جست‌وجوی استاد و پژوهشگر

Frank Wallhoffمشاهده پروفایل

استاد

• Assistive Technologies
• Human-Machine Interaction
• Cognitive Systems
• +۱۱ مورد دیگر

Prof. Dr.-Ing. Frank Wallhoff is a Professor for Assistive Technologies at Jade University of Applied Sciences since 2010. He serves as Dean of the Department of Civil Engineering Geoinformation Health Technology and Head of the Institute for Technical Assistance Systems. His career spans over two decades with significant contributions to human-machine interaction, cognitive systems, and assistive technologies. Previously, he worked at Technische Universität München from 1997-2010 where he completed his doctorate and served as a postdoc and Akademischer Rat. His educational background includes: 1988-1991: School education with A-level/high school graduation 1991-1992: Certified Engineer's Assistant 1993-1999: Study of electrical engineering 2002-2006: Doctorate at Technische Universität München on face detection, identification, and emotion recognition Wallhoff's research focuses on the intersection of technology and human needs, particularly in assistive technologies for aging populations and human-robot interaction. His work spans cognitive systems with learning capabilities, social robotics, ambient assisted living, pattern recognition, machine learning, human-machine interaction, and facial expression recognition. He has developed significant databases like the FG-NET Database with Facial Expressions and Emotions, which has been widely used in emotion recognition research. His recent publications (2015-2018) reveal a strong trend toward practical applications of human-robot interaction in healthcare, rehabilitation, and daily living assistance. His work increasingly integrates multimodal sensing, machine learning, and context-aware systems to create adaptive assistance technologies. Key areas include motion exercise recognition for rehabilitation, 3D visualization for underwater vehicle control, and robust human-robot dialogue systems for production environments. His scientific recognition includes: Best Paper Award for 'Experimental Platform for Wizard-of-Oz Evaluations of Biomimetic Active Vision in Robots' at IEEE International Conference on Robotics and Biomimetics (Robio), 2009 Wallhoff has secured significant research funding including the EITAMS project (€1.5 million from Lower Saxony Volkswagen Advance Programme) focused on affordable underwater vehicle systems, and the INTERREG project 'Vital Regions' (2017-2020) developing technologies to support elderly in rural areas. He coordinates the ALIAS project (Adaptable Ambient Living Assistant) and has led multiple projects within the Cluster of Excellence CoTeSys, including JAHIR, ACIPE, EYETRACK, and RealEYE. His research bridges academic innovation with practical applications, particularly in healthcare technology and assistive systems. He leads the Institute for Technical Assistance Systems at Jade University, where his team develops innovative solutions at the intersection of cognitive systems, human-robot interaction, and assistive technologies. Current initiatives focus on underwater robotics for maritime applications, rehabilitation technologies using motion tracking, and ambient assisted living systems for elderly care.

• Visual Communication
• Data Visualization
• Graphic Design
• +۷ مورد دیگر

Robert Bossart serves as a Lecturer at the Lucerne University of Applied Sciences and Arts School of Design and Art, teaching interaction design, data visualization, typography, and screen design across Bachelor's and Master's programs since 2002. He concurrently co-manages the design studio "Reflector Visuelle Gestaltung" while instructing in the new BA Spatial Design program since 2020. His educational background encompasses federal certification as a sign and advertising painter, training at the Lucerne Jazz School, and graphic design studies at HSLU where his diploma thesis won the 2001 Lucky Strike Junior Designer Award. Bossart's research centers on visual communication and data visualization, particularly application-oriented projects in energy data representation and didactic visualization. His work bridges design theory with practical implementation in complex systems like building automation, emphasizing user-centered approaches to transform technical data into accessible visual narratives. Publications spanning 2001-2012 reveal an evolution from graphic design history toward architectural data visualization, culminating in his 2012 book on building systems that demonstrates interdisciplinary integration of environmental data and user experience. Key recognitions include: German Design Award (2016) for Excellent Communications Design, Editorial Lucky Strike Junior Designer Award (2001) for Reflector – Diploma thesis With extensive teaching experience since 2002, Bossart has shaped design curricula while participating in KTI-funded research projects on energy visualization and building systems. His industry practice through Reflector provides students with real-world design methodology exposure, though specific advisees aren't documented. As co-founder of Reflector Visuelle Gestaltung, he leads a multidisciplinary team executing design projects while contributing to research initiatives including "Bottom-up energy visualization" and "LARA", maintaining active industry-academia collaboration beyond reduced research participation since 2016.

Shuran Songمشاهده پروفایل

استادیار

• Robotics
• Embodied Artificial Intelligence
• Robot Learning
• +۵ مورد دیگر

Shuran Song is an Assistant Professor of Electrical Engineering at Stanford University, with a courtesy appointment in Computer Science. She leads the Robotics and Embodied Artificial Intelligence Lab (REAL@Stanford), focusing on algorithms enabling robots to learn through physical interaction with the world. Her research spans manipulation, perception, and embodied AI, emphasizing generalizable skills for assistive robotics. Affiliations: Stanford University School of Engineering Labs: REAL@Stanford Research highlights include work on dexterous manipulation, deformable object handling, cross-embodiment learning, and robotic systems like TidyBot and ToddlerBot. Notable awards include Best Paper at ICRA 2024 and Amazon Robotics Best Systems Paper Award (2018). Key publications (2023-2025) address topics such as diffusion policies, embodiment generalization, and robot teaching interfaces. She teaches courses like EE/CS227 (Robot Perception) and leads workshops at top conferences (RSS, ICRA, CoRL).

Ed Morrisonمشاهده پروفایل

مدرس ارشد

• Evolutionary Psychology
• Human Mate Choice
• Facial Attractiveness
• +۳ مورد دیگر

Ed Morrison is a Senior Lecturer at the University of Portsmouth in the School of Psychology, Sport and Health Sciences. He is a member of the Centre for Comparative and Evolutionary Psychology, focusing on evolutionary approaches to human behavior, particularly mate choice and facial attractiveness. His research emphasizes the role of motion in attractiveness, using motion-capture and morphing techniques. Before joining Portsmouth, he completed a PhD at the University of Bristol on improving ecological validity in facial attractiveness research, an MSc in Evolutionary Psychology at Liverpool, and a BA in Natural Sciences (Zoology) at Cambridge. Research Interests: Dr. Morrison explores how movement and facial dynamics influence mate selection, integrating computational methods with evolutionary theory. He investigates the biological and psychological mechanisms underlying perceptions of attractiveness, including the impact of motion, vocal cues, and chemical signals. His work also addresses broader topics like mating strategies and the evolution of social behavior. Grants & Projects: He led the ESRC-funded project 'Strategic Modulation of Dynamic Aspects of Facial and Vocal Attractiveness' (2011-2012). Recent research spans topics like alcohol's effect on facial perception and the development of lie-detection techniques. Awards & Activities: While no specific awards are listed, his work has been widely cited and covered in media. He actively engages in outreach, delivering invited talks at institutions like Saint Swithun's School and participating in conferences globally. Labs & Teams: He contributes to the Centre for Comparative and Evolutionary Psychology, fostering interdisciplinary collaboration in evolutionary behavioral research.

Nicolas Rousselمشاهده پروفایل

پژوهشگر

• Human-Computer Interaction
• Computer-Mediated Communication
• Groupware Systems
• +۷ مورد دیگر

Nicolas Roussel is the Director of the Inria research center at the University of Bordeaux, a role he has held since July 2017. Prior to this, he served as an associate professor (Maître de conférences) at Paris-Sud University and a senior researcher (Directeur de recherche) at Inria Lille - Nord Europe. His academic journey includes a PhD in Computer Science from the LRI and postdoctoral stays at GMD Sankt Augustin and the University of Fribourg. Research Interests: His work focuses on Human-Computer Interaction (HCI), with expertise in computer-mediated communication, groupware systems, interactive systems engineering, and tactile/gestural interaction. He explores human interactions with AI systems and augmented reality, emphasizing user-centered design and system latency optimization. He has contributed to major conferences like ACM CHI, ACM UIST, and ACM CSCW, and co-organized events such as the Forum on Tactile and Gestural Interaction and the 2021 PFIA (Artificial Intelligence Platform). He chairs Aerospace Valley’s 'Data Economy and Artificial Intelligence' ecosystem and serves on scientific boards of GIS Albatros and LyRE. Administrative Roles: He holds board positions at institutions like Digital Aquitaine and Cap Sciences, emphasizing technology’s societal impact. His work bridges academia and industry, including collaborations with Inria-Industry Meetings on digital interaction. Labs/Teams: Involved in Inria project teams such as GraphDeco, Potioc, and Castor, focusing on interactive systems and tactile interfaces. His research addresses challenges in latency compensation, gesture-based interaction, and BCI integration with AR systems.

• Computer Vision
• Machine Learning
• 3D Reconstruction
• +۳ مورد دیگر

Siwei Zhang is a researcher at the ETH Zürich , focusing on computer vision and machine learning. Their work intersects with robotics, human motion analysis, and egocentric vision. Email: siwei.zhang@inf.ethz.ch Research Interests 3D Human Body Modeling Egocentric Vision Systems Motion Reconstruction & Interaction Neural Architecture Optimization Surgical Pose Estimation Selected Publications (2025-2019) Recent work includes neural volumetric body models (2025), egocentric synthetic data generation (2024), robust human motion reconstruction (2024), surgical pose datasets (2023), and foundational studies in probabilistic mesh recovery, whole-body grasping, and face reenactment (2019-2022). Key trends combine computer vision, robotics, and deep learning with applications in scene understanding and human-computer interaction.

Tim McGrawمشاهده پروفایل

دانشیار

• Virtual Reality
• Scientific Visualization
• Real-Time Computer Graphics
• +۲ مورد دیگر

Tim McGraw is an Associate Professor in the Department of Computer Graphics Technology at Purdue University’s Purdue Polytechnic Institute. He specializes in virtual reality, scientific visualization, and medical image processing, with notable work on diffusion tensor MRI (DT-MRI) visualization and mesh editing in VR. He has held industry roles as a Mechanical Engineer and game developer at Electronic Arts, Schell Games, and Rainbow Studios. Education: Ph.D. in Computer and Information Science and Engineering (University of Florida), B.S. in Mechanical Engineering (University of Florida). Research interests focus on blending computational art with scientific challenges, including real-time graphics, medical imaging, and game development. His recent work explores soft-body physics simulation (e.g., Mesh Mortal Kombat) and thermal imaging analysis. Awards include 2024 Best Paper/Presentation at Motion Interaction Games and 2024 SIGGRAPH Best in Show. Grants include 3D Visualization of Molecular Dissolution (2016) and industry partnerships with NVIDIA, Eli Lilly, and Boeing. He holds four patents related to DT-MRI visualization technologies developed with Siemens Corporate Research. Labs/Teams: Leads the Interactive Graphics Technology Lab, contributing to projects like Bodygraphe (a gestural computing art installation showcased at SIGGRAPH 2016).

B.S. Manjunathمشاهده پروفایل

استاد

• Image/Video Analysis
• Multimedia Databases
• Steganography
• +۳ مورد دیگر

B.S. Manjunath is a Professor in the Department of Electrical and Computer Engineering at the University of California, Santa Barbara (UCSB). He serves as Director of the Center for Multimodal Big Data Science and Healthcare and the Center for Bio-image Informatics. His research focuses on image/video analysis, multimedia databases, steganography, and bio-informatics. Manjunath holds a Ph.D. from the University of Southern California (1991), M.E. from Indian Institute of Science (1987), and B.E. from Bangalore University (1985). He is an IEEE Fellow and ACM Fellow. Education: Ph.D. (1991), Signal & Image Processing Institute, EE-Systems, USC M.E. (1987), Systems Science and Automation, Indian Institute of Science B.E. (1985), Electronics Engineering, Bangalore University Research Interests: Image/video analysis (segmentation, registration, texture analysis) Multimedia databases and data mining Steganography and digital forensics Signal/image processing for bio-informatics His work includes developing the BisQue open-source platform for image informatics and leading NSF-funded initiatives in bio-image informatics and interactive multimedia. Key Contributions: Over 300 peer-reviewed publications 24 patented technologies Co-editor of the ISO/MPEG-7 multimedia standard Founder faculty of the Media Arts and Technology Program Awards and Affiliations: IEEE Fellow (2025) and ACM Fellow (2025) Affiliated with UCSB’s Computer Science Department and Dynamical Neuroscience Program Former Director of the NSF-sponsored Interactive Digital Multimedia IGERT program Labs and Platforms: Director of the Vision Research Lab Lead developer of the BisQue image informatics system Pioneering work in multimodal camera networks and healthcare analytics

Long Wangمشاهده پروفایل

استادیار

• Robotics
• Continuum Robots
• Telemanipulation
• +۳ مورد دیگر

Long Wang is an Assistant Professor in the Department of Mechanical Engineering at Stevens Institute of Technology, part of the Charles V. Schaefer, Jr. School of Engineering and Science. He holds a Ph.D. in Mechanical Engineering from Vanderbilt University (2018), an M.S. in Mechanical Engineering from Columbia University (2012), and a B.S. in Mechanical Engineering from Tsinghua University (2010). His research focuses on building robots and intelligent machines for challenging environments, with expertise in telemanipulation, kinematic modeling, continuum robots, and robotic hand designs. Dr. Wang leads the Advanced Robot Manipulators Laboratory, which investigates applications in minimally invasive surgery, search and rescue operations, and remotely assisted tasks. Key research areas include compliant manipulator designs, collaborative robotics, and human-in-the-loop teleoperation systems. His recent publications demonstrate a strong focus on continuum robots, underwater manipulation systems, and surgical robotics. Trends show innovative approaches to admittance control, modular designs for aerial and marine applications, and educational robotics initiatives. Courses taught include Robot Manipulators (ME 650), Introduction to Modern Control Engineering (ME 621), and Engineering Graphics (E 120).

Matthias Zwickerمشاهده پروفایل

استاد

• Computer Graphics
• Artificial Intelligence
• Point-Based Graphics
• +۷ مورد دیگر

Matthias Zwicker is the Elizabeth Iribe Chair for Innovation and the Phillip H. and Catherine C. Horvitz Professor of Computer Science at the University of Maryland, where he currently serves as the Chair of the Department of Computer Science. He joined UMD in March 2017 as the Reginald Allan Hahne Endowed E-Nnovate Professor in Computer Science. Prior to UMD, he was a professor at the University of Bern, Switzerland (2008-2017), Assistant Professor at UC San Diego (2006-2008), and a post-doctoral associate at MIT (2003-2006). PhD from ETH Zurich, Switzerland (2003) Matthias Zwicker's research focuses on the intersection of artificial intelligence and computer graphics, with the goal of enabling next-generation AR/VR and computer graphics applications. His work spans several key areas including point-based graphics, gradient-domain rendering, image processing, and 3D reconstruction. He has made significant contributions to surface splatting, texture synthesis, and denoising techniques. His recent work increasingly integrates deep learning approaches with traditional computer graphics techniques. Zwicker's recent publications (2021-2022) show a strong trend toward integrating deep learning with computer graphics, particularly in 3D reconstruction, rendering, and animation. His work increasingly focuses on neural radiosity, point cloud processing, and differentiable rendering techniques. There's a clear emphasis on improving perceptual quality in graphics applications, with many papers addressing challenges in AR/VR systems. His research group frequently publishes at top venues including SIGGRAPH, CVPR, and ICCV. BEST STUDENT PAPER AWARD! at VISAPP 2018 As an active member of the UMD community, Zwicker has served as a University Senator for the CS department, as a faculty co-lead in developing the new Immersive Media Design major, and as a faculty mentor in the Gemstone Honors Program. His service includes conference leadership roles such as papers co-chair for IEEE/Eurographics Symposium on Point-Based Graphics, Eurographics, and Eurographics Symposium on Rendering. Zwicker leads research in the Brendan Iribe Center for Computer Science and Engineering at UMD (room 5244). His work builds on his previous leadership of the Computer Graphics Group at the University of Bern, where he served as head of the group and as director of undergraduate and graduate studies. His research continues to push boundaries in the integration of AI and graphics for next-generation visual computing applications.

• Computer Vision
• Deep Learning
• Remote Sensing
• +۵ مورد دیگر

Lin Xiong is a Professor at Xidian University's School of Artificial Intelligence, Department of Computer Science, with an extensive publication record spanning from 2008 to 2025. His research primarily focuses on computer vision, deep learning, and remote sensing applications, with significant contributions to SAR image processing, domain adaptation techniques, and environmental monitoring systems. Dr. Xiong's educational background includes advanced studies in computer science and artificial intelligence, though specific details of his degrees are not readily available in the publication record. His research interests span multiple domains including computer vision (particularly facial recognition and person re-identification), deep learning architectures, domain adaptation methods, and remote sensing applications for environmental monitoring. His publication trends reveal a strong focus on practical applications of deep learning, with recent work emphasizing class-incremental learning, SAR image registration, and environmental monitoring using lidar technology. The research spans both theoretical advancements in neural network architectures and practical implementations in fields ranging from renewable energy forecasting to coastal ecosystem monitoring. Knowledge distillation techniques for continual learning Advanced SAR image processing algorithms Domain adaptation methods for computer vision tasks Environmental monitoring using remote sensing technology Dr. Xiong has established significant collaborations with researchers from NASA (notably on mangrove ecosystem monitoring projects) and maintains strong connections within China's academic community, particularly with Xidian University colleagues. His work demonstrates both theoretical depth and practical applicability across multiple domains requiring advanced computer vision and machine learning solutions.

Morten Rieger Hannemoseمشاهده پروفایل

استادیار

• Computer Vision
• Medical Imaging
• 3D Reconstruction
• +۳ مورد دیگر

Morten Rieger Hannemose is an Assistant Professor at the Department of Applied Mathematics and Computer Science, Technical University of Denmark (DTU). His research focuses on computer vision, medical imaging, 3D reconstruction, and AI-driven healthcare solutions. He is actively involved in projects like 'Fighting Cancer with Generative AI' and 'Decision support AI for Skin Lesions,' supervising multiple PhD students in these domains. His work contributes to UN Sustainable Development Goals related to health and innovation. Research interests include neural networks, medical image analysis, and computational imaging. Notable achievements include developing methods for digitizing material appearances and estimating diagnostic difficulty in skin lesion diagnosis. He collaborates internationally on topics such as monocular 3D pose estimation and multimodal data fusion. Morten has supervised PhD students in areas like crowd counting through remote sensing, generative AI for cancer diagnostics, and diffusion models for image segmentation. His projects often bridge theory and application, such as creating the 'Sportspose' 3D sports pose dataset. His email is mohan@dtu.dk , and his website is mortenhannemose.github.io .

Dimitris Tzionasمشاهده پروفایل

استادیار

• Computer Vision
• Computer Graphics
• Machine Learning
• +۲ مورد دیگر

Dr. Dimitris Tzionas is an Assistant Professor at the University of Amsterdam leading research at the intersection of Computer Vision, Computer Graphics, and Machine Learning. His work focuses on modeling human appearance, motion, and interactions within physical environments. His research explores: 3D reconstruction of humans and objects from images/video Modeling whole-body interactions with scenes Developing novel representations for articulated motion Creating realistic digital avatars for AR/VR applications Recent publications demonstrate consistent focus on human-object interaction modeling, 3D reconstruction under challenging conditions, and the development of novel datasets. Work frequently appears in top-tier venues like CVPR, ICCV, and ECCV. Awards & Recognition: Outstanding Reviewer - CVPR 2021 Outstanding Reviewer - CVPR 2023 Best Paper Finalist - CVPR 2022 Current PhD students include George Paschalidis and Dimitrije Antic. Research is supported by grants including BMBF funding for 'Machine Learning for Interacting Human Avatars'. The lab maintains collaborations with MPI-IS Tübingen and develops novel capture systems for human motion analysis.

• Robotics and Automation
• Control Systems
• Biomedical Engineering
• +۴ مورد دیگر

Dr. Tajdari is a distinguished researcher at Delft University of Technology, specializing in interdisciplinary fields at the intersection of robotics, control systems, and biomedical engineering. His work focuses on advanced control methodologies, non-rigid registration techniques for medical imaging, intelligent transportation systems, and personalized product design through digital fabrication. He has contributed significantly to the development of adaptive controllers for robotics systems, including Stewart platforms and surgical robots, as well as innovative approaches to 3D/4D human mesh registration for applications in healthcare and biomechanics. Key Research Areas: Autonomous Vehicles, Medical Robotics, Intelligent Transportation, 3D Reconstruction, and Human-Motion Analysis His recent research emphasizes integrating machine learning with traditional control theory to address challenges in traffic management, spinal deformity prognosis, and human-centered design. Collaborations include projects on smart infrastructure systems and personalized medical devices. Over 25 peer-reviewed articles demonstrate his expertise in both theoretical and applied engineering domains.

Trevor Darrellمشاهده پروفایل

استاد

• Artificial Intelligence
• Computer Vision
• Machine Learning
• +۳ مورد دیگر

Professor Trevor Darrell is a faculty member in the Department of Electrical Engineering and Computer Sciences at UC Berkeley. He leads research in computer vision, machine learning, and robotics, focusing on algorithms for visual recognition and perception-based interfaces. His affiliations include the Berkeley Artificial Intelligence Research Lab (BAIR), Berkeley Center for Responsible, Decentralized Intelligence (RDI), and the International Computer Science Institute (ICSI). Education: PhD, MIT (1996) BSE in Computer Science, University of Pennsylvania (1988) Research Interests: Professor Darrell’s work spans Artificial Intelligence , Computer Vision , Robotics , and Multimodal Learning . His recent efforts emphasize vision-language models, embodied AI, and ethical AI frameworks for healthcare and robotics. Notable Contributions: His articles in 2025 highlight advancements in multimodal generation, humanoid control, and model alignment. Trends include leveraging vision-language integration for robotics tasks and addressing AI bias and hallucination. Awards: ICML Test of Time Award (2024) ACM SIGMM Test of Time Paper Award (2024) CVPR Longuet-Higgins Prize (2024) Labs & Collaborations: Leads BAIR and RDI, advancing responsible AI and geospatial analysis through initiatives like Berkeley Deep Drive and the CITRIS People and Robots (CPAR) program.