جستجوی استاد راهنمای دانشگاهی

Nadia Figueroa is the Shalini and Rajeev Misra Presidential Assistant Professor in the Mechanical Engineering and Applied Mechanics (MEAM) Department at the University of Pennsylvania. She holds secondary appointments in Computer and Information Science (CIS) and Electrical and Systems Engineering (ESE), and is a core faculty member at the GRASP Lab. Prior to Penn, she was a Postdoctoral Associate at MIT’s CSAIL and earned her PhD in Robotics from EPFL under Prof. Aude Billard. Her research focuses on physical and perceptual adaptive intelligence for robots, enabling fluid collaboration with humans in dynamic environments. Key applications include robot learning from demonstration , human-robot co-manipulation , safe navigation in human-centric spaces , and rehabilitation robotics . Her work integrates machine learning control theory artificial intelligence biomechanics psychology with guarantees of stability, safety, and robustness . Recent publications highlight advancements in reactive collision avoidance dynamical system learning intent estimation EEG-driven assistive control origami-based reconfigurable robots across platforms like autonomous vehicles and humanoid robots. She has authored a 2022 textbook on dynamical systems for robot control and received the Presidential Assistant Professorship at Penn.

• Robot Learning from Demonstration
• Human-Robot Collaboration
• Dynamical Systems
• +۵ مورد دیگر

Olga Sorkine-Hornung is a Professor of Computer Science at ETH Zurich and head of the Institute of Visual Computing. She leads the Interactive Geometry Lab, focusing on theoretical and practical advancements in digital content creation, geometry processing, and shape modeling. Current position: ETH Zurich, Department of Computer Science Previous roles: Courant Institute (NYU), Technical University of Berlin Education: BSc and PhD from Tel Aviv University, postdoc at TU Berlin Her research spans shape representation, digital fabrication, computer animation, and fundamental geometry processing. Key contributions include Laplacian surface editing, as-rigid-as-possible deformation, and generalized winding numbers. She works on applications in VR, AR, and autonomous systems. Awards include Test of Time Awards (2024), ACM Fellow (2020), ERC Consolidator Grant (2020), and EUROGRAPHICS Young Researcher Award (2008). She has supervised numerous students and co-developed software libraries like libigl and Instant Meshes . Co-chair roles for SIGGRAPH, Eurographics, and Pacific Graphics Editorial board member for ACM Transactions on Graphics and other journals Keynote speaker at VMV, CVPR, and SIAM conferences Her work bridges mathematical rigor with practical implementation, advancing computer graphics and geometry processing through intuitive algorithms that maintain surface detail while enabling efficient computation.

• Digital Content Creation
• Geometry Processing
• Shape Representation and Editing
• +۵ مورد دیگر

Shubham Tulsiani is an Assistant Professor at Carnegie Mellon University's Robotics Institute, where he leads the Computer Vision group and the Physical Perception Lab. His research focuses on inferring physically and spatially grounded representations from perceptual inputs, with applications in 3D vision, robot manipulation, and neural scene reconstruction. He directs an active research group with multiple PhD and Master's students. Research interests center on 3D scene understanding , robot learning , and generative modeling , with specific emphasis on: self-supervised perception, neural rendering, multi-view geometry, manipulation from visual inputs, and physics-based reasoning. The lab develops methods that leverage physical world constraints as supervisory signals. Recent publications demonstrate strong focus on diffusion models for 3D tasks , sparse-view reconstruction , and robotic manipulation transfer . Key trends include neural inverse rendering, view synthesis from limited observations, and translating human interactions to robot actions. Awards include: Best Student Paper Award at CVPR 2015 Advising includes supervision of 5 PhD students, 4 MS students, and undergraduates. Lab alumni hold positions at Google, Stanford, Meta, and Princeton. The Physical Perception Lab collaborates with FAIR Pittsburgh and the CMU Computer Vision group.

• Computer Vision
• 3D Vision
• Robot Learning
• +۴ مورد دیگر

Wim Gevers is a faculty member at the Université libre de Bruxelles (ULB) and leads the CS4S – Cognitive Control & Sleep laboratory within the CRCN research centre. His work bridges cognitive psychology, neuroscience and sleep research to understand how the brain exerts control over thoughts and actions and how sleep contributes to these processes. Research Interests Cognitive Control & Metacognition: Investigating how subjective experiences such as confidence and the "urge-to-err" guide strategic adjustments in behaviour. Working Memory & Ordinal Cognition: Examining how order information is maintained and manipulated, and how these processes relate to mathematical competence. Sleep, Memory & Decision Making: Exploring how sleep-dependent consolidation influences motor learning and decision strategies. Across his 2022–2025 publications a clear trend emerges: a focus on metacognitive monitoring —how humans evaluate their own cognitive states—and the role of emotional and temporal context in shaping those evaluations. Studies range from reaction-time introspection and confidence judgements in perceptual tasks to the impact of aging and depression on metacognitive accuracy. Doctoral Supervision & Mentoring Whitney Stee (PhD 2024) – Sleep-dependent structural brain reorganization & motor learning Gaia Corlazzoli (PhD 2024) – Subjective experience in decision-making Myrtille Dewulf (PhD 2023) – Ordinal coding mechanisms in working memory Rebeca Sifuentes-Ortega (PhD 2023) – REM sleep and memory reactivation All dissertations were defended at ULB, Faculté des Sciences psychologiques et de l’éducation, with Wim Gevers formally listed as Promotor . Laboratory & Collaborative Networks As head of CS4S, Gevers coordinates a multidisciplinary team that combines behavioural experimentation, EEG/MEG, computational modelling and sleep polysomnography. The lab is embedded in the larger CRCN ecosystem, fostering collaborations with groups such as CO3 (consciousness), LCLD (language & deafness), and UR2NF (neurofunctional imaging).

• Cognitive control
• Metacognition
• Working memory
• +۳ مورد دیگر

Andrea Cavallaro is a Full Professor at the École Polytechnique Fédérale de Lausanne (EPFL) and Director of the Idiap Research Institute. He holds dual appointments in the School of Engineering (STI) within the Institute of Electrical Engineering and Measurements (IEM) and the School of Engineering's Education Unit (SEL-ENS). His research focuses on machine learning for multimodal perception, privacy-preserving AI, and autonomous systems. Cavallaro earned his PhD in Electrical Engineering from EPFL in 2002 and has held leadership roles including Director of Research at Queen Mary University of London and Turing Fellow at The Alan Turing Institute. Education: PhD in Electrical Engineering (EPFL, 2002) Leadership: Idiap Director, Affiliate at ELLIS Society Editorial Roles: Editor-in-Chief of Signal Processing: Image Communication (2020–2023), Senior Area Editor for IEEE Transactions on Image Processing Research Interests: Machine learning for audio-visual sensing, privacy in AI, autonomous systems perception, and ethical AI frameworks. Key projects include AlignAI (trustworthy AI alignment) and CORSMAL (multimodal object manipulation). Recent articles explore privacy-aware AI models, adversarial attacks, and multimodal perception systems. His work bridges theoretical advancements with practical applications in robotics, healthcare, and education. Awards include the Royal Academy of Engineering Teaching Prize and IAPR Fellowship. Teaching: Leads courses on deep learning ethics and multimodal AI at EPFL. Advising: Supervises 11 PhD students in areas like privacy-preserving algorithms and autonomous systems. Labs/Teams: Coordinates Idiap’s Audiovisual Intelligence and Learning Lab (LIDIAP) and collaborates on projects like GraphNEx (explainable AI via graph neural networks).

• Machine Learning
• Artificial Intelligence
• Computer Vision
• +۷ مورد دیگر

Dr. Heather Culbertson is an Assistant Professor in the Department of Computer Science at the University of Southern California, leading the HaRVI (Haptics Robotics and Virtual Interaction) Laboratory. Her research focuses on designing haptic hardware and algorithms to create intuitive human-robot interactions through touch, emphasizing realism in virtual environments and social connectedness. Key areas include mediated touch, wearable haptic systems, and multisensory integration in VR/AR applications. The lab's work spans robotics, human perception modeling, and cross-disciplinary solutions for healthcare and immersive technologies. Research interests revolve around tactile feedback systems, social robotics, and the psychological impact of haptic interfaces. Recent work explores real-time haptic texture rendering, affective communication via touch, and motion platforms for VR. Culbertson's projects often integrate human factors early in design to ensure usability and immersion. Publications highlight advancements in haptics coding standards, drone-human interaction, and emotion regulation systems. Her contributions bridge engineering and cognitive sciences, addressing challenges in wearable tech, surgical training simulations, and assistive robotics. The HaRVI Lab collaborates across disciplines to advance tactile interfaces for virtual reality, social robotics, and medical applications.

• Haptics
• Robotics
• Virtual Reality
• +۳ مورد دیگر

Gerd Bruder is an Associate Professor at the University of Central Florida , affiliated with the Department of Computer Science . He previously held positions as a Research Associate Professor at UCF's Institute for Simulation and Training (2016-2022), Post-Doc at University of Hamburg (2014-2016), and Post-Doc at University of Würzburg (2011-2014). Habilitation : Computer Science, University of Hamburg (2017) Ph.D. : Computer Science, University of Münster (2011) M.Sc. : Computer Science (minor in Mathematics), University of Münster (2009) Research Interests : Gerd Bruder's work focuses on Extended Reality (XR) systems, spanning Virtual Reality (VR) , Augmented Reality (AR) , and Mixed Reality (MR) . Key areas include human factors , digital twins , 3D user interfaces , and perceptual modeling , with applications in healthcare, military operations, architecture, and smart environments. Recent Publications highlight innovations in XR locomotion , trust calibration with autonomous agents, spatial cognition , and haptic-visual integration . His 2025 articles address task-switching efficiency in XR and collaborative mixed reality design. Scientific Awards : Best Paper at ACM VRST 2023 2021 TechConnect Innovation Award Best Demo at ACM SUI 2021 Multiple Best Paper Awards (2016-2023) Best Poster & Demo Awards (2015-2020) Patents include systems for medical simulation , smart environment interruption management , and adaptive AR interfaces . His work bridges academic research and practical applications across VR, AR, and MR domains.

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

Susan Hughes, Ph.D., is a Professor of Psychology and Director of the Evolutionary Studies Program at Albright College. She holds a B.S. in Psychobiology from Binghamton University and a Ph.D. in Biopsychology from the University at Albany, SUNY. Her work bridges evolutionary psychology, biopsychology, and the study of human mating strategies. She explores how voice characteristics convey social, biological, and behavioral information, including attractiveness, mate selection, and sexual behavior. Her research also examines facial/body measures in attraction, female preferences for resources, and sexual orientation from an evolutionary lens. Education: B.S. Psychobiology, Binghamton University, SUNY Ph.D. Biopsychology, University at Albany, SUNY Research Interests: Evolutionary Psychology: Human mating strategies, sex differences, and ancestral adaptations Voice Analysis: Vocal attractiveness, manipulation, and its role in social perception Mating/Sexual Behaviors: Post-coital behaviors, jealousy, and physical markers of fitness Labs/Teams: Directs the Evolutionary Studies Program, fostering interdisciplinary research on evolutionary principles. Collaborates with colleagues on studies of vocal perception and behavioral ecology. Grants/Awards: None explicitly listed. Teaching: Teaches courses including Evolutionary Psychology, Human Sexuality, and Psychobiology. Engages students in research labs and fieldwork.

• Evolutionary Psychology
• Biopsychology
• Voice Attractiveness Analysis
• +۲ مورد دیگر

Adam Finkelstein is a Professor in the Department of Computer Science at Princeton University, where he has been a faculty member since 1997. He holds a PhD and Master's in Computer Science from the University of Washington and a dual degree in Physics and Computer Science from Swarthmore College. Finkelstein is renowned for his interdisciplinary work at the intersection of computer graphics, audio processing, and machine learning, and he co-organized the Art of Science exhibition at Princeton. Education: PhD, Computer Science, University of Washington MS, Computer Science, University of Washington BA, Physics and Computer Science, Swarthmore College His research spans audio processing (e.g., speech enhancement, voice conversion, audio metrics), computer graphics (e.g., line drawing algorithms, stylized rendering, image manipulation), and machine learning (e.g., self-supervised learning, differentiable programming). His work often bridges technical and creative domains, exemplified by collaborations at Pixar and Adobe Creative Technologies Lab. Recent publications highlight advancements in audio super-resolution and voice conversion using deep learning frameworks, as well as stylized line rendering for animated 3D models. His contributions to perceptual audio metrics and shader optimization further underscore his impact on human-centric computational systems. Scientific Awards: NSF CAREER Award Alfred P. Sloan Fellowship Fellow of the Association for Computing Machinery (ACM) Finkelstein has secured foundational grants for his research and actively mentors students, though no specific advisees are listed. He also explores collaborative tools for internet music performance, reflecting his broader interest in distributed systems and user interfaces.

• Computer Science
• Audio Processing
• Image Processing
• +۳ مورد دیگر

Dr. Lisa Libby is a Professor of Social Psychology at The Ohio State University, affiliated with the Department of Psychology. Her research focuses on how subjective perceptions shape cognition, emotion, and behavior, with a particular emphasis on mental imagery and visual perspective. She explores how manipulating these processes can improve decision-making, emotional well-being, and social harmony. Libby holds a PhD from Cornell University (2003), an MA from Simmons College (1997), and a BA from Williams College (1996). Education: PhD in Psychology, Cornell University, 2003 MA in Psychology, Simmons College, 1997 BA in Psychology, Williams College, 1996 Her research investigates how visual perspective in mental imagery influences self-perception, memory, and goal pursuit. Key themes include the interplay between imagery, identity, and decision-making, with applications to personal and interpersonal contexts. Libby's work highlights how shifting perspectives (e.g., first- vs. third-person imagery) can alter emotional responses, reduce bias in self-assessment, and enhance adaptive behaviors. Her advising contributions include mentoring students like Valenti G. and Shaeffer E.M., who have co-authored influential studies on imagery perspective and memory. Libby's lab at Ohio State University continues to advance understanding of how subjective experiences are constructed and manipulated through psychological mechanisms. Her research spans cognitive and social psychology, addressing topics such as autobiographical memory, regulatory fit, and the psychological effects of motion on conflict resolution. She has contributed to major academic volumes, including The Oxford Handbook of Social Cognition and Advances in Experimental Social Psychology .

• Social Psychology
• Cognitive Psychology
• Decision-Making
• +۵ مورد دیگر

Prof. Yon Visell is an Associate Professor at the University of California, Santa Barbara (UCSB) with appointments in the Department of Bioengineering, Department of Electrical and Computer Engineering, and Department of Mechanical Engineering. He directs the RE Touch Lab, which focuses on haptics, robotics, and interactive technologies, including sensorimotor augmentation, soft robotics, and virtual reality applications. The lab is affiliated with the Media Arts and Technology Program, Communication and Signal Processing group (ECE), Dynamic Systems and Control group (ME), California NanoSystems Institute, Center for Polymers and Organic Solids, UCSB Research Center for Virtual Environments and Behavior, and UCSB Robotics Group. Education: PhD in Electrical and Computer Engineering from McGill University, MA in Physics from University of Texas, Austin, and BA in Physics from Wesleyan University His research spans robotics, haptics, biomechanics, and soft electronics, aiming to advance human-computer interaction and wearable technologies. Recent work includes light-driven tactile displays, biomechanical filtering in tactile encoding, and haptic systems for VR and healthcare. The lab has received numerous awards at IEEE Haptics Symposium, World Haptics Conference, and EuroHaptics Society events. 2025 Best Demonstration Awards at IEEE World Haptics Conference 2024 Best Paper at IEEE Haptics Symposium 2023 Best Journal Paper at IEEE Transactions on Haptics Visell's group has pioneered wave-based haptic rendering, tactile holography, and soft wearable robotics. They have developed tools like SkinSource for tactile biomechanics simulation and collaborated with institutions in North America, Europe, and Japan. Current projects involve photonics-driven tactile systems, soft robotics for therapy, and next-generation haptic interfaces while mentoring students like Gregory Reardon (2024 EuroHaptics Best Dissertation), Max Linnander (IEEE Haptics awards), and Neeli Tummala (SWE Intel Scholar). Research Grants: Funded by NSF, tech, and healthcare industries Lab: RE Touch Lab at California NanoSystems Institute Collaborations: with TU Dresden, Northwestern University, NC State, UCLA, and others

• Haptics
• Robotics
• Human-Computer Interaction
• +۵ مورد دیگر

Daniel M. Wolpert is a Professor of Neuroscience at Columbia University and Principal Investigator at the Zuckerman Institute. His research focuses on computational models of movement, integrating sensory cues and cognitive elements to understand motor control, memory, and rehabilitation strategies for cerebellar disorders. Key Research Areas: Sensorimotor integration, probabilistic inference, reinforcement learning, predictive modeling of movement, and aging effects on motor learning. Selected Awards: Royal Society Fellow (2012), Minerva Golden Brain Award (2010), Fulbright Scholarship (1992-1995). Recent publications highlight his work on contextual learning, motor memory formation, and the computational basis of sensorimotor uncertainty. His lab develops robotic interfaces to study human motor behavior and collaborates on clinical applications for movement disorders. Current opportunities include postdoctoral fellowships in sensorimotor control and decision-making.

• Motor Control
• Computational Neuroscience
• Sensorimotor Learning
• +۴ مورد دیگر

Anand Bhattad is an Assistant Professor in the Department of Computer Science at Johns Hopkins University, starting Fall 2025. Previously, he held positions as a Research Assistant Professor at the Toyota Technological Institute at Chicago (TTIC) and a visiting scholar at UC Berkeley. His research focuses on the intersection of computer vision, generative modeling, and physical reasoning, aiming to develop perception-driven and physics-aware visual models. His academic journey includes a PhD in Computer Science from the University of Illinois Urbana-Champaign under David Forsyth, with mentorship from Derek Hoiem, Svetlana Lazebnik, Greg Shakhnarovich, and Shenlong Wang. Prior to his PhD, he earned dual master’s degrees in Computer Science and Civil and Environmental Engineering at UIUC and a bachelor’s in Civil Engineering from NITK Surathkal, India. Research interests center on how generative models encode physical and perceptual knowledge, with key contributions in intrinsic image emergence, projective geometry limitations, and physics-aware relighting techniques. His work bridges classical computer vision concepts with modern deep learning, producing state-of-the-art methods for 3D scene synthesis and image editing. Articles span topics like 3P Vision , diffusion models, and 360° video datasets, reflecting interdisciplinary approaches in computer graphics and computational photography. Scientific awards include Outstanding Reviewer at ICCV 2023, CVPR 2022 Best Paper Finalist, and multiple conference service roles as workshop organizer and area chair. He designed the TTIC course Past Meets Present: A Tale of Two Visions , teaching connections between historical and modern computer vision research.

• Computer Vision
• Computer Graphics
• Generative Modeling
• +۲ مورد دیگر

Jas Brooks is an incoming Assistant Professor at MIT's Department of Electrical Engineering and Computer Science (EECS) and the Computer Science and Artificial Intelligence Laboratory (CSAIL), starting Fall 2026. They completed a PhD in Computer Science at the University of Chicago under Prof. Pedro Lopes, focusing on perceptual engineering—designing interfaces to modulate human sensory perception. Their work addresses challenges in power efficiency and miniaturization for senses like taste, touch, and smell, enabling applications in health, safety, and immersive experiences. Research interests span HCI, olfactory interfaces, thermal feedback systems, and wearable technology. Notable publications include Best Paper Awards at CHI 2020 and CHI 2021, and Honorable Mentions at UIST 2023 and UIST 2021. Awards include the NSF Graduate Research Fellowship, Siebel Scholar, and Rising Star in EECS. Brooks has presented at MIT, UCSD, and international symposia, including a keynote at the 'New Metabolism' event. They co-organized workshops on smell/taste interfaces (STT21, STT23) and led projects like the Timeless Smell Archive and Smell & Paste prototyping toolkit. Teaching includes a graduate VR course at SAIC and contributions to sensory education via the CBORG initiative. Labs/teams include Pedro Lopes' research group at UChicago and collaborations with institutions like the Media Archaeology Lab. Current projects explore adaptive EMS systems, thermal feedback wearables, and historical scent technologies.

• Human-Computer Interaction (HCI)
• Perceptual Engineering
• Olfactory Interfaces
• +۵ مورد دیگر

Raymond J. Mooney is a Professor in the Department of Computer Science at the University of Texas at Austin, where he has been a faculty member since 1987. He is the Director of the UT Artificial Intelligence Laboratory and affiliated with multiple research groups including the Machine Learning Research Group, UT Computational Linguistics Lab, and the UT Center for Computational Biology and Bioinformatics. He holds a B.S., M.S., and Ph.D. in Computer Science from the University of Illinois at Urbana-Champaign, where his thesis was supervised by Gerald DeJong. His research spans diverse areas in artificial intelligence, machine learning, and natural language processing: Natural Language Learning Connecting Language and Perception Statistical Relational Learning Information Extraction Transfer and Active Learning Abductive Reasoning Text Mining and Clustering Recommender Systems Knowledge-Base Refinement Recent publications highlight trends in grounded language processing, human-robot interaction, and multimodal reasoning. He has been recognized with prestigious fellowships including ACL (2014), ACM (2010), and AAAI (2005). Scientific awards: Fellow of the Association for Computational Linguistics (2014) Fellow of the Association for Computing Machinery (2010) Fellow of the American Association for Artificial Intelligence (2005) Classic Paper Award (2019) Best Paper Awards (2007, 2004, 1996) He teaches graduate courses like CS 371R: Information Retrieval and Web Search (Fall 2025) and CS 395T: Grounded Natural Language Processing (Spring 2025). His research labs include: UT Artificial Intelligence Laboratory Machine Learning Research Group UT Computational Linguistics Lab UT Center for Computational Biology and Bioinformatics

• Artificial Intelligence
• Bioinformatics and Computational Biology
• Machine Learning
• +۱۴ مورد دیگر