Find Academic Supervisors

Dimitrios KanoulasView profile

Professor

• Robotics
• Artificial Intelligence
• Machine Learning
• +3 more

Dimitrios Kanoulas is a Professor in Robotics and AI at the Department of Computer Science, University College London (UCL). He holds the UKRI Future Leaders Fellowship and leads research in perception and learning for robotics, focusing on articulated robots navigating and manipulating in uncertain environments. His work emphasizes theoretical advancements in sensing, real-time mapping, and modeling of surface contact areas for locomotion on uneven terrain, leveraging SLAM systems and manipulation techniques. Research interests include robotics perception, SLAM, path planning, and reinforcement learning. His recent work explores adversarial attacks in path planning, high-fidelity simulators (e.g., Unreal Robotics Lab), and robust localization methods like AIR-HLoc and LiteVLoc. He also investigates humanoid robot stability, teleoperation systems, and autonomous mobile manipulators. Key contributions span legged locomotion, manipulation under uncertainty, and safety-critical control systems. His articles reflect trends in combining neural networks with traditional robotics frameworks, emphasizing real-world deployability and robustness. Beyond technical work, he emphasizes human-robot interaction through teleoperation interfaces and wearable technologies. Awards: UKRI Future Leaders Fellow Labs/Teams: RPL Lab at UCL Grants/Advising: No specific grants listed, but his research is supported by UKRI funding. Advising details not explicitly provided in text.

Kynthia ChamilothoriView profile

Assistant Professor

• Environmental Psychology
• Lighting Design
• Human-Technology Interaction
• +3 more

Kynthia Chamilothori is a tenured Assistant Professor in the Human-Technology Interaction (HTI) group at Eindhoven University of Technology (TU/e). She holds additional roles as an Assistant Professor at the EAISI Health institute and the Intelligent Lighting Institute. Her research bridges environmental psychology, architecture, lighting, and technology, focusing on how lighting and nature in spaces influence human wellbeing. She uses VR and biometric sensors to study healthy, comfortable, and energy-efficient environments. Dr. Chamilothori earned her PhD in Architecture from EPFL (2019) and a Master's in Architectural Engineering from Technical University of Crete (2014). She serves on the editorial board of Lighting Research & Technology and leads CIE reporterships on VR in lighting research. Her work addresses UN SDGs related to sustainable cities and communities. Research interests include daylighting, dynamic light patterns, and restorative environments. Notable contributions include studies on light quality perception, virtual reality applications for building performance, and the psychological impacts of natural light. Collaborations span Europe and involve interdisciplinary teams. She has supervised 19 academic works and teaches courses like Environmental Psychology and Light and Experience. Media engagements include interviews on VR's role in lighting research and architectural design.

Andrew HogueView profile

Associate Professor

• Virtual Reality
• Game Design for Education
• Stereoscopic Visualization
• +7 more

Dr. Andrew Hogue is an Associate Professor at Ontario Tech University within the Faculty of Business and Information Technology's Game Development and Interactive Media program. His research focuses on virtual reality (VR), stereoscopic visualization, and user experience optimization. He leads the Game Development Lab, equipping students with cutting-edge technology for research and training. Hogue holds a PhD, MSc, and BSc in Computer Science from York University. He has supervised over 40 undergraduate and five graduate students, securing over $4 million in research funding. His work spans gaming, robotics, simulation, and forensics, with over 30 publications in journals and conferences. Research Interests include developing photorealistic 3D models via photogrammetry, evaluating VR's environmental and design parameters, and enhancing immersive experiences through computer vision. Notable contributions include frameworks for VR user studies (StudyXR/StudyVR) and volumetric video techniques for gaming and education. His articles highlight advancements in volumetric video compression, XR therapeutic tools, and serious games addressing social issues. Collaborations include projects with McMaster Children’s Hospital and IBM, emphasizing real-world applications of VR/AR technologies. Through experiential learning initiatives, Hogue bridges academic research with industry needs, fostering innovation in interactive media and technology-driven solutions.

Stephen LaycockView profile

Professor

• Molecular Graphics
• Scientific Visualization
• Virtual Reality (VR)
• +5 more

Stephen Laycock is a Professor of Computer Graphics at the University of East Anglia (UEA), affiliated with the School of Computing Sciences. He holds additional roles as Associate Dean for Admissions in the Science Faculty. His expertise spans Molecular Graphics, Scientific Visualization, Virtual Reality (VR), Haptics, and GPU programming, with applications in Cultural Heritage preservation and biomedical research. Laycock earned his PhD in 2005 and has been a faculty member since 2005, advancing to Professor in 2024. His research focuses on interactive molecular docking, haptic rendering, and GPU-accelerated algorithms. Notable projects include the development of DockIT software for molecular docking and collaborations in precision agriculture and ornithological migration tracking. Laycock’s work has been recognized with the 2017 Biophysics and Physicobiology Editors’ Choice Award. He teaches computer graphics and GPU programming, and actively supervises PhD students in interdisciplinary areas like virtual reality and haptics. Key initiatives include the Digital Preservation and Immersive Heritage project and GPU-accelerated agricultural monitoring systems.

Mengyu ChuView profile

Assistant Professor

• Physics-Enhanced Deep Learning
• Fluid Dynamics Simulation
• Computer Graphics
• +3 more

Mengyu (Rachel) Chu is a tenure-track Assistant Professor at the School of Intelligence Science and Technology, Peking University, affiliated with the Visual Computing and Learning Lab. Previously, she was a Lise Meitner Postdoctoral Research Fellow at the Max Planck Institute for Informatics (2020–2022), and completed her Ph.D. in Computer Science at Technical University of Munich (2014–2020). She holds a B.Eng. in Software Engineering from Southeast University (2007–2011) and an M.Eng. in Computer Science from Zhejiang University (2011–2014). Her research focuses on Physics-Enhanced Deep Learning , combining deep learning with physical simulations to enhance fluid dynamics modeling, video synthesis, and neural network training. Key areas include fluid reconstruction, manipulation, synthesis, and temporally coherent video generation. Her work bridges physics-based principles with modern AI techniques for realistic simulations and generative models. Notable contributions include Physics Informed Neural Fields for sparse data reconstruction (SIGGRAPH 2022), Learning Meaningful Controls for Fluids (SIGGRAPH 2021), and TempoGAN for fluid flow super-resolution (SIGGRAPH 2018). Her research emphasizes real-world applications in graphics, visualization, and computational physics. She has been recognized with the Lise Meitner Postdoctoral Fellowship (2020) and Summa Cum Laude distinction for her Ph.D. (2020). Her work spans academic publications, patents, and open-source projects, with collaborations across institutions like TU Munich and Max Planck Institute.

• Virtual Reality
• Computer Graphics
• Scientific Visualization
• +3 more

Martin Göbel is a Professor at the Department of Computer Science, Technische Universität Darmstadt, Germany, and affiliated with Fraunhofer IGD. His research focuses on Virtual Reality (VR), Computer Graphics, and Scientific Visualization. He has contributed to VR system development, interaction techniques, and collaborative environments. Notable work includes the Virtual Reality Demonstration Center, laser tracking systems (e.g., Sceptre), and elastic object simulation in VR. Key roles include co-chairing VR conferences (e.g., VR 2018) and editing IEEE Computer Graphics and Applications. His career spans over three decades, with contributions to visualization in engineering, medicine, and topology. He has co-authored over 50 publications, emphasizing real-time rendering, haptic interaction, and distributed VR systems. Publications highlight innovations in tracking systems, collaborative workflows for industries, and educational materials on AR/VR. He has collaborated with institutions like Eurographics and IEEE, advancing VR's practical applications and theoretical foundations.

Stefan GumholdView profile

Professor

• Computer Graphics
• Visualization
• Medical Imaging
• +3 more

Professor Stefan Gumhold is a leading academic in computer graphics and visualization at TU Dresden. He has held roles including Head of the Chair for Computer Graphics and Visualization since 2005 and served as Dean of the Faculty of Computer Science from 2010 to 2012. His expertise spans visualization techniques, medical imaging, and immersive technologies. Gumhold earned his Ph.D. in 2000, focusing on mesh compression, and later received a Dissertation Award in the same year. He has contributed to projects like the Heisenberg Scholar Research Group and led the Kommission Umwelt at TU Dresden. His teaching includes courses such as Introduction to Computer Graphics, Data Visualization, and Scientific Visualization. Gumhold’s research emphasizes visualization platforms (e.g., ISAAC), image fusion, and neural network applications in medical diagnostics. His work often integrates virtual reality for data analysis, as seen in tools like VRCellLabeler and ExtremeWeatherVis. Education: Diploma in Computer Science (University of Tübingen, 1998), M.Sc. in Applied Physics (University of Massachusetts Boston, 1996). Research Highlights: Development of visualization frameworks, 3D reconstruction, and invertible neural networks for outlier detection. Awards: Dissertation Award 2000. Grants & Labs: Leadership in TU Dresden’s Computer Graphics lab and contributions to collaborative research projects like Fast-Haptic.

Massimiliano Di LucaView profile

Associate Professor

• Human Perception
• Multisensory Integration
• Temporal Perception
• +7 more

Massimiliano Di Luca is an Associate Professor at the University of Birmingham, affiliated with both the School of Psychology and the School of Computer Science. His research focuses on understanding the mechanisms of human perception through psychophysical methods, computational modeling, and immersive technologies, particularly in the dynamic and temporal aspects of multisensory integration. He has made significant contributions to the study of virtual reality, haptics, and 3D shape perception. PhD in Cognitive Science (Brown University, 2006) Laurea in Psychology (Università di Trieste, 2000) Di Luca’s research spans human perception, haptics, and computational modeling, emphasizing the temporal dynamics of multisensory processing. His recent work includes the ARME project , Virtual Reality Lab , and collaborations on wearable haptic devices. He has developed models for perceptual recalibration, synchronization in musical ensembles, and tactile feedback optimization in XR systems. His publications highlight trends in virtual reality applications, haptic technology, and multisensory perception, with keywords like 3D shape , augmented reality , Bayesian modeling , and wearable haptics . Notable projects include TEXT: Text Entry for XR Trove and ARME . Scientific Awards: Turing Fellow (2021-2023), Fellow of the InterContinental Academia UBIAS (2021-2023). Di Luca mentors PhD, MSc, and BSc students in psychology and computer science. His grants include funding from EPSRC, BBSRC, Google, and UKRI for projects like ARME , Perception of Materials , and iCURE . He leads the Virtual Reality Lab and has contributed to the InterContinental Academia and Alan Turing Institute .

Femke van BeekView profile

Assistant Professor

• Soft Robotics
• Haptic Perception
• Human-Computer Interaction
• +5 more

Femke van Beek is an Assistant Professor in the Robotics section of the Department of Mechanical Engineering at Eindhoven University of Technology. Her research focuses on integrating soft robotics with haptic perception to develop autonomous robots with tactile sensing capabilities, particularly for agricultural applications within the 4TU Green Sensors project . She employs VR/AR experiments to study human haptic perception and design bio-inspired sensors. Academic Background : PhD in Psychonomics and Cognitive Psychology (Vrije Universiteit Amsterdam), MSc in Sensory Biology and Biomechanics (Wageningen University), and BSc in Biology (Wageningen University). Her research spans soft robotics , haptic feedback , and human-in-the-loop engineering , emphasizing practical sensor design and robotic movement optimization. Recent work includes open-source platforms for real-time control of soft robots and studies on vibrotactile vs. auditory feedback in tele-operation. Scientific Awards : Eurohaptics Society PhD Award (2017)

Jamie PaikView profile

Professor

• Soft Robotics
• Origami Robotics
• Wearable Technologies
• +4 more

Prof. Jamie Paik is a Full Professor at the Swiss Federal Institute of Technology (EPFL), where she serves as Director of the Reconfigurable Robotics Lab (RRL) and is a core member of the Swiss NCCR robotics group. She holds multiple academic appointments across EPFL's School of Engineering, including positions in the Institute of Mechanical Engineering (IGM), STI-SMT SMT-ENS, and STI-SGM SGM-ENS. Additionally, she serves as a PhD program committee member for the Doctoral Program in Robotics, Control and Intelligent Systems. Her research focuses primarily on soft robotics , origami-inspired robotics , and wearable technologies . Prof. Paik's work leverages multi-material fabrication and smart material actuation to develop novel robotic designs that push the physical limits of materials and mechanisms. Her current research includes self-morphing Robogami (robotic origami) that transforms from planar shapes to 2D or 3D structures through predefined folding patterns, similar to traditional paper origami. Prof. Paik has published extensively on robotic origami, haptic feedback systems, and soft actuators, with her most recent work (2024-2025) focusing on vibration of soft twisted beams for locomotion, semi-autonomous surgical assistance, plug-and-play pneumatic systems, and data-driven kinematic modeling. Her research demonstrates a clear trajectory toward more adaptive, reconfigurable robotic systems with applications in surgery, human-robot interaction, and wearable technologies. Among her notable achievements, she developed a 7-DoF humanoid arm during her PhD at Seoul National University (sponsored by Samsung Electronics), which was the lightest in literature at that time (3.7kg including the 8-DoF hand). During postdoctoral work at Pierre Marie Curie University, she developed the internationally patented JAiMY laparoscopic tools now commercialized by Endocontrol-medical.com. PhD: Seoul National University (Humanoid Arm and Hand Design) Postdoc: Institut des Systems Intelligents et de Robotic, Université Pierre Marie Curie Postdoc: Harvard University's Microrobotics Laboratory Prof. Paik has supervised numerous PhD students, both current and past, including Bakir Alihan, Demirtas Serhat, Jiang Shaopeng, Kanno Ryo, Schüssler Alexander Michael, and Wang Ziqiao. Her teaching includes Topics in Autonomous Robotics, Mechanical Product Design and Development, and Advanced Design for Sustainable Future.

• Computer Graphics
• Virtual Reality
• Augmented Reality
• +9 more

Anderson Maciel is an Associate Professor at the Technical Superior Institute (Instituto Superior Técnico) of the University of Lisbon, holding a position in the Department of Computer Engineering. He is also affiliated with the Instituto de Engenharia de Sistemas e Computadores: Investigação e Desenvolvimento em Lisboa (INESC-ID). His academic work focuses on the intersection of computer graphics, virtual reality, and medical applications, with particular emphasis on surgical simulation and visualization. Dr. Maciel's research spans several key areas including virtual reality for medical training, augmented reality applications in surgery, haptic interfaces, and 3D visualization techniques. His work often bridges computer science with practical medical applications, particularly in colonoscopy simulation, radiology, and surgical training systems. He leads research projects such as XAVIER (eXplainable Artificial intelligence and VIrtual reality for Enhanced Radiology), RECOVERS (REmote COllaboration in Virtual EnviRonments for Surgery), and VR Colonography, demonstrating his focus on applying immersive technologies to healthcare challenges. His recent publications (2023-2024) reveal a strong trend toward medical applications of extended reality, with significant work in virtual colonoscopy, surgical simulation, and AI-enhanced radiology. The research shows increasing integration of eye-tracking data with AI systems for medical diagnostics, alongside continued development of physics-based simulation techniques for medical procedures. His work consistently appears in top-tier venues including Computers & Graphics, IEEE VR, and ACM SIGGRAPH. Dr. Maciel leads the Visualization, Interaction and Simulation Lab, which collaborates with institutions like UFRGS (Universidade Federal do Rio Grande do Sul) in Brazil. His research has practical applications in medical training, surgical planning, and healthcare education, with several projects translating into patentable technologies such as the intervention drive system comprising an umbilical (US Patent 11,920,722).

Srinath SridharView profile

Assistant Professor

• 3D Computer Vision
• Artificial Intelligence
• Human-Object Interaction
• +3 more

Srinath Sridhar serves as the John E. Savage Assistant Professor in the Department of Computer Science at Brown University, where he directs the Interactive 3D Vision & Learning Lab (IVL). His research program centers on 3D computer vision and artificial intelligence, specifically developing foundational methods for 4D spatiotemporal visual understanding of objects, human motion, and human-object interactions in dynamic environments. His academic foundation includes a PhD from the Max-Planck Institute (2016), an MSE from the University of Michigan (2012), and a BE from Anna University (2010). Prior to his faculty position, he completed a postdoctoral fellowship at Stanford University under Leonidas Guibas and gained industry experience at Microsoft Research and Honda Research Institute. Research interests span 3D computer vision, artificial intelligence, human-object interaction, robot perception, and deep learning. The IVL lab pioneers techniques for modeling complex 4D visual phenomena, with emphasis on real-world applicability in robotics and virtual environments. Current work integrates geometric computer vision with deep learning to solve challenges in dynamic scene understanding. Analysis of recent publications (2024-2025) reveals dominant trends in 3D vision, generative modeling, and human-robot interaction. Key themes include Gaussian splatting optimization, diffusion-based 3D generation, hand-object manipulation, and multimodal perception. The work consistently bridges theoretical advances with practical robotics applications, particularly in pose estimation, tactile sensing, and dynamic scene decomposition. His scientific recognition includes: NSF CAREER award Google Research Scholar award Best Student Paper award at WACV 2025 Best Paper Honorable Mention at Eurographics 2019 Sridhar teaches core computer vision courses including CSCI 1430 (Computer Vision) and specialized graduate seminars on 3D vision and robot perception. He maintains active research partnerships through his roles as Amazon Scholar and Visiting Faculty at the Indian Institute of Science (IISc), supported by grants from NSF and industry collaborators. The Interactive 3D Vision & Learning Lab (IVL) operates as a multidisciplinary hub for advancing 3D perception, with ongoing projects in generative 3D modeling, real-time pose tracking, and embodied AI. The lab emphasizes open collaboration and maintains strong ties with robotics research groups at Brown and industry partners.

Momen AbayazidView profile

Assistant Professor

• Robotic Image-Guided Needle Insertion
• Motion Compensation Using Machine Learning
• Soft Robotics
• +3 more

Momen Abayazid is an Assistant Professor in the Robotics and Mechatronics group (RaM) at the Faculty of Electrical Engineering, Mathematics and Computer Science (EEMCS) at the University of Twente. He holds a PhD in Surgical Robotics from the University of Twente and an M.Sc. in Biomedical Engineering from Delft University of Technology. His research focuses on robotic image-guided interventions, soft robotics, and machine learning applications in medical systems. Education: M.Sc. in Biomedical Engineering (Delft University of Technology), PhD in Surgical Robotics (University of Twente) His expertise includes haptic feedback, needle insertion control, and organ motion compensation. Recent projects involve AI-driven medical imaging, soft robotics for rehabilitation, and sensorized medical devices. Collaborations span institutions like Harvard Medical School and Brigham and Women’s Hospital. ResearchGate and Google Scholar profiles highlight his contributions to medical robotics. Scientific Awards: No explicit awards mentioned in the provided text.

Jun-Yan ZhuView profile

Assistant Professor

• Computer Vision
• Computer Graphics
• Computational Photography
• +5 more

Jun-Yan Zhu is the Michael B. Donohue Assistant Professor of Computer Science and Robotics at Carnegie Mellon University's School of Computer Science. He holds affiliated faculty roles in the Computer Science Department and Machine Learning Department. His research focuses on generative models, computer vision, graphics, and computational photography. Education: Ph.D., UC Berkeley (2017), advised by Alexei A. Efros B.E., Tsinghua University (2012), advised by Zhuowen Tu, Shi-Min Hu, and Eric Chang Postdoc, MIT CSAIL (2017–2018), with William T. Freeman, Josh Tenenbaum, and Antonio Torralba Research Interests: Zhu's work explores the synergy between human creators and generative models. Key areas include: - Controllable Visual Synthesis : Developing algorithms for precise image/video editing and generation. - Model Customization : Enabling users to adapt models for new tasks/concepts with minimal input. - Data Attribution : Addressing ethical challenges in synthetic data usage. - 3D/Neural Rendering : Advancing techniques for 3D object synthesis and tactile integration. His lab, Generative Intelligence Lab , emphasizes human-AI collaboration and practical applications like NVIDIA Canvas and Adobe Firefly. Articles Trends: Recent work spans 3D object generation (LEGO designs), efficient diffusion models (SVDQuant), tactile-aware 3D synthesis, and ethical data attribution systems. His research balances technical innovation with user-centric design, often bridging theory and industry applications. Awards: ACM SIGGRAPH Outstanding Doctoral Dissertation (2017) CVPR Best Paper Finalist (2022), ICRA Best Paper (2024) NVIDIA GTC Best in Show (2019) for GauGAN Advising & Grants: Supervises 10+ PhD students across CMU Robotics (RI), Machine Learning (MLD), and Computer Science (CSD). Active in NSF grants and industry collaborations (Adobe, NVIDIA). His lab hosts the Generative Intelligence Lab , part of CMU Graphics Lab and Computer Vision Group.

• Interactive Graphics
• Virtual Reality
• Augmented Reality
• +5 more

Professor Kenny Mitchell is a faculty member at the School of Computing Engineering and the Built Environment at Edinburgh Napier University. With over 60 research outputs listed, he specializes in Interactive Graphics, Virtual Reality, and Augmented Reality technologies. Research Interests Mitchell's work focuses on real-time systems, motion prediction, and human-computer interaction in immersive environments. His research spans generative AI environments , 3D facial reconstruction , and light field rendering . Key themes include AI-driven animation , networked VR experiences , and haptic-visual integration . Article Trends Recent publications emphasize Transformer-based motion prediction (NeFT-Net), speech-to-VR systems (HoloJig), and low-latency avatar synchronization . His work integrates machine learning with computer graphics for applications in telepresence dance and emotionally intelligent avatars . Projects CAROUSEL+ : £929,077 funded by European Commission (2021-2024) for telepresent dance systems DISTRO : £243,804 European Commission grant for 3D graphics training (2015-2018)