Find Academic Supervisors

• Geometry Processing
• Computer Graphics
• Shape Analysis
• +5 more

Niloy J. Mitra is a Professor of Geometry Processing at the Department of Computer Science, University College London (UCL). He holds a MS and PhD in Electrical Engineering from Stanford University, with postdoctoral research at Technical University Vienna. His research focuses on shape analysis, geometry processing, computational fabrication, and neural rendering. Notable contributions include work on structure-aware 3D representations and data-driven methods for scene understanding. Mitra has received prestigious awards such as the ACM Siggraph Significant New Researcher Award (2013) and the Eurographics Outstanding Technical Contributions Award (2019). He leads the SmartGeometryProcessing research group and has authored over 150 papers in top venues like SIGGRAPH and CVPR. His service roles include chairing conferences like Symposium on Geometry Processing and serving on editorial boards for journals like ACM Transactions on Graphics. Mitra's work bridges computer graphics, machine learning, and geometry, with applications in 3D modeling, animation, and generative AI. Education: PhD in Electrical Engineering (Stanford University, 2006), MS in Electrical Engineering (Stanford University, 2003), B.Tech in Computer Science & Engineering (IIT Kharagpur, 1999). Research interests include neural rendering, diffusion models for 3D generation, and procedural modeling. His lab develops tools like ShapeLib and Diff3F for 3D content creation. Awards also include the ERC Starting Grant (2013) and Eurographics Fellowship (2021). Mitra's hobbies include rock climbing, cooking, and reading, with a focus on technical and fiction literature.

Felix WechslerView profile

Researcher

• Computational Optics
• 3D Printing
• Optical Propagation
• +3 more

Felix Wechsler is a Doctoral Assistant and PhD Student in Photonics at the École Polytechnique Fédérale de Lausanne (EPFL), working in the Laboratory of Applied Photonics Devices (LAPD) under Prof. Christophe Moser. He is also a PhD Student Representative in the EDPO-GE group within the Doctoral Program in Photonics. His primary affiliation is with the School of Engineering (STI) and the Department of Microengineering (IEM) at EPFL. Education: Felix holds a Bachelor of Science in Informatics and Physics from the Technische Universität München (TUM), and a Master of Science in Photonics from Friedrich Schiller University Jena (FSU Jena). Research Interests: His research focuses on computational tools for tomographic 3D printing, optical wave propagation, and microscopy. He develops innovative methods using Julia programming, including packages like SwissVAMyKnife.jl and Dr.TVAM. His work aims to improve volumetric additive manufacturing through advanced optical techniques and algorithmic optimization. Publications: Recent work includes scalable optical propagation methods, MEMS-based light modulators for holographic manufacturing, and inverse rendering frameworks for tomographic additive processes. These contributions highlight advancements in both theoretical and applied aspects of optical engineering and manufacturing. Awards: No scientific awards have been explicitly mentioned in the provided information. Advising & Collaborations: Felix has not yet advised students, but his research is supported through collaborations and institutional funding at EPFL. His involvement in developing open-source tools reflects his commitment to reproducibility and community-driven science. Labs & Teams: He is part of the LAPD laboratory and collaborates with the Realistic Graphics Lab (RGL) at EPFL, as evidenced by his reposts on Bluesky.

Arnoud VisserView profile

Senior Lecturer

• Artificial Intelligence
• Robotics
• Multi-Agent Systems
• +3 more

Dr. Arnoud Visser is a Senior Lecturer at the Informatics Institute within the Faculty of Science at the University of Amsterdam . He holds a PhD in Computer Science (2007) and an MSc in Experimental Physics (1987). His research focuses on artificial intelligence and robotics , particularly cooperative robot teams in real-world environments. He has led projects like Meaningful Control of Autonomous Systems (2020) and developed simulation frameworks for RoboCup Rescue challenges. His 15 most recent publications (2022-2025) span topics including generative AI for military scene understanding , GAN-based nighttime re-identification , soft actor-critic locomotion , and ROS2 simulation environments . These works integrate machine learning with robot navigation and multi-agent coordination . Scientific Awards include: 1th Prize in RoboCup Rescue Simulation League (2018, 2014, 2012) Best Demo Award (Benelux Conference on AI 2016) IEEE RAS Most Active Technical Committee Award (2018) USARsim Development Prize (2010) As a thesis committee member for 27 PhD and 68 Master's theses (2000-2025), he has mentored students in areas like spiking neural networks , soft robotics , and autonomous navigation . He has also served on program committees for major robotics conferences including ICRA, IROS, and RoboCup Symposia (2011-2025).

Christopher MetzlerView profile

Assistant Professor

• Computer Vision and Machine Perception
• AI and Robotics
• Machine Learning and Data Science
• +2 more

Christopher Metzler is an Assistant Professor in the Department of Computer Science at the University of Maryland (UMD), with appointments in the University of Maryland Institute for Advanced Computer Studies (UMIACS) and a courtesy appointment in the Electrical and Computer Engineering Department. He leads the UMD Intelligent Sensing Laboratory, focusing on computational imaging, machine learning, and wireless communications. His research develops novel systems and algorithms for imaging through scattering media, multimodal sensor fusion, and self-supervised AI techniques. Education: PhD in Electrical and Computer Engineering (Rice University, 2019), MSEE (2014), BSEE (2013). Postdoctoral Fellowship: Stanford Computational Imaging Lab (2020). Awards: AFOSR Young Investigator Program (2022), NSF CAREER (2023), ARO Early Career Award (2024), and multiple fellowships (NSF GRFP, NDSEG). Research interests include computational imaging, machine learning, statistical signal processing, and AI-driven sensor fusion. His work addresses challenges in non-line-of-sight imaging, turbulence mitigation, and hardware-aware algorithms. He advises 10 PhD students and collaborates on projects funded by the Air Force, NSF, and other agencies. Key contributions include neural wavefront shaping, adversarial sensing frameworks, and high-resolution non-line-of-sight imaging. His lab develops open-source software and datasets, such as the Transmission Matrix Dataset and learned compressive sensing tools.

• AI and Robotics
• IoT and Wearables Technology
• Computer Vision and Machine Perception

Shuvra Bhattacharyya is an Affiliate Professor at the University of Maryland, holding appointments in the Department of Computer Science (CS), the University of Maryland Institute for Advanced Computer Studies (UMIACS), and the Department of Electrical and Computer Engineering (ECE). His research focuses on AI and Robotics, IoT and Wearables Technology, and Computer Vision and Machine Perception, with a strong emphasis on embedded systems, real-time processing, and interdisciplinary applications. Key research interests include optimizing neural networks for resource-constrained environments, developing gait recognition systems using pose estimation, and exploring synthetic data applications in aerial surveillance and VR content creation. He has contributed to frameworks for adaptive digital predistortion systems, dynamic data-driven hyperspectral video processing, and collaborative UAV-based human detection benchmarks like Archangel. His work often bridges theoretical computer science with practical engineering challenges, such as scheduling algorithms for real-time systems, energy-efficient IoT deployments, and interpretable AI models for criminal justice applications. Bhattacharyya collaborates across disciplines to address challenges in edge computing, wearable technology, and sustainable industrial processes. Notable projects include the HoloCamera system for cinematic VR capture and the Flydeling framework for CNN acceleration on heterogeneous platforms. His research also addresses fairness in predictive models and dynamic memory optimization techniques for dataflow-based applications.

Jerry TessendorfView profile

Professor

• Computer Graphics
• Visual Computing
• Fluid Dynamics Simulation
• +6 more

Professor Jerry Tessendorf is a Professor of Visual Computing at Clemson University's School of Computing within the College of Engineering, Computing and Applied Sciences. He also holds the position of Faculty Fellow of the Hagler Institute for Advanced Study at Texas A&M University. His work bridges computer graphics, physics-based simulation, and visual effects with applications in film production and scientific visualization. Professor Tessendorf's research focuses on physically based simulation of natural phenomena , particularly ocean and fluid dynamics, volume rendering, and radiative transfer. His work spans theoretical foundations to practical applications in visual effects. He has developed influential algorithms including the iWave water surface simulation technique, Gilligan (a maritime digital twin framework), and advanced volume rendering methods. His research combines mathematical rigor with practical implementation for both scientific and entertainment applications. Tessendorf's publication record demonstrates consistent innovation across decades, with recent work focusing on maritime digital twins, advanced ocean rendering techniques, and path integral methods for radiative transfer. His research shows a clear trajectory from fundamental theory to practical applications in visual effects and scientific visualization. Awards and Recognition: AMPAS Technical Achievement Award 2008 (Oscar for technical achievement) for developing fluid dynamics tools at Rhythm and Hues Studios, used to create realistic animation of liquids and gases in film production Co-chair of the Symposium on Computer Animation 2008 at Trinity College Dublin Professor Tessendorf teaches advanced courses in computer graphics, including CPSC 4040/6040 Computer Graphics Images, CPSC 4190/6190 Introduction to Physically Based Modeling and Animation, and CPSC 8190 Physically Based Effects (focusing on Volume Modeling and Rendering). His educational approach integrates theoretical foundations with practical implementation through projects like the Fitz Film initiative, which involves students in all stages of digital content creation. His lab work centers around the Gilligan project , a prototype framework for simulating and rendering maritime environments with capabilities including ocean with normal mapping and whitecaps, wakes with whitecaps, hydrostatic boat buoyancy dynamics, nonlinear free surface dynamics, and atmospheric optics. This work represents a comprehensive digital twin approach to maritime visualization with applications in both entertainment and scientific domains.

Marc OlanoView profile

Associate Professor

• Computer Graphics
• Real-Time Systems
• Game Development
• +5 more

Dr. Marc Olano is an Associate Professor of Computer Science and Electrical Engineering at the University of Maryland, Baltimore County (UMBC). He specializes in real-time 3D graphics, non-graphics applications of graphics hardware, and game development. As director of UMBC’s Game Development Track and 3D photogrammetric scanning facility, he focuses on advancing interactive technologies and environmental monitoring systems like Ecosynth. His research collaborations include work with gaming companies such as Firaxis, Epic Games, and Activision, as well as contributions to virtual reality (VR) applications in healthcare and scientific visualization. Dr. Olano holds a Ph.D. in Computer Science from the University of North Carolina and a B.S. in Electrical Engineering from the University of Illinois. Education: Ph.D., Computer Science, UNC (1998); B.S., Electrical Engineering, UIUC (1990). Research Interests: Computer graphics, GPU acceleration, VR, game development, and ecological 3D scanning. Key Roles: Director of Game Development Track, Editor-in-Chief of the Journal of Computer Graphics Techniques. Olano’s work bridges academia and industry, emphasizing practical applications like texture compression for games, VR-based rehabilitation systems, and UAV-driven environmental analysis. His research often leverages GPU computing to solve real-world problems, from optimizing rendering algorithms to enabling large-scale ecological data collection through Ecosynth. Publications span VR systems, subsurface scattering techniques, and GPU algorithms, reflecting his commitment to advancing interactive and computational graphics. His teaching and mentorship in the Game Development Track prepare students for roles in game design, while his lab facilities provide hands-on experience with cutting-edge technologies.

Shiaofen FangView profile

Professor

• Data Visualization
• Visual Analytics
• Interactive Machine Learning
• +2 more

Shiaofen Fang is Professor of Computer Science and Associate Dean for Research at Indiana University's Luddy School of Informatics, Computing, and Engineering. He holds a Ph.D. in Computer Science from the University of Utah and M.S./B.S. degrees in Mathematics from Zhejiang University. His research focuses on data visualization, medical image analysis, and interactive machine learning. Research interests span: Data visualization including healthcare analytics and neuroimaging tools Medical image analysis for FASD diagnosis and brain connectomics Interactive AI for explainable machine learning systems Volume graphics for 3D modeling and rendering Publications demonstrate strong focus on AI applications in healthcare and education, visualization techniques for biomedical data, and geometric modeling. Recent works increasingly address ethical AI and bias mitigation. Research funded by NSF, NIH, DoD, and NIJ. Collaborates extensively with biomedical researchers and healthcare institutions. Leads projects on neuroimaging visualization, healthcare data exploration, and 3D facial analysis.

• Computer Science
• Medical Imaging
• Virtual Reality
• +4 more

Dr. Victor Asavei is a Lecturer in the Faculty of Automatic Control and Computers at the Politehnica University of Bucharest. His research spans interdisciplinary areas including virtual reality, medical imaging, and high-performance computing. He is affiliated with the 3DUPB Lab, focusing on 3D virtual environments and GPU optimizations for massive multiplayer online systems. His work integrates computer graphics, signal processing, and network engineering, with notable contributions to 3D Smith chart theory, medical image processing for orthopedic applications, and real-time 3D reconstruction techniques. Collaborations include projects on augmented reality in surgery, distributed file systems, and immersive virtual rehabilitation systems. Key research directions include: Virtual Reality (VR) and Augmented Reality (AR) applications in healthcare and education GPU-accelerated algorithms for medical imaging and deferred rendering RF/microwave engineering with focus on nonlinear circuits and impedance analysis Software-Defined Networking (SDN) architectures for data centers Notable publications highlight advancements in 3D Smith chart visualization, real-time depth map processing on mobile devices, and scalable server architectures for 3D virtual spaces. He actively contributes to conferences such as IEEE Microwave Symposium and RoEduNet. Research infrastructure includes collaborations with medical institutions for computer-aided surgery tools and partnerships with industry on nearshore software development methodologies.

• Electrical & Electronics Engineering
• Radar Signal Processing
• Waveform Design
• +3 more

Dr. Mohammad ALAEE is a Researcher at the University of Luxembourg's Interdisciplinary Centre for Security, Reliability and Trust (SnT), specifically within the SPARC department. His research focuses on radar signal processing, waveform design, and optimization theory, with applications in automotive, medical, and communication systems. He has conducted research stays in Italy and speaks French and English fluently. His work emphasizes the development of advanced radar technologies, including MIMO radar systems, interference mitigation techniques, and waveform optimization for spectral efficiency. He has contributed to projects such as contactless vital sign monitoring using radar, automotive radar coexistence with communications, and 4D imaging radar for high-resolution applications. His publications highlight trends in radar-communication integration, waveform design for medical and automotive systems, and adaptive signal processing techniques. He has also explored hardware prototyping and simulation tools for radar systems, demonstrating practical implementations of his theoretical contributions. Dr. ALAEE's research bridges theoretical advancements with real-world applications, addressing challenges in modern radar systems' performance and integration. While no specific awards or grants are listed, his extensive publication record underscores his expertise in radar engineering and signal processing.

Sarah Adel BargalView profile

Assistant Professor

• Computer Vision
• Machine Learning
• Explainable AI
• +1 more

Sarah Adel Bargal is an Assistant Professor in the Department of Computer Science at Georgetown University. Her research focuses on computer vision and machine learning, particularly in the areas of explainable AI and neural-backed decision trees. Education: She holds a PhD in Computer Science from Boston University (2018), an MSc in Computer Science from The American University in Cairo, and a BSc in Computer Science from Kuwait University. Research interests include developing transparent AI systems and creating methods for neural network interpretability. Her work bridges theoretical computer science with practical applications in visual recognition systems. Her publications demonstrate a consistent focus on computer vision applications in healthcare, education, and security. Recent trends show increasing work on generative models, medical imaging, and educational technology applications. Awards include: Provost's Distinguished Faculty Fellow IBM Ph.D. Fellow Hariri Graduate Fellow Outstanding Teaching Fellow Award Top-three finalists for EmotiW 2016 Competition Social Entrepreneurship Award Hariri Award for Transformative Computational Science Research Office of Technology Development Award Dr. Bargal leads the Image and Video Computing Group and has directed AI education initiatives including Boston University's AI4ALL program. Her lab focuses on developing explainable computer vision systems for real-world applications.

Konstantinos DerpanisView profile

Associate Professor

• Computer Vision
• Artificial Intelligence
• Data Science
• +5 more

Konstantinos Derpanis is an Associate Professor in the Department of Electrical Engineering & Computer Science at York University. He holds a BSc (Honours) in Computer Science from the University of Toronto (2000), an MSc and PhD in Computer Science from York University (2003, 2010). His doctoral work earned the CIPPRS Doctoral Dissertation Award 2010 Honourable Mention. Prior to York, he served as Associate Professor at Ryerson University (2012–2020) and was a postdoctoral researcher at the GRASP Laboratory, University of Pennsylvania (under Prof. Kostas Daniilidis). He currently serves as an Associate Editor for IEEE TPAMI and Area Chair for AAAI 2021, ICRA 2021, CVPR 2021, and ICCV 2021. His research focuses on computer vision with emphasis on motion analysis, human motion understanding, and applications in image processing and machine learning (including deep learning). Key interests include generative models, neural radiance fields, and vision-language systems. His work bridges theoretical advancements and practical applications in computational photography, 3D reconstruction, and AI-driven perception. Education: BSc (Honours), Computer Science, University of Toronto, 2000 MSc (Computer Science, York University, 2003, supervised by Prof. John Tsotsos & Prof. Richard Wildes) PhD (Computer Science, York University, 2010, supervised by Prof. Richard Wildes) Awards: CIPPRS Doctoral Dissertation Award 2010 Honourable Mention His recent research trends highlight contributions to neural radiance fields (NeRF), generative models, and vision-language systems. He explores techniques for robust scene representation, image/video editing via text instructions, and cross-modal retrieval. His work also addresses challenges in sensor fusion, temporal alignment, and interpretable AI. Dr. Derpanis has no listed grants or advisees in the provided texts but maintains active roles in academic service and conference organization.

Narjes PourjafarianView profile

Researcher

• Human-Computer Interaction
• Ubiquitous Computing
• Embedded Sensing Systems
• +4 more

Narjes Pourjafarian is a postdoctoral researcher at Cornell University's Hybrid Body Lab, collaborating with Dr. Cindy Kao. She holds a Ph.D. in Human-Computer Interaction from Saarland University (2023) and two M.Sc. degrees: one in Electrical Engineering from Shiraz University (Iran) and another in Computer Science from Saarland University. Her research focuses on embedded sensing systems, wearable technologies, and customizable interactive interfaces. She has pioneered novel fabrication techniques for on-skin and everyday surfaces, such as BodyStylus and Multi-Touch Skin. Education: Ph.D., Human-Computer Interaction, Saarland University, 2023 M.Sc., Computer Science, Saarland University, 201? M.Sc., Control System Engineering, Shiraz University, 201? B.Sc., Electrical Engineering, Shiraz University of Technology, 201? Research interests span digital fabrication, ubiquitous computing, and AI-driven interaction design. Her work bridges physical and digital realms through tools like Print-A-Sketch (handheld circuit printers) and RoboSketch (robotic sketching systems). She also contributed to optimization algorithms and drought prediction models early in her career. Labs/Teams: Hybrid Body Lab (Cornell), Human-Computer Interaction Lab (Saarland). Her projects emphasize democratizing fabrication and enhancing human-computer interaction through tactile and wearable systems.

Chris JoslinView profile

Professor

• Computer Graphics
• Medical Imaging
• Virtual Reality
• +5 more

Chris Joslin is a Professor at the School of Computer Science, Carleton University. His office is located in 4302 Canal Building, and he can be reached at Chris.Joslin@carleton.ca. He specializes in interdisciplinary research areas including computer graphics, medical imaging, virtual reality, computer vision, and human-computer interaction. His work bridges theoretical advancements with practical applications in animation, 3D modeling, and medical visualization. Research interests include developing novel techniques for 3D editing, medical image processing, and immersive virtual environments. Notable contributions include advancements in 3D Gaussian splatting, AI-driven MRI analysis, and robust sensor fusion for autonomous systems. His publications span from foundational studies on motion retargeting to applied work in procedural audio generation for soft-body simulations. Recent trends in his articles emphasize integration of deep learning with traditional computer vision tasks, optimization of medical imaging workflows, and enhancing accessibility in virtual reality systems. Despite prolific output, no scientific awards are explicitly mentioned in the provided texts. Advising and grant details remain unspecified, though his involvement in collaborative projects like VPARK and ISIS suggests engagement with interdisciplinary teams. His work is anchored at Carleton’s Herzberg Laboratories, a hub for advanced computational research.

• Production Systems
• Business Processes
• Supply Chain Optimization
• +4 more

George Ioannou is a Professor of Production Management and Business Processes at the Athens University of Economics and Business, where he leads the MBA International Postgraduate Program and the Center for Business Processes and ERP Systems at the Laboratory of Management Science. Previously, he served as Assistant Professor at Virginia Tech's Department of Production and Systems Engineering. His academic journey includes a B.Sc. in Mechanical Engineering from National Technical University of Athens, an M.Sc./DIC in Industrial Robotics/Production Automation from Imperial College London, and a Ph.D. in Mechanical Engineering from the University of Maryland. Current Academic Roles: Professor, Director of MBA Program, Head of ERP Systems Center Prior Academic Roles: Assistant Professor at Virginia Tech Education: B.Sc., M.Sc./DIC, Ph.D. His research focuses on integrating web-based technologies with operational research to optimize production systems, business processes, and supply chains. This spans applications in plant spatial planning, ERP systems, and cultural heritage digitization. He has secured research funding from global organizations including NSF, European Commission, and private sector leaders like Microsoft. Scientific awards include Microsoft's Excellence in Education Award and multiple teaching excellence recognitions for MBA programs. Ioannou serves on the Technical Chamber of Greece (TEE) and the editorial board of Production Planning & Control , with extensive consulting experience for public and private sector entities.