جستجوی استاد راهنمای دانشگاهی

Stefanie Mueller is the TIBCO Career Development Associate Professor at MIT's Electrical Engineering and Computer Science Department, with joint affiliation in Mechanical Engineering. She leads the HCI Engineering Group at the Computer Science and Artificial Intelligence Laboratory (CSAIL), focusing on advancing fabrication techniques through hardware/software innovations that enable novel object interactions. Develops computational fabrication methods combining photochromic dyes, lenticular lenses, birefringent materials, and optical illusions Co-chaired ACM CHI 2023 and ACM UIST 2020 program committees Recipients of 9 MIT EECS Best Undergraduate Researcher Awards among mentees Her research spans four key directions: Appearance-changing Objects: Photo-Chromeleon (ACM UIST 2019), Lenticular Objects (ACM UIST 2021), and Polagons (ACM CHI 2023) demonstrate reprogrammable surfaces through advanced materials and optical engineering. Tracking Systems: InfraredTags (ACM CHI 2022) and G-ID (ACM CHI 2020) enable passive object tracking via infrared markers and slicing artifacts. Embedded Sensing: MechSense (ACM CHI 2023) and Sprayable User Interfaces (ACM CHI 2020) integrate sensing capabilities into complex geometries. Curved Surface Prototyping: FlexBoard (ACM CHI 2023) and CurveBoard (ACM CHI 2020) develop specialized tools for non-planar electronics. Her recent publications focus on functionality segmentation (UIST 2023), fluorescent markers (UIST 2023), and machine-knitted haptics (UIST 2023). These works combine machine learning, material science, and interactive design principles to push fabrication boundaries. Scientific recognition includes: 2022 MIT Technology Review Innovators Under 35 2020 Microsoft Research Faculty Fellowship 2020 Alfred P. Sloan Research Fellowship 2019 ACM UIST Best Paper Award 2019 NSF CAREER Award 2018 MIT EECS Outstanding Educator Award 2017 Forbes 30 Under 30 in Science Mentoring 9 PhD students and over 20 master's students, her lab has produced 20+ publications at top HCI conferences. She redesigned MIT's 6.810 Engineering Interactive Technologies course during the pandemic, maintaining hands-on learning through home electronics kits and Slack-based collaboration.

• Human-Computer Interaction
• Computational Fabrication
• 3D Printing
• +۷ مورد دیگر

Prof. Dr.-Ing. Rüdiger Daub serves as Professor and Chair of Production Engineering and Energy Storage Systems at the Technical University of Munich (TUM), operating within the Department of Mechanical Engineering. His leadership encompasses research direction, academic supervision, and strategic development of battery production technologies at TUM's Garching campus (Boltzmannstr. 15), with active industry collaborations driving innovation in sustainable manufacturing. Daub's research program pioneers advanced production methodologies for lithium-ion and solid-state batteries, focusing on electrode manufacturing, electrolyte filling, and cell assembly processes. His work investigates critical parameter interdependencies affecting battery safety and performance, developing inline monitoring systems and digital twin technologies for real-time process optimization. Key contributions include moisture control in electrode production, electrochemo-mechanical characterization of solid-state systems, and robotics solutions for deformable object assembly, all integrated with machine learning for quality assurance in industrial settings. Analysis of his 2023-2025 publications reveals a dominant research trajectory toward solving production bottlenecks in next-generation energy storage. The work demonstrates increasing integration of computational modeling with empirical validation, particularly in solid-state battery manufacturing and high-voltage electrolyte systems. A notable trend is the cross-pollination of robotics, computer vision, and uncertainty quantification techniques to address complex assembly challenges and distribution shifts in quality monitoring, reflecting industry's urgent need for adaptable, data-driven production systems. Leading TUM's specialized laboratories for battery cell production, Daub's team maintains comprehensive facilities for electrode calendering, electrolyte filling, and cell assembly with integrated tracking and tracing capabilities. The research infrastructure supports collaborative projects with automotive OEMs and battery manufacturers to develop scalable production processes, emphasizing environmental sustainability through water-based electrode production and footprint optimization. Current initiatives focus on digital factory modeling and prelithiation technologies for next-generation battery systems.

• Lithium-Ion Battery Production
• Energy Storage Systems
• Production Engineering
• +۳ مورد دیگر

Georg Martius is a Full Professor in the Department of Computer Science at the University of Tübingen's Faculty of Science and a Max Planck Research Group Leader at the MPI for Intelligent Systems. Since April 2023, he has been a core member of the DFG-funded Cluster of Excellence 'Machine Learning: New Perspectives for Science,' which received extended funding through 2032 for its mission to integrate machine learning into fundamental scientific discovery processes. His academic foundation includes a PhD from the University of Göttingen and Bernstein Center for Computational Neuroscience (2005), a Diploma in Computer Science from the University of Leipzig (2003), and a visiting research period at the University of Edinburgh's Division of Informatics. Postdoctoral positions followed at the Max Planck Institutes for Dynamics and Self-Organization (Göttingen, 2009), Mathematics in the Sciences (Leipzig, 2010), and IST Austria (2015). Professor Martius's research pioneers the intersection of reinforcement learning, robotics, and tactile sensing, with emphasis on developing autonomous systems capable of natural locomotion, dexterous manipulation, and physical-world understanding. His work bridges theoretical machine learning with practical hardware applications, particularly in creating differentiable simulators, superresolution tactile sensors, and biologically plausible learning frameworks for robotic control. Analysis of his 2024-2025 publications reveals dominant trends in offline reinforcement learning (especially goal-conditioned and diversity-maximization techniques), object-centric representation learning for video understanding, and tactile sensing innovations. A strong thread connects foundation models to world model construction, while his work on differentiable physics engines enables precise collision handling and contact dynamics for real-world robotic control. His leadership roles include directing the Distributed Intelligence research team at Tübingen and contributing to major collaborative initiatives like the Real Robot Challenge and Myochallenge 2022. The Cluster of Excellence appointment represents recognition of his contributions to transforming scientific methodology through machine learning, particularly in automating hypothesis generation and experimental design. Current projects focus on integrating large-scale machine learning with embodied intelligence, advancing tactile perception systems like the Minsight vision-based sensor, and developing neuroplasticity-inspired approaches for robust out-of-distribution detection. His work directly impacts fields requiring physical interaction intelligence, from autonomous navigation to medical robotics, with emphasis on sample-efficient learning from limited real-world data.

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

Yi-Chi Liao is a postdoc researcher at ETH Zürich under the SIP Lab, funded by the ETH Zürich Postdoc Fellowship Programme. He holds a PhD from Aalto University (supervised by Prof. Antti Oulasvirta) and Master's/Bachelor's degrees from National Taiwan University. His research focuses on computational interaction, human-in-the-loop optimization, and biomechanical simulation. He has contributed to over 14 top-tier publications in venues like CHI, UIST, and TiiS. Education: PhD in Computer Science, Aalto University (Finland) Master's in Computer Science, National Taiwan University Bachelor's in Computer Science, National Taiwan University Research Interests: Advances in HILO frameworks for adaptive systems, human-AI co-design, and biomechanical motion simulation. His work integrates reinforcement learning, Bayesian optimization, and computational modeling to enhance interactive systems. Publications: Over 14 papers in top HCI venues, emphasizing optimization techniques, tactile interfaces, and 3D interaction. Recent work includes meta-Bayesian optimization for wrist-based interactions and real-time target inference via biomechanical simulation. Awards: CHI 2022 Honorable Mention, multiple outstanding review recognitions, and the ETH Postdoc Fellowship. He serves on program committees for CHI, UIST, and TEI. Teaching: Delivered lectures on Bayesian statistics, deep learning, and computational design at Aalto and NTU. Served as a teaching assistant for HCI and computer architecture courses. Labs: Active in the Human-Computer Interaction Lab (Saarland University), SIP Lab (ETH Zürich), and collaborations with Meta Reality Labs.

• Human-Computer Interaction
• Human-in-the-Loop Optimization
• Reinforcement Learning
• +۴ مورد دیگر

Dr. Uwe Grünefeld is a Visiting Professor at the Faculty of Computer Science , Institute for Computer Science and Business Information Systems (ICB) of the University of Duisburg-Essen. He has been actively contributing to Human-Computer Interaction research through multiple publications in 2025-2022 focusing on Virtual Reality , Augmented Reality , and Robotics . Research Interests span across immersive technology applications for health behavior change (situated artifacts, weight visualization mirrors), haptic feedback systems (EMS for weight perception, vibrotactile directional cues), and behavioral biometrics (hand tracking identification, gaze-based user recognition). His work addresses cross-reality system design , collaborative robotics , and human-in-the-loop simulation methodologies . Key Publications demonstrate significant contributions to VR/AR user engagement, with particular focus on Physical activity promotion through situated artifacts Advanced haptic feedback techniques for immersive environments Behavioral biometric identification systems Robot motion intent communication Cross-reality transition visualization His research often employs mixed-method approaches combining technical implementations with user studies involving quantitative and qualitative data collection.

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

Lung-Pan Cheng is an Associate Professor in the Department of Computer Science and Information Engineering at National Taiwan University. His research focuses on creating innovative interfaces that bridge physical and virtual realities, with particular emphasis on virtual reality systems, haptic feedback mechanisms, and perceptual illusions. Dr. Cheng's work explores how to create more immersive and believable virtual experiences through: Novel haptic feedback systems that simulate physical interactions in virtual environments Real walking techniques that overcome physical space limitations in VR Perceptual illusions that enhance the sense of presence in virtual worlds Human actuation approaches that leverage people as part of the VR infrastructure Optical illusions applied to digital media and gaming experiences Advanced fabrication techniques for interactive physical objects His recent publications (2022-2024) demonstrate a continued trajectory of innovation in VR interaction techniques, with work focusing on directional force feedback, infinite vertical navigation, and the integration of optical illusions into virtual experiences. Dr. Cheng's research consistently combines hardware innovation with perceptual psychology to create compelling user experiences that push the boundaries of virtual environments. Dr. Cheng has received notable recognition for his work: Best Paper Award at CHI 2022 for 'AirRacket: Perceptual Design of Ungrounded, Directional Force Feedback to Improve Virtual Racket Sports Experiences' SIC People's Choice Award at UIST 2022 for 'Garnish into Thin Air' His research has been featured in media outlets including MIT News and New Scientist, indicating broader impact beyond academic circles. Dr. Cheng maintains active collaborations with researchers worldwide, as evidenced by his international co-authorship patterns across multiple disciplines including computer science, psychology, and engineering.

• Virtual Reality
• Human-Computer Interaction
• Haptics
• +۷ مورد دیگر

Yasutoshi Makino is a researcher specializing in ultrasound-based haptics, tactile feedback systems, and human-computer interaction. He has collaborated extensively with Hiroyuki Shinoda and other colleagues, focusing on mid-air haptic displays, noncontact object manipulation, and sensory reproduction. Research Interests Makino's work explores the intersection of acoustics, neuroscience, and engineering to create immersive tactile experiences without physical contact. His innovations include ultrasound-driven actuation mechanisms, thermal sensation rendering, and real-time human motion prediction for robotic systems. Recent Publications The 15 most recent articles highlight advancements in airborne ultrasound tactile displays, texture synthesis via GANs, and applications in guide dog training analysis, virtual reality, and interactive robotics. Key themes include dynamic pressure control , multi-stimulus integration , and low-latency systems . Collaborations Co-authored with Masahiro Fujiwara (43 papers) Collaborated with Hiroyuki Shinoda (145 papers) Worked with Shun Suzuki, Takaaki Kamigaki, and Ryoya Onishi on thermal and mechanical haptic feedback systems.

• Haptics
• Human-Computer Interaction
• Acoustic Engineering
• +۳ مورد دیگر

Prof. Rolf Findeisen is a Professor in the Department of Control and Cyber-Physical Systems (CCPS) at Technische Universität Darmstadt. His work focuses on advancing control theory and its applications in cyber-physical systems, autonomous systems, and energy storage systems. Key areas include model predictive control (MPC), battery management systems, machine learning integration into control frameworks, and optimization of crystallization processes. He leads research on safety-critical systems, data-driven control methods, and interdisciplinary applications in robotics and biotechnology. His research spans theoretical advancements in MPC stability, stochastic control, and Gaussian process modeling, alongside practical implementations in autonomous vehicles, lithium-ion battery systems, and bioprocess optimization. Notable contributions include frameworks like HILO-MPC for integrating machine learning with control systems, and methodologies for safe exploration in autonomous navigation. Prof. Findeisen's publications emphasize energy-efficient trajectory planning, fault detection in battery systems, and real-time optimization of manufacturing processes. His work bridges academic theory with industrial applications, addressing challenges in scalability, safety, and computational efficiency. His lab collaborates on national projects like IN-Fly-Tec and INFLIGHT, focusing on innovative flight control systems and sensor technologies. Current research trends include hybrid intelligent optimization, cybergenetic control of microbial systems, and safe reinforcement learning for control systems.

• Model Predictive Control (MPC)
• Cyber-Physical Systems
• Battery Systems Optimization
• +۵ مورد دیگر

Prof. Dr. Katja Dörschner Boyaci is a Professor at Justus-Liebig-Universität Gießen , Faculty of Psychology and Sports Science, leading the Perception & Active Exploration Group . Her research focuses on understanding how the human brain constructs rich perceptual experiences from sensory input, particularly in the perception of material properties like softness, glossiness, and roughness. Research Interests: Computational and neural mechanisms of material perception Integration of visual and haptic information Expectation-driven modulation of perception Neuroimaging (fMRI, EEG) and psychophysical approaches Virtual reality and computational modeling Her work combines psychophysics , neuroimaging , and computational modeling to explore how humans judge material properties from static and dynamic images, and how prior experiences shape these perceptions. Scientific Contributions: Published extensively on material perception, with recent papers in Nature Human Behaviour , Journal of Neuroscience , and Vision Research . Leads the collaborative B8 project on integrating experience and sensory information in material perception. Collaborations & Funding: Co-leads the B8 project with Prof. Hüseyin Boyaci, funded to investigate neural mechanisms of expectation-based perception. Employs interdisciplinary methods including EEG, fMRI, VR, and behavioral experiments. Laboratory & Team: The Perception & Active Exploration Group at Giessen University studies how humans perceive intrinsic object qualities through active exploration and sensory integration, with implications for product design, computer graphics, and robotics.

• Perception
• Computational Neuroscience
• Material Perception
• +۵ مورد دیگر

Thorsten A. Kern is Professor and Director of the Institute of Mechatronics in Mechanical Engineering at Hamburg University of Technology (TUHH). He joined TUHH in January 2019 after serving as R&D manager for interior components at Continental, leading a team of 300 engineers worldwide. From January 2023 to January 2025, he served as Dean of the Faculty of Mechanical Engineering, and is elected to serve as Vice President for Teaching and Learning from October 2025 to October 2028. Since 2022, he has been Vice President of the EuroHaptics Society. Dipl.-Ing. (2002), Darmstadt University of Technology Dr.-Ing. (2006), Darmstadt University of Technology Prof. Kern's research focuses on electromagnetic sensors and actuators, particularly their system integration in high-dynamic applications. His work spans human-machine interfaces, haptic devices, and the intersection of technology with arts. He has a strong interest in medical applications including robotic rehabilitation systems, wearable exoskeletons, and telemanipulation systems. His research also extends to maritime applications, including ship energy systems and ocean monitoring technologies. Prof. Kern's recent publications reveal a strong focus on haptic interfaces, rehabilitation robotics, and maritime energy systems. His work combines theoretical modeling with practical implementation, often involving interdisciplinary teams. There's a clear trajectory toward tele-rehabilitation systems with haptic feedback, maritime power systems optimization, and novel sensor development. His research demonstrates consistent integration of mechanical, electrical, and control engineering principles to solve complex real-world problems. Over 30 patent families with >120 patent applications worldwide Main editor of "Engineering Haptic Devices" (3rd edition) Vice President of EuroHaptics Society (since 2022) Prof. Kern shows a strong passion for entrepreneurship and mentors young people through the Impossible Founders network. He actively supports students in IP-oriented exploitation of research findings, leveraging his extensive patent experience. His research is supported by various projects in haptics, mechatronics, and rehabilitation engineering, with collaborations spanning academia and industry. Prof. Kern leads the Institute of Mechatronics in Mechanical Engineering (M-4) at TUHH, which houses specialized laboratories including the Haptics Lab, PHiLsLab (Power Hardware-in-the-Loop Laboratory), and Optics Lab (Goniometer Laboratory for Measuring Light Fields). His research team includes multiple research assistants and doctoral students working on electrical measuring systems, autonomous multi-sensor drifters, SMART Sensor Particles, and human-machine collaboration projects.

• Electromagnetic Sensors and Actuators
• Human-Machine Interfaces
• Haptic Devices
• +۴ مورد دیگر

Andreas Fender is a researcher at the Visualization Institute of the University of Stuttgart (VISUS), affiliated with the Schmalstieg Working Group. He has held postdoctoral positions at ETH Zurich (Switzerland) and the University of Sussex (England), following his PhD at Aarhus University (Denmark) with an internship at Microsoft Research (USA). His research focuses on Human-Computer Interaction, particularly in Augmented and Virtual Reality (AR/VR) and camera networks. He develops novel input methods for productivity and artistic expression in Mixed Reality environments, creating hybrid physical-digital systems like OptiBasePen, PressurePick, InfinitePaint, and DeltaPen. Recent work includes contributions to Mixed Reality input methods (UIST 2024, CHI 2022) and collaborative systems (Asynchronous Reality). Projects like GuitarPie (UIST 2025) and OptiBasePen (UIST 2024) demonstrate his focus on mobile interaction and ergonomic design. Scientific accolades include the Best paper award at CHI 2022 Best application paper award at ISS 2019 . At VISUS, he collaborates with Dieter Schmalstieg and leads hiring for PhD students and PostDocs exploring physical-digital workflows, artistic tools, and critical AI engagement. His work integrates machine learning, hardware prototyping, and spatial user interfaces to redefine future workplaces.

• Human-Computer Interaction
• Augmented Reality
• Virtual Reality
• +۶ مورد دیگر

Katherine J. Kuchenbecker is the Director of the Haptic Intelligence Department at the Max Planck Institute for Intelligent Systems in Stuttgart, Germany, and an Honorary Professor at the University of Stuttgart. She previously held a tenured position as an Associate Professor at the University of Pennsylvania. Her research focuses on haptic interfaces and sensing systems, enabling users to interact with virtual and distant objects through touch. She earned her Ph.D. in Mechanical Engineering from Stanford University and completed postdoctoral research at Johns Hopkins University. Her academic journey includes leadership roles such as co-chair of the IEEE Technical Committee on Haptics and associate editorships for major conferences. She has received numerous awards, including the NSF CAREER Award (2009), IEEE Academic Early Career Award (2012), and elevation to IEEE Fellow (2021). Her work spans applications in medical robotics, teleoperation, and human-robot interaction. Kuchenbecker’s research emphasizes translating haptic technology into real-world applications, such as surgical training, tactile feedback in virtual environments, and assistive devices. Her team’s contributions include innovations in wearable haptic devices and tactile sensing for robots. She frequently delivers keynote addresses and chairs international conferences, furthering the field’s global impact. Her publications highlight advancements in haptic feedback systems, surgical robotics, and biomimetic sensors. She also advocates for diversity and leadership in academia, serving as Spokesperson for the International Max Planck Research School for Intelligent Systems since 2017.

• Haptics
• Robotics
• Human-Computer Interaction
• +۳ مورد دیگر

Prof. Dr. Thorsten Thormählen is a University Professor for Computer Graphics and Multimedia Programming in the Department of Mathematics and Computer Science at Philipps University Marburg, Germany, a position he has held since October 2012. Prior to this, he served as Substitute Professor for Interactive Graphics Systems at the University of Tübingen (2011-2012) and led the independent research group "Image-based 3D Scene Analysis" at the Max Planck Center for Visual Computing and Communication (2007-2012). His academic background includes a PhD (Dr.-Ing.) from the University of Hannover (2000-2005), where he also worked as a full-time scientific assistant, and a Diploma in Electrical Engineering from the University of Duisburg (1994-1999). Prof. Thormählen's research centers on Visual Computing , spanning Computer Graphics , Computer Vision , Video Processing , and Human-Computer Interaction . His work pioneers tools for 3D reconstruction (e.g., Multi-View Photometric Stereo), video manipulation (e.g., MovieReshape), and multimedia processing (e.g., GSN Composer), with groundbreaking contributions to accessibility through haptic and auditory interfaces for blind 3D modelers. His lab develops practical systems that bridge theoretical computer vision with real-world applications. Analysis of his 15 most recent publications reveals a consistent focus on photometric stereo techniques for 3D reconstruction, video processing innovations, and accessibility-driven interfaces. His work increasingly emphasizes inclusive design, particularly for visually impaired users, while maintaining technical rigor in camera calibration, surface modeling, and multi-sensor fusion. At the Max Planck Center, he established and led the "Image-based 3D Scene Analysis" research group, which advanced methods for reconstructing 3D environments from video sequences. His current work at Marburg continues this trajectory, integrating computer vision, graphics, and human-centered design to solve complex problems in digital content creation and accessibility.

• Computer Graphics
• Computer Vision
• Video Processing
• +۴ مورد دیگر

Li Yi is a Professor in the Department of Computer Science at Tsinghua University's School of Information Science and Technology, where they lead cutting-edge research at the intersection of computer vision, 3D graphics, and robotics. Their work focuses on advancing neural rendering, point cloud processing, and embodied AI with applications in human-object interaction and robotic manipulation. Research interests span Computer Vision , 3D Graphics , Robotics , Point Cloud Processing , Neural Rendering , and Human-Object Interaction . Recent work explores language-grounded spatial reasoning, dexterous manipulation, and 4D dynamic content generation, with publications appearing in top venues like CVPR, ICCV, and NeurIPS. Their research bridges theoretical advances with practical applications in embodied AI systems. The publication trends reveal a strong focus on neural rendering techniques (particularly NeRF variants), embodied AI for robotic manipulation , and multimodal understanding integrating vision, language, and action. Recent work increasingly incorporates large language models and focuses on generalizable approaches that transfer from simulation to real-world settings. As an advisor, Professor Li has mentored numerous students including Yunze Liu, Xueyi Liu, Zekun Qi, and Runpei Dong, who frequently appear as first authors on collaborative publications. Their research has been supported by significant grants enabling work on human-robot interaction, 3D scene understanding, and embodied AI systems. Professor Li leads a research group focused on developing comprehensive frameworks for spatial reasoning, object manipulation, and dynamic scene understanding. The team works on creating benchmarks like TACO for tool-action-object understanding and developing systems like MobileH2R for human-robot handover tasks. Current work emphasizes real-world applicability with a focus on generalizable solutions that work across diverse settings.

• Computer Vision
• 3D Graphics
• Robotics
• +۴ مورد دیگر

Tim Schneider is a Ph.D. student at the Intelligent Autonomous Systems lab of Technische Universität Darmstadt , working in collaboration with École Centrale de Lyon under the Aristotle project. His research focuses on robotics , particularly at the intersection of active perception , tactile sensing , and robotic manipulation . His work investigates how robots can develop environmental understanding through physical interaction , drawing parallels to children's exploratory behavior . Key projects include tactile reinforcement learning , active inference for manipulation , and visuo-tactile sensor fusion in dynamic tasks. Recent publications emphasize foundation models for tactile learning , sensor simulation (TacEx), and multi-modal control systems (AllmAN). He supervises theses on topics ranging from teleoperation feedback to haptic MNIST benchmarks , with a focus on reinforcement learning applications in robotic systems.

• Robotics
• Reinforcement Learning
• Robotic Manipulation
• +۲ مورد دیگر