrid control systems for adverse conditions, obstacle avoidance algorithms, and tactile force prediction models using deep learning. Key Research Areas: Drone autonomy, materials testing, and pedagogical best practices 2024-2025 Trends: Integration of reinforcement learning with fault detection in UAVs, digital twin simulations Contact: rj.mcmurray@ulster.ac.uk

• Robotics
• Artificial Intelligence
• Machine Learning
• +۴ مورد دیگر

Prof. Dr. Berthold Bäuml serves as a full Professor at the Technical University of Munich (TUM) within the TUM School of Computation, Information and Technology, holding the Chair for Learning AI for Dextrous Robots. His research bridges artificial intelligence and robotics to develop advanced manipulation capabilities in humanoid systems, with particular emphasis on tactile sensing and learning-based control architectures. His core research interests span Robotics, Artificial Intelligence, Machine Learning, Dextrous Manipulation, Tactile Sensing, and Reinforcement Learning. Bäuml investigates how robots can autonomously learn complex manipulation skills through tactile feedback, focusing on in-hand manipulation, grasping of unknown objects, and sim-to-real transfer for multi-fingered hands. His work integrates state estimation with reinforcement learning to achieve robust performance in unstructured environments. Analysis of his 2022-2025 publications reveals a concentrated research trajectory in tactile dexterous manipulation, characterized by modular reinforcement learning architectures, shape-conditioned agents, and torque prediction systems. Key trends include the development of time-optimal controllers, self-contained calibration methods, and collision-aware motion planning, all leveraging deep learning for real-time performance in humanoid platforms like Agile Justin.