جست‌وجوی استاد و پژوهشگر

Daniel Powersمشاهده پروفایل

استاد

• Illustration
• Children's Book Illustration
• Visual Literacy
• +۲ مورد دیگر

Daniel Powers is a Professor of Illustration at the Savannah College of Art and Design (SCAD), where he has served since 2006. He holds an M.F.A. in Visual Arts from Marywood University and a B.F.A. in Art History from Ohio University. His career spans academic roles at institutions including the University of Minnesota and Albuquerque Academy, alongside leadership as Graduate Coordinator for SCAD's Illustration program since 2013. Education: M.F.A., Visual Arts, Marywood University B.F.A., Art History, Ohio University Daniel's research and creative work focus on illustration , particularly children's book illustration , nonfiction visual storytelling , and watercolor techniques . His exhibitions, such as the Small Works show at the National Watercolor Society Gallery and SILA's 50th Illustration West , highlight his expertise in visual literacy and artistic collaboration . His recent publications and presentations, including works on History of Illustration Project and talks at the Society of Children's Book Writers and Illustrators (SCBWI), demonstrate his commitment to advancing illustrated educational media . Daniel has received accolades like the Society of Illustrators Merit Award and the New Mexico Watercolor Society Fellowship . As a dedicated academic, he has contributed to labs and teams through initiatives like the Storybook Look traveling exhibition and collaborations with institutions such as the Georgia Center for the Book. His work bridges art education , cultural storytelling , and pedagogical innovation in visual arts.

Lingjie Liuمشاهده پروفایل

استادیار

• Computer Graphics
• Computer Vision
• Artificial Intelligence
• +۷ مورد دیگر

Lingjie Liu is the Aravind K. Joshi Assistant Professor in the Department of Computer and Information Science at the University of Pennsylvania, leading the Penn Computer Graphics Lab and co-chairing the GRASP Lab. Previously, he was a Lise Meitner Postdoctoral Fellow at the Max Planck Institute for Informatics, and earned his Ph.D. from the University of Hong Kong (2019). His research focuses on neural scene representations, neural rendering, human performance modeling, and 3D reconstruction, blending computer graphics, vision, and AI. He is actively recruiting PhD students in areas like neural representations, generative models, and LLM-guided graphics. Education: Ph.D. in Computer Science (University of Hong Kong, 2019); BEng in Computer Science (Huazhong University of Science and Technology, 2014). Research highlights include NeuS/NeuS2 for 3D reconstruction, DragGAN for interactive image manipulation, and Holodeck for text-driven 3D environments. He has received awards such as the IVA Best Paper Award (2021) and holds editorial roles at IEEE TVCG and program committees for SIGGRAPH/ICCV. Professional activities include organizing workshops on neural fields, generative models, and robotics. His lab emphasizes 3D/4D reconstruction, generative models, and physics-aware systems. Current students include Chen Wang (Meshy AI Fellow), Yiming Huang, and Qiao Feng. His work spans over 50 publications in top venues like SIGGRAPH, CVPR, and NeurIPS.

• Superconductivity
• Thin Film Physics
• Quantum Materials
• +۲ مورد دیگر

Attanasio Carmine is a Full Professor at the CNR Institute for SuPerconductors, Innovative Materials, and Devices. His research focuses on superconducting materials, thin film characterization, and nanoscale device applications, particularly NbRe-based systems for quantum technologies. Research Focus: Investigation of superconducting microstrips, vortex dynamics, and material interfaces for single-photon detectors and energy-efficient electronics. Recent work includes NbRe thin films and hybrid structures.

• Computer Graphics
• Computer Vision
• Image Processing
• +۱ مورد دیگر

Herb Yang is a Professor in the Faculty of Science - Computing Science at the University of Alberta. A senior member of IEEE and Associate Editor for Pattern Recognition, he has published over 80 technical papers in international journals and conference proceedings. His research covers computer graphics and computer vision, including 2D/3D shape analysis, segmentation, motion analysis, and image-based rendering. Dr. Yang's research focuses on computational methods for visual data processing across domains from medical imaging to animation. Key interests include edge detection algorithms, ultrasound image enhancement, and realistic rendering techniques.

Thomas Marrinanمشاهده پروفایل

استادیار

• Computer Graphics
• Visualization
• Human-Computer Interaction
• +۳ مورد دیگر

Thomas Marrinan is an Assistant Professor of Computer & Information Science at the University of St. Thomas, College of Arts and Sciences. His expertise spans computer graphics, visualization, human-computer interaction, and high-performance computing. He specializes in developing interactive tools for large-scale data analysis, including multi-platform visualization applications like VisAnywhere and immersive virtual reality experiences. His research focuses on bridging gaps between simulation analysis and user interaction through novel interfaces and algorithms. He has pioneered work in 3D Gaussian splatting, real-time image compression, and collaborative environments using 360 panoramas. Marrinan teaches courses such as Intro to Programming & Problem Solving and Web Development, emphasizing practical application of computational concepts. In 2024, his team won the IEEE Scientific Visualization Contest for VisAnywhere, a tool enabling cross-platform scientific visualization. His work spans over two decades, with contributions to scalable resolution displays (SAGE2), GPU-based rendering optimizations, and AI-driven audio generation for video games. He holds a strong commitment to data-intensive collaboration and immersive technologies. Recent projects include developing omnidirectional stereo imaging techniques for VR exploration of large datasets and leveraging AI to enhance user-generated content in interactive media. His research addresses challenges in distributed rendering, real-time data transmission, and improving accessibility to complex scientific datasets.

• Cardiac Biomechanics
• Congenital Heart Malformations
• Medical Device Materials
• +۴ مورد دیگر

Dr. Choon Hwai Yap is a Senior Lecturer in the Department of Bioengineering at Imperial College London's Faculty of Engineering. His research focuses on cardiac biomechanics, particularly in embryonic and fetal hearts, investigating mechanical influences on growth and congenital heart defects. He also explores materials for cardiovascular devices, including anti-thrombotic coatings and hemostatic technologies. Dr. Yap holds editorial roles at Scientific Reports and Medical and Biological Engineering and Computing . His academic journey includes a PhD from Georgia Institute of Technology, a postdoc at University of Pittsburgh, and prior faculty work at National University of Singapore. Research themes include fetal heart interventions via ultrasound-based simulations, zebrafish cardiac development biomechanics, and fluid dynamics in congenital heart defects. Key contributions include finite element modeling of fetal heart mechanics and novel materials for medical devices. Recent work emphasizes AI-driven medical imaging advancements (e.g., deep learning for motion estimation in echocardiography) and multi-case physics-informed neural networks for fluid dynamics. His lab bridges engineering and clinical applications, aiming to improve fetal heart diagnostics and treatment strategies. Notable projects include predicting outcomes of fetal aortic valvuloplasty through myocardial stress analysis and developing superhydrophobic hemostats for minimal blood loss. He collaborates with clinicians to translate biomechanical insights into clinical practice, focusing on fetal cardiology and biomedical device innovation.

Leonid Sigalمشاهده پروفایل

دانشیار

• Computer Vision
• Machine Learning
• Computer Graphics
• +۸ مورد دیگر

Leonid Sigal is an Associate Professor in the Department of Computer Science at the University of British Columbia (UBC), holding the NSERC Canada Research Chair (CRC II) in Computer Vision and Machine Learning and a CIFAR AI Chair at the Vector Institute. He also serves as an Academic Advisor to Borealis AI. His research focuses on visual understanding, including object recognition, scene analysis, motion capture, and the intersection of computer vision with machine learning and graphics. Prior roles include Senior Research Scientist at Disney Research and Adjunct Faculty at Carnegie Mellon University. Education: Ph.D. (Computer Science, Brown University, 2008), M.Sc. (Computer Science, Brown University, 2003), B.Sc. (Computer Science & Mathematics, Boston University, 1999). Research interests span computer vision challenges such as human motion analysis, activity recognition, and generative models, alongside cross-disciplinary work in robotics and psychology. Notable achievements include Best Paper Awards at WACV 2015 and AMD 2012/2006, and leadership in organizing workshops like VisStory and tutorials on 'Looking at People.' Awards include the Killam Accelerator Fellowship, NSERC DAS award, and recognition as Area Chair for CVPR 2022, ICML 2022, and IJCAI 2022. His lab advises numerous graduate students and postdocs, with active collaborations spanning industry (e.g., Disney, Borealis) and academia (e.g., CMU, Vector Institute).

Farid Boussaidمشاهده پروفایل

استاد

• Machine Learning
• Computer Vision
• Neuromorphic Engineering
• +۵ مورد دیگر

Farid Boussaid is a Professor in the School of Electrical, Electronic and Computer Engineering at The University of Western Australia (UWA), affiliated with the UWA Oceans Institute. He holds an MM PhD from INSA Toulouse, France, and has held roles including Head of School (2014–2017). His research focuses on smart sensors, neuromorphic engineering, and machine learning applications in computer vision and signal processing. Education: M.S. and Ph.D. from National Institute of Applied Science (INSA), Toulouse, France (1996, 1999) Postdoctoral Fellow at Edith Cowan University (2000–2001) Australian Research Council APD Fellowship recipient (2001) Research Interests: Design of low-cost smart sensing systems, neuromorphic approaches for olfactory/visual processing, and interdisciplinary work in microelectronics, gas sensors, and camera-on-chip technologies. His research addresses bio-inspired signal processing and efficient integrated circuit design. Recent Research Trends: His publications emphasize deep learning applications in 3D vision, generative models, and medical imaging, with a focus on weakly supervised learning and multimodal data integration. Awards: 2016 Citation for Outstanding Contribution to Student Learning UWA Award for Excellence in Teaching (2014) Award for Growth in Innovation and Entrepreneurship (2021) Grants & Projects: Leads initiatives like the National Australian Cardiac CT Platform and robotics with 3D vision. Involves collaborations with Tokyo University of Science and NSF-funded projects. Labs/Teams: Active in UWA’s Oceans Institute and interdisciplinary teams advancing AI-driven sensing technologies.

• Machine Learning
• Artificial Intelligence
• Reinforcement Learning
• +۳ مورد دیگر

Alexander Ilin is a Visiting Professor and part-time teacher in the Department of Computer Science at Aalto University, specializing in Artificial Intelligence and Machine Learning. He holds roles in both the Computer Science - Artificial Intelligence and Machine Learning (AIML) research area and the Professors of Practice group. His research focuses on Machine Learning, Reinforcement Learning, and Deep Learning applications, with contributions to areas like neural networks, generative models, and healthcare informatics. Dr. Ilin earned a Doctoral degree in Engineering and Technology from Helsinki University of Technology in 2006. His work aligns with UN Sustainable Development Goals, particularly in advancing education and innovation. Key projects include the Finnish Center for Artificial Intelligence (FCAI) and the APPIA project on privacy-aware AI applications. His research explores cutting-edge topics such as diffusion models for dynamical systems, reinforcement learning for robotics, and self-supervised forecasting in healthcare. He has led projects like APPIA (2020–2021) and FCAI (2020–2026), securing grants from the Academy of Finland and Business Finland. His work bridges theory and practice, with applications in autonomous systems, nanotechnology, and medical diagnostics. Notable activities include visiting research at the UK Met Office Hadley Centre and presentations at top conferences like NeurIPS and AAMAS. His lab focuses on scalable AI solutions for real-world challenges, emphasizing ethical AI and privacy-preserving techniques.

• Visual and Cognitive Computing
• Machine Learning
• Social Robotics
• +۶ مورد دیگر

Professor Hui Yu is a Professor of Visual and Cognitive Computing at the University of Glasgow's School of Psychology & Neuroscience. He leads the Visual Computing and Social Robotics Group (VCSR) within the cSCAN research center. His research focuses on machine learning, social robotics, and 3D/4D facial avatar technologies. Professor Yu holds editorial roles for journals including Neurocomputing and IEEE Transactions on Human-Machine Systems. He has secured grants from EPSRC, EU Horizon, and the Royal Society. Notable awards include the Royal Academy of Engineering Industrial Fellowship and inclusion in Stanford's global top 2% cited scholars list. His work bridges theoretical frameworks with practical applications in healthcare, autonomous vehicles, and human-machine interaction. Ongoing projects include the EPSRC-funded ACMod initiative exploring affective computing and real-time wave imaging for maritime safety. Yu actively supervises PhD students in visual computing and social robotics, with current openings in 3D vision and social signal analysis. Grants: EPSRC ACMod (2024-2028), EPSRC Seakeeping (2025-2027), Royal Society Newton Fellowship Lab Affiliation: VCSR Group at cSCAN Professional Roles: IEEE SMC Associate Vice President, Chair of IEEE Social Computing Technical Committee

Souyoung Jinمشاهده پروفایل

استادیار

• Computer Vision
• Machine Learning
• Cognitive Science
• +۳ مورد دیگر

Souyoung Jin is an Assistant Professor in the Department of Computer Science at Dartmouth College. Her research focuses on Computer Vision, Machine Learning, and Cognitive Science with expertise in video understanding. She earned her B.S. from Dongguk University, M.S. from KAIST, Ph.D. from UMass Amherst, and completed a postdoc at MIT's CSAIL under Aude Oliva. She teaches courses like Machine Learning and Deep Learning, and leads research on AI systems mimicking human perception. Her lab explores multimodal tasks and synthetic data applications. She is an Area Chair for WACV 2025 and actively recruits motivated students for her lab. Education: B.S., Dongguk University M.S., Korea Advanced Institute of Science and Technology Ph.D., University of Massachusetts Amherst Postdoc, MIT Research Interests: Dr. Jin develops AI systems to understand human experiences through video analysis. Her work spans video understanding, synthetic data applications, and cognitive-inspired models. She emphasizes temporal context in low-resource regimes and cross-modal learning. Recent projects include BOLD Moments (fMRI-video datasets) and LangNav (language-based navigation). Grants & Labs: Her research is supported by grants focusing on synthetic video representations and multimodal fusion. She leads Dartmouth's Video Understanding Lab, fostering interdisciplinary collaborations between computer vision and cognitive science.

Adithya K Pediredlaمشاهده پروفایل

استادیار

• computational photography
• computer graphics
• acousto-optics
• +۸ مورد دیگر

Adithya K Pediredla is an Assistant Professor in the Department of Computer Science at Dartmouth College. His research focuses on computational imaging systems that co-design hardware and software to enhance imaging capabilities. He holds a B.Tech from the National Institute of Technology, Warangal (India), an M.E. from the Indian Institute of Science (Bangalore), a Ph.D. from Rice University, and completed a postdoctoral fellowship at Carnegie Mellon University. Educational Background: B.Tech, National Institute of Technology, Warangal, India M.E., Indian Institute of Science, Bangalore, India Ph.D., Rice University Postdoctoral Researcher, Carnegie Mellon University His research interests include computational photography, computer graphics, acousto-optics, and computer vision. He explores adaptive sensing, depth imaging, computational microscopy, and imaging in non-line-of-sight scenarios. His work also involves physically-based rendering and inverse rendering techniques for advanced computational imaging applications. No scientific awards or grants are explicitly listed in the provided information. He advises no students (PhD/Master’s) as per the data, and no lab affiliations are specified beyond his personal website.

Anjan Duttaمشاهده پروفایل

مدرس ارشد

• Computer Vision
• Machine Learning
• Deep Learning
• +۴ مورد دیگر

Dr. Anjan Dutta is a Senior Lecturer in Artificial Intelligence at the University of Surrey, UK. He holds a PhD in Computer Science from the Autonomous University of Barcelona (UAB), awarded with Excellent Cum Laude and the Extraordinary PhD Thesis Award (2013-14). His research focuses on computer vision and machine learning, particularly deep multi-modal embedding, zero-shot learning, and graph neural networks. Education: PhD in Computer Science, UAB (2014) MSc in Computer Vision & AI, UAB (2010) MCA, Maulana Abul Kalam Azad University of Technology (2009) BSc Mathematics (Honours), University of Calcutta (2006) Research Interests: Deep Learning for Vision Tasks Zero-Shot and Few-Shot Learning Graph Neural Networks Multi-modal Embedding Techniques Structured Representation Learning Recent Research Trends: His work emphasizes scalable and interpretable AI systems, with notable contributions in object counting, bias reduction in neural networks, and sketch-based retrieval. Publications span top-tier venues, reflecting interdisciplinary innovation in vision and learning. Awards & Honors: Extraordinary PhD Thesis Award (UAB, 2013-14) Excellent Cum Laude PhD Award (UAB, 2014) Labs & Affiliations: Active in the Surrey Institute for People-Centred AI (PAI) and the Centre for Vision, Speech and Signal Processing (CVSSP), contributing to cross-disciplinary AI research.

• Digital Watermarking
• Neural Representation
• Copyright Protection
• +۵ مورد دیگر

Renjie Wan is an Assistant Professor in the Department of Computer Science at Hong Kong Baptist University. He holds a BEng from the University of Electronic Science and Technology of China (2012) and a Ph.D. from Nanyang Technological University (2019). His research focuses on digital watermarking, neural representation, copyright protection, and AI security, with notable contributions in computational photography and image processing. He has received awards including the Microsoft CRSF Award and VCIP 2020 Best Paper Award. His academic journey includes a Wallenberg-NTU Presidential Postdoctoral Fellowship (2020–2022). He currently advises Ph.D. students in areas like neural radiance field watermarking and backdoor attack mitigation. Teaching responsibilities include courses on AI application development and Python for data analysis. Research Projects: Developing multispectral imaging algorithms for coastal surveillance Dynamic environment reflection separation techniques Face image reflection removal using neural radiance fields Awards: Meritorious Winner at Mathematical Contest in Modeling 2023 Silver Medal of 50th International Exhibition of Inventions Geneva His lab focuses on advancing AI security and 3D content protection through innovative techniques like neural radiance field watermarking and adversarial defense mechanisms.

Jochen Langمشاهده پروفایل

استاد

• Computer Graphics
• Computer Vision
• Computational Photography
• +۳ مورد دیگر

Professor Jochen Lang is a faculty member at the University of Ottawa's School of Electrical Engineering and Computer Science. He holds a Ph.D. from the University of British Columbia (2001) and M.Sc. from York University (Toronto), along with engineering degrees from Germany. Previously, he was a researcher at the Max-Planck-Institut für Informatik (2002–2004). His research focuses on measurement-based modeling in visual computing, integrating computer graphics, computer vision, and robotics. Notable projects include the IRIS NCE-funded 'Reality-based Modeling and Simulation' and EU-funded 'Virtual Heritage' initiatives. Key research areas include Computer Graphics , Computer Vision , and Computational Photography . His work addresses challenges like optical flow estimation, 3D modeling, medical imaging (e.g., SPECT analysis), and haptic rendering. He has contributed to advancements in video object segmentation, texture synthesis, and deep learning applications in medical diagnostics. His recent publications (2023–2025) explore topics such as optical flow under low visibility, medical image processing, and AI-driven defect detection in scintigraphy. His work often emphasizes practical applications in healthcare, robotics, and immersive technologies like virtual reality. Funding sources include EU grants and industry partnerships, reflecting his interdisciplinary impact.