جست‌وجوی استاد و پژوهشگر

Greg Slabaughمشاهده پروفایل

استاد

• Computer Vision
• Deep Learning
• Computational Photography
• +۴ مورد دیگر

Professor Greg Slabaugh is the Director of the Digital Environment Research Institute (DERI) at Queen Mary University of London and holds a Professorship in Computer Vision and AI. He earned a PhD in Electrical Engineering from Georgia Institute of Technology, focusing on 3D shape reconstruction from 2D images. Prior academic roles include six years at City, University of London, where he taught computer vision, graphics, and programming while leading research grants funded by the EU Commission, EPSRC, and Innovate UK. Industrial experience includes roles at Huawei (Chief Scientist in Computer Vision), Medicsight (medical imaging for cancer detection), and Siemens (medical image computing). His research interests span computer vision, deep learning, computational photography, and medical image computing. Key achievements include 36 granted patents and over 150 publications. Awards include a 2017 Research Student Supervision Award and a 2016 Teaching Award. He also serves as the Alan Turing Institute's Turing (Academic) Liaison for Queen Mary. Current research projects include collaborations on digital twins for healthcare, AI-driven cardiac modelling, and multimodal AI applications. His work bridges academia and industry, emphasizing practical applications in health tech and imaging.

Simon Hadfieldمشاهده پروفایل

دانشیار

• Computer Vision
• Robotics
• Machine Learning
• +۳ مورد دیگر

Dr Simon Hadfield is an Associate Professor (Reader) in Robot Vision and Autonomous Systems at the University of Surrey, affiliated with the Centre for Vision, Speech and Signal Processing (CVSSP) within the School of Computer Science and Electronic Engineering. His research focuses on advancing computer vision and machine learning techniques for real-world applications, particularly in robotics. He holds a PhD and certifications such as FHEA (Fellow of the Higher Education Academy) and AUS (Advanced University Skills). Research Interests: - Effective exploitation of novel visual sensors - Practical application of computer vision to robotics - Efficient dynamic reconstruction techniques - Real-time robotics applications - Sensor fusion and calibration systems Recent projects include the NIMROD initiative exploring analogue visual sensors and contributions to multimillion-pound research efforts in sustainable packaging and agricultural robotics. His work emphasizes bridging the gap between lab-based techniques and real-world deployment, with publications in top-tier conferences and journals. Notable achievements include developing paradigms for low-complexity 3D reconstruction and proposing methods for depth estimation and localization. His research has been funded by grants such as a £1m award for robotic applications in farming. Collaborations and lab affiliations include CVSSP, where he leads projects at the intersection of vision, robotics, and autonomous systems. Future work continues to focus on scalable vision techniques and ethical AI practices in representation learning.

John Keyserمشاهده پروفایل

استاد

• Computer Science
• Graphics and visualization
• Physically-based simulation
• +۵ مورد دیگر

John Keyser is a Professor in the Department of Computer Science & Engineering at Texas A&M University, serving as Graduate Advisor. He holds a Ph.D. from the University of North Carolina at Chapel Hill and multiple B.S. degrees from Abilene Christian University. His research focuses on geometric computing, physically-based simulation, graphics, and modeling, with notable contributions to 3D visualization and computational geometry. Keyser's educational background includes advanced degrees in Computer Science, Applied Mathematics, and Engineering Physics. He has received prestigious awards such as the William Keeler Faculty Fellowship and teaching accolades from the Association of Former Students and Tenneco. His research interests span robust geometric modeling, physically-based simulation, brain networks, and graphics. Keyser's work bridges theoretical foundations with applied systems, including innovations in particle-based fluids, mesh rendering, and filament tracking in microscopy. Awards: William Keeler Faculty Fellow (2009-2010), Teaching Excellence Awards (2007), Montague Scholar (2003-2004). Advising: Graduate Advisor role with expertise in guiding students through complex computational projects. Keyser collaborates on advanced imaging techniques like the Knife-Edge Scanning Microscope (KESM) for brain tissue analysis and contributes to GPU-accelerated algorithms for real-time simulations. His research trends emphasize interdisciplinary applications of geometric computing in both academic and industrial contexts.

Pierre Poulinمشاهده پروفایل

استاد

• Computer Graphics
• Realism
• Image Synthesis
• +۶ مورد دیگر

Pierre Poulin is a Full Professor in the Department of Computer Science and Operations Research at the Université de Montréal. He leads the LIGUM laboratory and has held roles such as Department Chair (2017–2021) and PREDOC responsible (2023). His research focuses on computer graphics, realism, and image synthesis, with expertise in global illumination, procedural modeling, and real-time rendering. Poulin holds a Ph.D. from the University of British Columbia (1993), M.Sc. from the University of Toronto (1989), and B.Sc. from Université Laval (1986). His research spans natural phenomena simulation, fluid dynamics, and interactive visualization. Notable awards include the CHCCS Achievement Award (2021) and Fellow of Eurographics France (2022). He has supervised over 50 students, contributing to advancements in rendering algorithms and software visualization. Key grants include funding from CRSNG and FRQNT for projects on procedural scene creation and fluid simulation. His work bridges academia and industry, with collaborations in animation, visualization, and software engineering.

• Computer Vision
• Medical Imaging
• Generative Models
• +۴ مورد دیگر

Guha Balakrishnan is an Assistant Professor in the Electrical and Computer Engineering (ECE) department at Rice University, affiliated with the Digital Health Initiative. His research focuses on computer vision, medical imaging, and algorithmic fairness. He holds a BS from the University of Michigan, and MS and PhD from MIT's CSAIL, followed by a postdoc at MIT and industry experience at Amazon Web Services. Education: BS in Computer Science Engineering & Computer Engineering, University of Michigan (2011) MS in EECS, MIT (2013) PhD in EECS, MIT (2018) Postdoc: MIT (2018-2020) Applied Scientist: Amazon Web Services (2020-2021) Research Interests: His work spans generative models for visual data, medical applications (e.g., CT reconstruction, vital sign measurement), geospatial imaging, and ethical AI systems. He emphasizes fairness, accountability, and responsible deployment of vision systems. Recent projects include ALPINE (PyTorch library for implicit neural representations) and the EMACS workshop at CVPR 2025. Industry Impact: Prior experience at AWS focused on fairness in AI systems. Active in developing tools like Voxelmorph for medical image registration and frameworks like GELDA for dataset bias analysis. Labs & Teams: Leads efforts in Rice's Digital Health Initiative, focusing on low-cost medical AI solutions and cross-disciplinary collaborations.

Ningtao Maoمشاهده پروفایل

استاد

• Technical textiles
• High performance textiles
• Protective clothing
• +۷ مورد دیگر

Professor Ningtao Mao is a leading academic in Fibre and Textile Technology at the University of Leeds' School of Design, part of the Faculty of Arts, Humanities and Cultures. He holds a Personal Chair and serves as Director of Research and Innovation. His expertise spans technical textiles, protective clothing, and sustainable materials engineering. Educated at Northwest Institute of Textile Science and Technology (China) for BSc and MSc, he earned his PhD from the University of Leeds in 2001. His career includes roles at Heriot-Watt University before joining Leeds in 2003 as a Research Fellow, progressing to Lecturer (2008), Senior Lecturer (2010), and full Professor (2019). Research focuses on functional fabrics, including tactile property digitization, fluid dynamics in fibrous materials, and photocatalytic composites. Key projects include the Intelligent Simulation Tool for Fabric Tactile Properties and Smart Textiles for Healthy Aging . He collaborates with industry (e.g., Rheon Lab KTP) and publishes widely in journals like Composite Part B and ACS Sustainable Chemistry & Engineering . Teaching includes MSc Textile Sustainability and Innovation, MA Fashion Enterprises, and MA Global Fashion Management programmes. Current advisees include Qinyuan Li, Molly Talbot, Sophie Fields, and Abigail Tranter. He leads teams exploring sustainable textiles, nanocomposite coatings, and life cycle assessment methodologies. Awards and recognitions are unspecified in the provided text, though his prolific publication record and academic promotions reflect his impact. His labs focus on material characterization, digital textile innovation, and environmental applications.

Konstantinos Daniilidisمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• 3D Perception
• +۷ مورد دیگر

Konstantinos Daniilidis is the Ruth Yalom Stone Professor at the Department of Computer and Information Science, University of Pennsylvania, within the School of Engineering and Applied Science. He holds an adjunct position at Archimedes, Athena Research Center, Greece. His research focuses on computer vision, robotics, and geometric methods in AI, with a strong emphasis on 3D perception, event-based vision, and neural networks for motion analysis. Education : - PhD in Computer Science, University of Karlsruhe (1992), advised by Hans-Hellmut Nagel. - Diploma (Master's equivalent) in Electrical Engineering, National Technical University of Athens (1986). Research Interests : Daniilidis explores equivariant neural networks for structure from motion and robotics, event-based vision systems for low-latency perception, and 3D human motion capture using monocular and multi-sensor approaches. His work integrates geometric priors with deep learning to address challenges in SLAM, object pose estimation, and autonomous navigation. He also investigates robotic systems for tasks like object catching and fluid dynamics modeling, applying uncertainty-aware methods for robust decision-making. Articles Trends : Recent publications highlight advancements in event camera processing (e.g., EV-TTC, EqNIO), equivariant architectures for shape and motion analysis (SE(3)-Equivariant Networks), and multi-agent robotics with distributed perception systems. Collaborations with institutions such as ETH Zurich and Boston University reinforce his contributions to scalable and geometrically grounded AI solutions. Advising & Grants : He advises over 30 PhD students and postdocs, many now faculty or industry leaders. His grants include NSF awards (NCS-FO 2124355, CPS 2038873), ARL DCIST, and ONR funding, focusing on robotics, vision, and AI. His work often bridges theoretical insights (e.g., matrix permanent for localization) with practical robotic systems like the Tiercel drone. Labs & Teams : Affiliated with the GRASP Laboratory at Penn, a premier robotics & vision research center. Collaborates widely, including with the Robotics Lab at ETH Zurich and researchers at the University of Coimbra. His group develops open-source tools like EV-FlowNet and EventGAN for event-based vision.

Camillo Jose Taylorمشاهده پروفایل

استاد

• Computer Vision
• Robotics
• 3D Reconstruction
• +۳ مورد دیگر

Camillo Jose Taylor is the Raymond S. Markowitz President’s Distinguished Professor in the Department of Computer and Information Science at the University of Pennsylvania. He also serves as an Associate Dean. His research focuses on computer vision, robotics, and 3D reconstruction, with contributions to autonomous systems, SLAM, and multi-agent coordination. Education: A.B. in Electrical, Computer & Systems Engineering (Harvard, 1988), M.S. and Ph.D. in Computer Science (Yale, 1990/1994). Research interests include vision-guided robotics, structure from motion, and smart camera networks. Notable projects include GRASP Laboratory’s work on modular robots, self-localizing camera networks, and air-ground robotic systems. Awards include the NSF CAREER Award (1998), Lindback Teaching Award (2012), and best paper recognitions in computer vision workshops. Labs/Teams: GRASP Laboratory, MARS Project, and collaborations with the Penn Robotics Group.

Michael Yipمشاهده پروفایل

دانشیار

• Robotics
• Medical Robotics
• Surgical Robotics
• +۶ مورد دیگر

Michael Yip is an Associate Professor of Electrical and Computer Engineering at UC San Diego and Director of the Advanced Robotics and Controls Laboratory (ARCLab). He leads research in surgical robotics, biomimetic design, and robot learning. His work focuses on autonomous systems for medical applications, including robotic surgery and continuum robots. Dr. Yip holds affiliate faculty positions in Computer Science and Engineering, Mechanical and Aerospace Engineering, and the Contextual Robotics Institute. Education: Ph.D. in Bioengineering (Stanford University), M.Sc. in Electrical Engineering (University of British Columbia), B.Sc. in Mechatronics Engineering (University of Waterloo). Previous roles include visiting positions at Amazon Robotics and Disney Research. Research interests span surgical robotics, reinforcement learning, and robot manipulation in dynamic environments. His lab develops systems for minimally invasive surgery and medical interventions. Notable contributions include the CRANE tele-surgical system and the ARCSnake reconfigurable robot. Key awards include the NSF CAREER Award, NIH Trailblazer Award, and election to the National Academy of Inventors. He has authored over 150 peer-reviewed publications and co-founded multiple startups. His work bridges robotics, AI, and biomedical engineering, with applications in telesurgery and autonomous systems. Lab initiatives include the Medical Robotics Collaboratory and contributions to the US Congressional Robotics Roadmap. Teaching focuses on robotics control, reinforcement learning, and hands-on prototyping. Active service roles include editorial positions for IEEE Robotics and Automation Letters and leadership in robotics conferences.

Andrei Jalbaمشاهده پروفایل

استادیار

• Computer Graphics
• Medical Imaging
• Visualization Algorithms
• +۳ مورد دیگر

Andrei Jalba is an Assistant Professor at Eindhoven University of Technology (TU/e), affiliated with the Department of Mathematics and Computer Science. His research focuses on visualization algorithms, medical imaging, computational fluid dynamics, and real-time graphics. He leads groups in Visualization and Visual Analytics, contributing to interdisciplinary projects like physics-based fluid simulations and MRI data processing. Jalba teaches courses such as Simulation in Computer Graphics and Computer Graphics . His work bridges theoretical advancements with practical applications in healthcare and interactive systems. Research Interests: Computer Graphics, Medical Imaging, Data Assimilation, Scientific Visualization. Key Projects: Physics-based MRI denoising, volumetric light transport simulation, and collision response algorithms for deformable models. His publications emphasize efficient algorithms for real-time applications and medical data analysis, with notable contributions to ACM Transactions on Graphics and Computer Graphics Forum. No specific awards or grants are explicitly listed, but his work is funded by initiatives like the ERC TouchDesign project (2019).

Junpeng Wangمشاهده پروفایل

پژوهشگر ارشد

• lightweight structural design
• structural optimization
• scientific visualization
• +۵ مورد دیگر

Dr. Junpeng Wang is a Postdoctoral Researcher (since June 2023) in the Chair of Computer Graphics and Visualization at the Technical University of Munich, working under Prof. Rüdiger Westermann. Previously, he completed his PhD at the same institution from November 2018 to June 2023. His research focuses on lightweight structural design and optimization with geometry-based approaches, as well as scientific visualization of tensor and mesh data. Wang's research interests span lightweight structural design , structural optimization , and scientific visualization . His work integrates computational mechanics with computer graphics to develop novel methods for stress analysis, lattice structure optimization, and 3D data visualization. His research has practical applications in mechanical engineering, additive manufacturing, and scientific data analysis. His publication portfolio shows a strong trend toward integrating machine learning with traditional computational mechanics methods, particularly in the areas of 3D Gaussian Splatting and neural data structures. Wang has developed the 3D-TSV (3D Trajectory-based Stress Visualizer), a significant tool for exploring principal stress directions in 3D solids under load, which has been published in Advances in Engineering Software (2022). Wang serves as a reviewer for prestigious journals including IEEE Transactions on Visualization and Computer Graphics (TVCG), Computer Methods in Applied Mechanics and Engineering (CMAME), Journal of Mechanical Design (JMD), Optics Express (OPTE), Computer-Aided Geometric Design (CAG), and Shape Modeling International Conference (SPM[C]). His collaborative work primarily involves Prof. Rüdiger Westermann at TUM and Jun Wu at other institutions, demonstrating strong interdisciplinary connections between computer graphics and mechanical engineering research groups.

Aysegul Dundarمشاهده پروفایل

استادیار

• Deep Learning
• Computer Vision
• Generative Models
• +۳ مورد دیگر

Aysegul Dundar is an Assistant Professor of Computer Science at Bilkent University, Ankara, Turkey. She previously served as a senior research scientist at NVIDIA in Santa Clara, USA. Her research focuses on deep learning algorithms for computer vision, particularly generative models, 3D reconstruction, and image editing. She leads the Generative Deep Learning Research Lab at Bilkent. Education: Ph.D. in Electrical and Computer Engineering, Purdue University (2016), supervised by Eugenio Culurciello. B.Sc. in Electrical and Electronics Engineering, Bogazici University, Turkey (2011). Research Interests: Her work emphasizes generative deep learning, with applications in 3D head stylization, image editing via diffusion models, and neural network architectures for vision systems. She explores disentangled latent spaces, GAN inversion, and robust instance segmentation. Awards & Funding: 2024: Young Scientist Award (BAGEP), EuroHPC AI Award. 2021: TÜBİTAK 3501 Grant. 2020: Marie Skłodowska-Curie Fellowship. 2018: 1st Place in CVPR Domain Adaptation Challenge. Teaching & Labs: Teaches CS 490 (Research in Computer Engineering/Science). Leads projects on image synthesis, with a focus on selective student recruitment for lab contributions. Prioritizes undergraduates actively engaged in lab activities.

• Computer Graphics
• Scientific Visualization
• Crowd Simulation
• +۵ مورد دیگر

Ugur Gudukbay is a Professor in the Department of Computer Science at Bilkent University. He specializes in computer graphics, scientific visualization, and crowd simulation, with extensive contributions to video databases and augmented reality systems. His research explores topics including tetrahedral mesh rendering, human motion animation, and content-based multimedia retrieval. Education Background: Not explicitly stated in the provided text. Research Interests: Real-time rendering techniques Virtual environment modeling Machine learning for video analysis Privacy-preserving data processing Human-computer interaction Advising & Collaboration: Supervised 35+ graduate students since 1998 Co-supervisor in projects involving video databases, medical visualization, and urban crowd simulation Notable collaborations with Dr. Özgür Ulusoy and Dr. Bülent Özgüç Labs/Teams: No specific lab names mentioned, but active in computer graphics and multimedia research groups at Bilkent.

Yifan (Evan) Pengمشاهده پروفایل

استادیار

• Computational Optics
• Imager and Sensor Technology
• Holography
• +۵ مورد دیگر

Yifan (Evan) Peng is an Assistant Professor at the University of Hong Kong, jointly affiliated with the Departments of Electrical & Electronic Engineering and Computer Science. He leads the WeLight Lab, focusing on interdisciplinary research at the intersection of Optics, Graphics, Vision, and Artificial Intelligence. His work emphasizes computational imaging systems, holography, and human-centered visual technologies. Education: PhD in Computer Science from the Imager Lab, University of British Columbia Postdoctoral Research Scholar at Stanford University's Computational Imaging Lab Visiting Student Researcher at KAUST's Visual Computing Center and Stanford MS & BS in Optical Science and Engineering from Zhejiang University Research Interests: His research explores computational optics, holographic displays, VR/AR/MR systems, and low-level vision techniques. Recent efforts include developing snapshot hyperspectral imaging systems, lighting-robust machine vision, and neural rendering frameworks for dynamic scenes. He investigates hardware-software co-design in imaging systems and explores applications in medical imaging and mixed reality. Publications: Recent work focuses on advancing holographic display technologies, neural rendering, and hybrid optical-computational imaging systems. Key contributions include metasurface-based AR displays, speckle reduction techniques, and learned optical systems for hyperspectral imaging. His research bridges physical optics with digital algorithms to achieve high-quality imaging and display solutions. Grants & Advising: Hosts visiting scholars and collaborates with industry partners like Ford, Sony, and Intel. Openings exist for PhD students, postdocs, and research assistants in computational imaging and optics. Labs & Teams: Leads the WeLight Lab at HKU, collaborating with global institutions on projects like neural holography and diffractive optics. Active in conferences like SIGGRAPH, CVPR, and ISMAR as program committee member.

• Computer Animation
• Machine Learning
• Virtual Reality
• +۶ مورد دیگر

Professor Xiaosong Yang serves as Professor and Deputy Head of Department at the National Centre for Computer Animation, Bournemouth University. With over 30 years of experience in research, education, and professional practice, he leads the MSc AIM program and has established himself as a prominent figure in computer animation and AI applications. His work bridges academic research with industry applications through collaborations with organizations including Disney Research and Double Negative. Professor Yang's research spans computer animation, machine learning, data mining, digital health, virtual reality, augmented reality, medical visualization, and surgery simulation. His innovative work in muscle-based animation has received international recognition from prestigious outlets such as NewScientist and MIT Technology Review. He has developed novel techniques that have been successfully integrated into animation production pipelines, demonstrating practical applications of his research. His publication record includes over 140 peer-reviewed papers in prestigious journals and conferences, with recent work focusing on AI-driven animation techniques, medical visualization, and human-computer interaction. The research trends show a consistent progression from foundational computer animation techniques toward increasingly sophisticated AI applications in both entertainment and healthcare domains. Recognized Research Supervisor from UK Council for Graduate Education Professor Yang has supervised over 30 PhD students and numerous postdocs, research assistants, and international visiting scholars. His research impact is further evidenced by securing over 35 research grants from major funding bodies including the European Commission, Arts and Humanities Research Council, British Academy, Leverhulme, British Council, Newton Fund, Innovate UK, Wessex AHSN, and Higher Education Innovation Fund. He serves on the Peer Review College of the Arts and Humanities Research Council (AHRC) UK and the Computer Science Evaluation Group of the Natural Science and Engineering Research Council of Canada (NSERC). He actively contributes to the academic community as a program committee member for international conferences (SIGGRAPH Asia, CGI, CASA), conference program chair (CGI2012, CASA2020/2022), and reviewer for top journals (TVCG, ACM ToG, C&G) and conferences (SIGGRAPH, Eurographics, ISMAR).