جستجوی استاد راهنمای دانشگاهی

Angjoo Kanazawa is an Assistant Professor in the Department of Electrical Engineering and Computer Sciences (EECS) at the University of California, Berkeley. She leads the Kanazawa AI Research (KAIR) lab under the Berkeley Artificial Intelligence Research (BAIR) umbrella and serves on the advisory board of Wonder Dynamics. Her research focuses on the intersection of computer vision, computer graphics, and machine learning, with a particular emphasis on 4D reconstruction of dynamic scenes, neural radiance fields (NeRF), and systems that model human-environment interactions from 2D visual data. Education : Ph.D., Computer Science (2017), University of Maryland, College Park BA, Mathematics and Computer Science (2012), New York University (NYU) Her work aims to build systems that can capture, perceive, and understand complex 3D/4D worlds from photographs and videos, enabling applications in scene reconstruction, motion analysis, and generative modeling. She has pioneered techniques for scaling NeRFs across GPUs (NeRF-XL), developing open-source tools like nerfstudio and gsplat. Her recent publications focus on topics like self-occluded avatar recovery (SOAR), decentralized diffusion models, and 4D reconstruction of articulated objects for robotics. Kanazawa's research has been recognized with prestigious awards including the IEEE CS TCPAMI Young Researcher Award (2024) , Sloan Research Fellowship (2023) , and Google Faculty Research Award (2021) . Her lab has trained numerous students who now hold positions at leading institutions and companies like Anthropic, Meta Reality Labs, and Luma AI. Key Scientific Awards : IEEE CS TCPAMI Young Researcher Award (2024) Sloan Research Fellow (2023) Hellman Fellow (2022) Bakar Fellows Spark Award (2022) Google Faculty Research Award (2021) Her KAIR lab collaborates extensively with industry partners and academic institutions, including the Max Planck Institute and Google Research. She has served as an advisor for PhD students and postdocs who now lead teams at UC Berkeley, MIT, Stanford, and Luma AI, while her teaching includes graduate courses like CS 280A (Computer Vision) and CS 294-173 (Learning for 3D Vision).

• Computer Vision
• Computer Graphics
• Artificial Intelligence
• +۶ مورد دیگر

Timothy M. Hospedales is a Professor of Artificial Intelligence at the Institute of Perception, Action and Behaviour within the School of Informatics at the University of Edinburgh . He also serves as VP AI and Head of Samsung AI Research Centre Europe . His research focuses on efficient and robust AI , emphasizing meta-learning , lifelong transfer-learning , and domain adaptation in both probabilistic and deep learning frameworks. Applications span computer vision , vision and language , reinforcement learning for robotics , and finance . Professor at University of Edinburgh (2020–present) ELLIS Fellow (2021) Head of Samsung AI Research Europe (2020–present) Founding Director of Applied Machine Learning Lab at QMUL (2012–2016) His work includes pioneering contributions to meta-learning , few-shot learning , and self-supervised methods , with notable awards such as the Best Paper Prize at ICML AutoML 2018 and Best Student Paper at ICPR 2018 . He has co-authored 15+ recent papers on topics like Vision-Language Models , Medical AI Fairness , and Diffusion Model Optimization . He served as Program Co-Chair for BMVC 2018 and AAAI 2022 , and authored a book on Visual Adaptation in the Deep Learning Era (2022). Co-Chair, BMVC 2018 Guest Editor, IET CV Special Issue (2016) Keynote Speaker at TASK-CV Workshop (ECCV 2016) Special Issue on Fewer Labels (IEEE PAMI 2020) His leadership extends to organizing workshops like the Learning-to-Learn Workshop at ICLR 2021 , Meta-Learning Workshop at NeurIPS 2020 , and Domain Generalisation Workshop at ICLR 2023 . Current projects include Meta-Omnium (CVPR 2023) for general-purpose meta-learning and MetaAudio (ICANN 2022) for few-shot audio classification benchmarks.

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۶ مورد دیگر

Ira Kemelmacher-Shlizerman is a Full Professor of Computer Science at the Paul G. Allen School of Computer Science & Engineering at the University of Washington and Director of the UW Reality Lab. She also serves as a Principal Scientist at Google, where she leads the Shopping Gen AI visuals teams focusing on Virtual Try-On, 3D, and product videos. Her research spans computer vision, computer graphics, and Generative AI, with particular contributions to virtual try-on technology, 3D modeling, and augmented reality applications. Professor Kemelmacher-Shlizerman's research interests focus on Generative AI applications in visual computing. Her work bridges the gap between theoretical computer vision and practical applications, particularly in e-commerce and virtual reality. She has made significant contributions to virtual try-on technology, 3D editing with generative models, and AI applications for shopping experiences. Her research combines deep learning with traditional computer vision techniques to solve challenging problems in image and video synthesis. Her recent publications demonstrate a strong trend toward Generative AI applications for visual shopping experiences, virtual try-on technology, and 3D content creation. The work spans multiple top conferences including CVPR, SIGGRAPH, and ICCV, with a focus on practical applications of computer vision and graphics. Her research has evolved from foundational work in face reconstruction and aging to current applications in virtual shopping and 3D content generation. Google faculty award Madrona prize GeekWire Innovation of the Year Award Covers of CACM and SIGGRAPH Best student paper honorable mention at CVPR'21 Best demo runner up MobiSys'22 Senior member of IEEE Distinguished Member of ACM Professor Kemelmacher-Shlizerman has successfully tech-transferred multiple research projects to industry. She founded Dreambit, a startup acquired by Meta, and previously built and launched the Face Movies feature at Google. She currently leads Google's Shopping Gen AI visuals teams, focusing on 10x improvements to shopping journeys. Her UW Reality Lab serves as a hub for AR/VR research with industry partnerships. She has mentored numerous PhD students who have become researchers in both academia and industry, with several publications featuring student co-authors receiving recognition at top conferences. Professor Kemelmacher-Shlizerman leads the Graphics and Imaging Laboratory (GRAIL) and the UW Reality Lab, which focuses on augmented and virtual reality research with industry partnerships including Google. The labs work on cutting-edge projects in virtual try-on, 3D modeling, and immersive experiences, bridging academic research with real-world applications.

• Computer Vision
• Computer Graphics
• Generative AI
• +۶ مورد دیگر

Harish Ravichandar is an Assistant Professor at the School of Interactive Computing , Georgia Institute of Technology, and a core faculty member of the Institute for Robotics and Intelligent Machines (IRIM) . He leads the Structured Techniques for Algorithmic Robotics (STAR) Lab , focusing on structured computational frameworks and learning algorithms with inductive biases to enhance robot efficiency, reliability, and self-sufficiency in human-robot collaboration and complex applications like dexterous manipulation and multi-agent coordination. His research bridges robot learning , human-robot interaction , and multi-agent systems , emphasizing stable, frugal, and safe skill acquisition from human demonstrations. Key themes include intention inference , trajectory optimization , and heterogeneous team coordination , often leveraging Koopman operators , hypernetworks , and graph-based methods . Scientific recognition includes the NSF CAREER Award , IEEE MRS Best Paper Award , and Georgia Tech’s College of Computing Outstanding Post-Doctoral Research Award . His work also received the ASME DSCC Best Student Paper Award and P&W Institute Graduate Fellowship . Harish’s educational background includes a Ph.D. in Electrical and Computer Engineering from the University of Connecticut (2018) , an M.S. from the University of Florida (2014) , and a B.E. in Instrumentation and Control Engineering from Anna University (2012) . He previously held postdoctoral and research scientist roles at Georgia Tech before his current position.

• Robotics
• Machine Learning
• Human-Robot Interaction
• +۲ مورد دیگر

Davide Scaramuzza is a Professor and Director of the Robotics and Perception Group at the University of Zurich. He holds a Ph.D. from ETH Zurich and has conducted postdoctoral research at the University of Pennsylvania and Stanford. His research focuses on autonomous drone navigation using visual and event-based sensors, leading to breakthroughs like AI drones outperforming human pilots in racing (Nature 2023). He pioneered algorithms for Mars helicopter navigation and developed the PX4 autopilot system. Key awards include the Kiyo-Tomiyasu IEEE Technical Field Award (2024), ERC Consolidator Grant (2019), and multiple best paper awards. His entrepreneurial ventures include co-founding Zurich-Eye (later Meta Zurich) and SUIND for agricultural drones. He co-authored the textbook Introduction to Autonomous Mobile Robots , widely used in academia. Research spans event camera algorithms, visual-inertial SLAM, and reinforcement learning for agile flight. His lab's work is featured in IEEE Spectrum, The Guardian, and Forbes. He advises UN initiatives on AI for disaster response and nuclear safety. Current projects include Graph-Generating State Space Models (CVPR 2024) and event-based vision for automotive systems (Nature 2024).

• Robotics
• Computer Vision
• Autonomous Navigation
• +۴ مورد دیگر

Jill A. Olin is an Assistant Professor in the Department of Biological Sciences at Michigan Technological University, affiliated with the College of Sciences and Arts. She holds a PhD in Environmental Science from the University of Windsor, an MS in Marine Biology from Hofstra University, and a BS in Marine & Freshwater Biology from the University of New Hampshire. Her research focuses on community ecology, trophic interactions, and marine ecosystems, with an emphasis on conservation through biomarker and modeling approaches. Key interests include ecosystem stability, anthropogenic impacts, and food web dynamics. She teaches Ecology and Evolution, Marine Ecology, and Ecogeochemical Tracer Techniques. Her work integrates stable isotope analysis, DNA metabarcoding, and ecological modeling to address questions about species distribution, trophic niche partitioning, and resilience to environmental stressors. Notable projects include studies on Lake Superior fish ecotypes, Gulf of Mexico oil spill impacts, and salt marsh restoration. Dr. Olin collaborates with NOAA on restoration research and has published extensively on trophic ecology, resource partitioning, and ecosystem responses to human activities. While no formal grants or awards are listed, her contributions highlight interdisciplinary approaches to ecological challenges.

• Community Ecology
• Trophic Interactions
• Marine Ecology
• +۳ مورد دیگر

Ryan K. Williams is an Assistant Professor in the Bradley Department of Electrical and Computer Engineering at Virginia Tech. His research focuses on real-time systems optimization, multi-agent robotics, and computational frameworks for autonomous systems. He holds an NSF Career Award (2021) and has contributed to advancing algorithms for resilient and efficient multi-robot coordination. His work addresses challenges in distributed systems, including scheduling, fault tolerance, and resource allocation. Key areas include probabilistic security in multi-robot teams, topology control for stable coordination, and anticipatory planning for search and rescue operations. He also explores intersections with education, such as analyzing teacher professional learning impacts on student outcomes in STEM. Awards: NSF Career Award 2021 Grants: AF: Small grants (2024, 2021), CPS: Medium grant (2019) Labs/Teams: Collaborates on multi-robot systems and computational autonomy projects

• Real-Time Systems
• Robotics
• Multi-Agent Systems
• +۵ مورد دیگر

Ben Ward-Cherrier is a Senior Lecturer in Robotics at the University of Bristol's School of Engineering Mathematics and Technology. His research focuses on biomimetic tactile sensing, neuromorphic systems for robotics, and haptic interfaces. He develops artificial tactile systems inspired by biological sensory mechanisms for applications in prosthetics, robotic manipulation, and human-robot interaction. Key research areas include neuromorphic tactile sensors that mimic biological afferents, real-time texture and edge classification algorithms, incipient slip detection for stable grasping, and vibrotactile feedback systems. Recent work integrates spiking neural networks with tactile hardware for efficient sensory processing. Publications demonstrate advancement in tactile sensing capabilities, including braille recognition in noisy environments, psychophysics-inspired benchmarking, multi-modal texture/velocity classification, and industrial applications like composite defect detection. Research bridges computational neuroscience with practical robotic systems.

• Robotics
• Computational Neuroscience
• Prosthetics
• +۲ مورد دیگر

Essam M. Abdelfattah serves as Assistant Professor in the Department of Animal & Veterinary Science at California State Polytechnic University, Pomona's Huntley College of Agriculture. His research integrates behavioral and physiological methodologies to enhance animal health and welfare through early disease detection technologies and stress mitigation strategies, with statewide extension leadership in dairy/beef cattle herd health and food safety. Education: PhD in Animal Behaviour and Welfare (2014), Purdue University & Benha University (Mutual supervision) MVetMed in Veterinary Medical Sciences (2008), Benha University BVetMed in Veterinary Medical Sciences (2004), Benha University (Class Rank: 1/250) Research Focus: Dr. Abdelfattah investigates environmental, nutritional, and management impacts on livestock welfare using advanced monitoring systems. His work spans poultry behavior, dairy/beef cattle health optimization, and antimicrobial resistance mitigation, emphasizing practical applications for California's agricultural industry through UC Davis collaborations. Publication Trends: Recent publications (2020-2024) demonstrate concentrated research on antimicrobial stewardship post-Senate Bill 27, dairy calf housing systems, and bovine disease management. His work consistently bridges veterinary science, behavioral analysis, and food safety through multi-institutional field studies across California dairies and international contexts. Scientific Recognition: 2023 CPP Professional Development Travel Award 2021 UC Davis Award for Excellence in Postdoctoral Research Multiple UC Davis Postdoctoral Travel Grants (2017-2019) Leaders for the Future Program Fellowship (UC Davis) Academic Engagement: Teaches core courses including Animal Behavior (AVS 3456) and Senior Seminar (AVS 4610), while directing extension programs that translate research into practical herd health protocols. His statewide outreach focuses on evidence-based management practices for dairy/beef producers, leveraging publications in Journal of Dairy Science and Antibiotics to inform industry standards. Professional Integration: Active in Veterinary Association for Farm Animal Welfare, American Veterinary Medical Association, and Dairy Calf and Heifer Association, with sustained membership in antimicrobial resistance research networks since 2017. His collaborative work with UC Davis and California dairies positions him at the forefront of sustainable livestock management innovation.

• Animal Welfare
• Animal Behavior
• Poultry Science
• +۴ مورد دیگر

Jack Doerner is an Assistant Professor of Computer Science at the University of Virginia. His research focuses on cryptography, particularly secure multi-party computation, threshold cryptography, and oblivious RAM (ORAM). Previously, he held postdoctoral positions at Brown University (hosted by Anna Lysyanskaya) and jointly at the Technion and Reichman University (hosted by Yuval Ishai and Elette Boyle). He completed his PhD at Northeastern University, advised by Abhi Shelat. His work spans foundational advancements in cryptographic protocols, including threshold ECDSA, modular analysis of broadcast protocols, and scalable ORAM solutions. Notable contributions include the first constant-round coin tossing extension with guaranteed output and efficient secure stable matching at scale. His research emphasizes practical efficiency and security in distributed systems. Doerner also engages in artistic endeavors, creating films, photography, and sculptures that explore perception and space. His art has been exhibited in galleries such as the Second Street Gallery in Charlottesville. Publications highlight contributions to secure computation frameworks, threshold signatures, and cryptographic protocols. His work addresses challenges in distributed systems, privacy-preserving algorithms, and foundational cryptographic assumptions.

• Cryptography
• Secure Multiparty Computation
• Oblivious RAM (ORAM)
• +۴ مورد دیگر

Madeleine Mant is an Assistant Professor in the Department of Anthropology at the University of Toronto Mississauga, specializing in Biocultural Anthropology, Paleopathology, and Medical History. Her research examines health inequities in marginalized populations through interdisciplinary analysis of skeletal remains, historical archives, and contemporary surveys. PhD in Anthropology, McMaster University (2016) Banting SSHRC Postdoctoral Fellow (2017-19) Mant's work bridges Bioarchaeology and Medical Anthropology, focusing on trauma, infectious disease, and institutional health practices. Current projects explore longitudinal health trends in 18th-19th century hospitals, prison health records, and pandemic vaccine hesitancy. Her recent publications highlight the integration of multi-method datasets to analyze: Historical morbidity patterns in London and Newfoundland Intersectional trauma analysis Modern vaccine confidence dynamics Scientific Awards: Banting SSHRC Postdoctoral Fellowship Editor’s Choice, American Journal of Physical Anthropology (2021)

• Anthropology of Health
• Paleopathology
• Bioarchaeology
• +۴ مورد دیگر

David S. Russell, MD, PhD is an Assistant Clinical Professor at Yale School of Medicine with primary appointments in Psychiatry and secondary appointments in Neurology. He serves as Senior Medical Director at Perceptive New Haven Clinic, a 100% research-dedicated clinical research facility focused on diseases with major unmet needs. Dr. Russell is a neurologist specializing in movement disorders, dementias, and other neurodegenerative conditions. Dr. Russell earned his BA in Biology from Oberlin College (1982), followed by MD and PhD degrees from Cornell University (1991). He completed his internship (1992) and served as Chief Resident in Neurology at Yale-New Haven Hospital (1995). His research focuses on neurodegenerative diseases, particularly Alzheimer's and Parkinson's disease, with emphasis on biomarker development, neuroimaging techniques (especially PET imaging), and clinical translation of novel therapeutics. Dr. Russell has made significant contributions to the development and validation of tau and alpha-synuclein imaging agents, as well as research on O-GlcNAcase inhibitors for Alzheimer's disease treatment. His work bridges academic medicine and pharmaceutical development, with numerous publications on diagnostic biomarkers and therapeutic targets for neurodegenerative conditions. Analysis of his recent publications (2020-2025) reveals a strong emphasis on molecular imaging techniques for neurodegenerative diseases, particularly PET imaging of tau and alpha-synuclein pathology. His work spans basic biomarker validation, head-to-head comparisons of imaging agents, and clinical translation of novel therapeutics targeting neurodegenerative pathways. A significant portion of his research focuses on differentiating between various tauopathies and synucleinopathies through advanced imaging techniques. Dr. Russell leads the Perceptive New Haven Clinic, a dedicated clinical research facility focused on neurodegenerative disorders. His work involves close collaboration with pharmaceutical companies and academic researchers to advance understanding and treatment of movement disorders and dementias.

• Movement Disorders
• Alzheimer Disease
• Huntington Disease
• +۴ مورد دیگر

Marc Hanheide is a Professor of Intelligent Robotics and Interactive Systems in the School of Computer Science at the University of Lincoln, UK. His academic career spans positions at the University of Lincoln (2012-present), University of Birmingham (2009-2011), and Bielefeld University (2006-2009). His doctoral training at Bielefeld University (2001-2006) established his foundation in computer science, leading to significant contributions in robotics research. He began his research career working on the EU IST project VAMPIRE, followed by leadership roles in major EU projects including COGNIRON, CogX, and the long-running STRANDS project. Marc Hanheide's research focuses on Autonomous Robotics, Human-Robot Interaction, Long-term Autonomy, Agricultural Robotics, and Nuclear Robotics . His work addresses fundamental challenges in enabling robots to operate effectively in dynamic, real-world environments over extended periods. He has pioneered approaches to human-robot spatial interaction, long-term localization, and multi-robot fleet management. Analysis of his recent publications reveals a strong trajectory toward practical applications in agriculture and hazardous environments, with emphasis on long-term stability, human-aware navigation, causal modeling for interaction, and fleet optimization. His work integrates theoretical advances in AI with tangible robotics applications that address real-world challenges in food production and nuclear decommissioning. Principal Investigator for major research initiatives: EU FP7 STRANDS project on long-term robotic behavior EPSRC Centre for Doctoral Training in Agri-Food Robotics (AgriFoRwArdS) National Centre for Nuclear Robotics (NCNR) Multiple agricultural robotics projects including ILIAD and Bacchus Long-Term His research leadership has secured substantial funding from EPSRC, BBSRC, Innovate UK, and the European Commission. He actively mentors students and early-career researchers, with a focus on translating theoretical robotics research into practical applications. His work demonstrates strong industry engagement, particularly in agricultural technology and nuclear robotics sectors. Based at the Lincoln Centre for Autonomous Systems (LCAS), Hanheide leads research on enabling robots to operate continuously in changing environments through innovations in perception, navigation, and human-robot interaction. His team develops systems that maintain functionality despite environmental changes, sensor degradation, and evolving task requirements.

• Robotics
• Human-Robot Interaction
• Artificial Intelligence
• +۴ مورد دیگر

Dr. Alexander Pastukhov is an Assistant Professor at the Department of General Psychology and Methodology, University of Bamberg. His research focuses on multi-stable perception , perceptual inference , and the interplay between attention and microsaccades . He develops open-source tools like saccadr , eyelinkReader , and bistablehistory for analyzing eye movements and perceptual dynamics. Research Interests : Multi-level mechanisms of perception and memory History effects in bistable perception Attentional allocation via microsaccade analysis Bayesian modeling of perceptual decision-making Scientific Awards : 2013 'Best of the Year' award from the Psychonomic Society for work on sensory memory and adaptation in structure-from-motion displays His recent software development includes probabilistic programming tools for 2D/3D transformations and eye-tracking analysis. He also contributes to applied data analysis teaching materials using R and Python. Collaborative projects with industry partners (e.g., BMW) and institutions (e.g., Fraunhofer, Orange Labs) highlight his research transfer efforts.

• Multi-stable Perception
• Perceptual Inference
• Cognitive Neuroscience
• +۷ مورد دیگر

James Tompkin is an Associate Professor in the Department of Computer Science at Brown University, specializing in visual computing. His research focuses on computer graphics, computer vision, and human-computer interaction, with an emphasis on techniques for image/video creation, editing, analysis, and interaction. His lab develops methods for scene reconstruction (especially from multi-camera systems), dynamic scene modeling, and applications in 2D, multi-view, and VR/AR displays. Research interests include neural radiance fields (NeRFs), Gaussian splatting, time-of-flight sensing, and generative adversarial networks (GANs). He has collaborated extensively with industry partners (Adobe, Amazon, Meta) and received funding from NSF, DARPA, NASA, and UK/EPSRC. His work is disseminated via top-tier venues like CVPR, SIGGRAPH, and ECCV. Teaching includes visual computing topics, and his lab maintains active projects on GitHub and project webpages. Office hours are held weekly, with scheduling via Google Calendar integration.

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