جست‌وجوی استاد و پژوهشگر

Steve Counsellمشاهده پروفایل

استاد

• Software Engineering
• Empirical Software Engineering
• Software Metrics
• +۶ مورد دیگر

Professor Steve Counsell is a distinguished academic in the Department of Computer Science at Brunel University London's College of Engineering, Design and Physical Sciences. Holding a PhD from Birkbeck, University of London (2002), he previously served as a Lecturer at Birkbeck and brings industry development experience to his academic role. As a Fellow of the British Computer Society, his career bridges theoretical research and practical software engineering applications. PhD in Software Engineering from Birkbeck, University of London (2002) Former Lecturer at Birkbeck Department of Computer Science Industry software development experience prior to PhD Professor Counsell's research centers on empirical software engineering with particular focus on software metrics, refactoring techniques, code smells, fault analysis, and agile methodology implementation. His work consistently emphasizes industry collaboration, addressing real-world challenges faced by developers and project managers. A significant portion of his research investigates the relationship between software structure metrics and maintainability, with extensive studies on object-oriented systems evolution and web application engineering. Analysis of his recent publication trends reveals a sustained focus on empirical validation of software engineering practices, with increasing emphasis on industrial case studies and reproducibility of results. His work spans both theoretical metric development and practical application in commercial environments, particularly examining how structural code properties correlate with fault-proneness and maintenance effort. Fellow of the British Computer Society Professor Counsell actively supervises doctoral research, currently guiding three PhD students while having successfully completed nine PhD supervisions since 2004, all within software engineering and information systems domains. His research has attracted significant funding including EPSRC grants EP/E055141/1 (as Co-investigator studying program slicing and faults), EP/H019685/1 (with Moorfields Eye Hospital on glaucoma data analysis), and current project EP/L011751/1 exploring fault prediction techniques in collaboration with industry partners. His research activities are coordinated through the CIDA research group at Brunel, where he maintains strong collaborations with industry partners to ensure practical relevance of his empirical studies. Current projects focus on analyzing industrial fault data to determine which prediction techniques provide the most accurate explanations of software faults in real-world systems.

Tolga Ovatmanمشاهده پروفایل

استاد

• Algorithms and Computing Theory
• Computer Software and Software Engineering
• Cloud Computing
• +۶ مورد دیگر

Prof. Dr. Tolga Ovatman is a faculty member at the Department of Computer Engineering, Istanbul Technical University , where he has been serving as Head of Department since 2024. His academic career spans roles from Research Assistant (2004-2012) to Associate Professor (2019-2023) and full Professor (2023-present). He previously held administrative roles such as Vice Dean (2018-2022) and Deputy Head of Department (2016-2018). PhD in Computer Engineering (2005-2011) MS in Computer Engineering (2003-2005) BSc from Hacettepe University (1999-2003) His research focuses on model checking , replicated state machines , cloud computing , and object-oriented software . Recent work addresses computation offloading in 6G networks , collaborative text editing data structures , and energy-efficient environmental monitoring systems . Key projects led include Design of a Multiplexed State Machine Storage System for Edge Computing (2022-2024) and Microservice Compatible Symphony Infrastructure Research (2020). He has supervised numerous theses on topics ranging from collaborative text editing to AI applications in watershed management . Publications span IEEE Transactions , Springer , and conferences like CSCE and CLOSER .

Robert Bergevinمشاهده پروفایل

استاد

• Cognitive Computer Vision
• Pattern Recognition
• Artificial Vision
• +۷ مورد دیگر

Robert Bergevin is a Full Professor in the Department of Electrical Engineering and Computer Engineering at Laval University's Faculty of Science and Engineering, where he has been employed since 1990 and achieved full professor status in 2001. He is also a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence) and actively participates in graduate recruitment. Dr. Bergevin's educational background includes: Ph.D. in Electrical Engineering from McGill University (1985-1990), with thesis titled "Primal Access Recognition of Visual Objects" under Professor Martin D. Levine M.Sc.A. in Biomedical Engineering from École Polytechnique de Montréal (1982-1984), with thesis on "Modeling and numerical simulation of a nuclear magnetic resonance imaging system" under Professor Robert Guardo B.Sc.A. in Electrical Engineering (Communications specialty) from École Polytechnique de Montréal (1978-1982) Professor Bergevin's research spans cognitive computer vision, pattern recognition, and information systems design methodologies. His work is guided by a unique methodology that progresses "from the general to the particular" to achieve "simply communicable and universally applicable understanding." He has been a researcher in cognitive computer vision since 1985, with particular focus on ontology, methodology, and categorization. His research interests include Ontology of Cognitive Digital Vision, Cognitive Digital Vision Development Methodology, Categorization in cognitive digital vision, Analysis and understanding of images and videos, and Understandable artificial intelligence. As a generalist, he is also a proponent of the science of global anticipatory design (R. Buckminster Fuller) and general semantics (Alfred Korzybski). Analysis of Professor Bergevin's recent publications reveals a strong focus on video anomaly detection, carried object detection, and human activity recognition. His work consistently applies cognitive principles to computer vision problems, often developing novel methodologies for segmentation, tracking, and recognition. The research shows progression from foundational work on image analysis to more complex spatio-temporal understanding of video content, with increasing integration of deep learning techniques in recent years while maintaining a focus on interpretable and cognitively-inspired approaches. Among his professional recognitions: Teaching Star, Faculty of Science and Engineering (2019, 2012) Professor Bergevin has supervised numerous graduate students throughout his career, including four PhD candidates and four Master's students in recent years. His current research includes the "Cyber-physical systems and materialized machine intelligence" project funded by Université Laval, École de technologie supérieure, and Fonds de recherche du Québec - Nature and technologies, running from 2019 to 2026. He was also the director of the bachelor's program in computer engineering from 2001 to 2010 and served as Area Editor for the journal Computer Vision and Image Understanding from 2002 to 2017. As a member of CeRVIM (Research Center in Robotics, Vision and Machine Intelligence), Professor Bergevin collaborates with researchers across multiple disciplines to advance the fields of robotics, computer vision, and machine intelligence. His work bridges theoretical foundations with practical applications, particularly in the analysis of human activities and object recognition in complex visual scenes.

Gregory F. Welchمشاهده پروفایل

استاد مدعو

• Human motion tracking systems
• 3D telepresence
• Virtual reality
• +۷ مورد دیگر

Gregory F. Welch serves as the Florida Hospital Endowed Chair in Healthcare Simulation at the University of Central Florida, with primary appointments in the College of Nursing, Department of Computer Science, and Institute for Simulation & Training. He also holds an Adjunct Professor position in Computer Science at the University of North Carolina at Chapel Hill. With a Ph.D. from UNC-Chapel Hill in 1996, his career spans academia, NASA's Jet Propulsion Laboratory, and Northrop-Grumman's Defense Systems Division. Ph.D. in Computer Science, University of North Carolina at Chapel Hill, 1996 Degree in Electrical Technology, Purdue University (with Highest Distinction), 1986 Dr. Welch's research spans human-computer interaction, virtual and augmented reality, motion tracking systems, 3D telepresence, and stochastic estimation , with significant applications to healthcare training and education. His work focuses on creating seamless interactions between physical and virtual environments, particularly through innovations in tracking technology, view synthesis, and the Kalman filter. A notable contribution is his internationally-recognized website dedicated to the Kalman filter, which has become a standard reference in the field. Dr. Welch's recent publications (2016-2017) demonstrate a strong focus on social presence in virtual and augmented reality environments , particularly examining how physical-virtual interactions affect user experience. His work explores nuanced aspects like spatial coherence, gesturing, vibrotactile feedback, and environmental effects on social presence. A recurring theme is the development of "human surrogates" - physical manifestations of virtual humans that bridge the gap between real and virtual spaces, with direct applications to healthcare simulation and training. IEEE Senior Member 2nd Prize Best ICDSC 2011 Paper While specific student names aren't listed in the available materials, Dr. Welch has advised numerous researchers in virtual reality, human-computer interaction, and healthcare simulation. His work has attracted significant research funding, particularly through his role as the Florida Hospital Endowed Chair in Healthcare Simulation. His research spans multiple domains including medical applications, military training, and emergency response scenarios, suggesting diverse grant support from NIH, NSF, and defense-related agencies. Dr. Welch is affiliated with multiple research entities including the Institute for Simulation & Training at UCF and maintains connections with UNC-Chapel Hill's Computer Science department. His work often involves interdisciplinary collaborations between computer scientists, medical professionals, and educators. Notably, he co-developed the HuSIS (Human Surrogate Interaction Space), a dedicated facility for studying human interactions with virtual surrogates, demonstrating his commitment to creating specialized research environments for advancing virtual and augmented reality applications.

Kyle Bradburyمشاهده پروفایل

مدرس

• Machine Learning
• Statistical Signal Processing
• Energy Systems
• +۷ مورد دیگر

Kyle Bradbury is a Lecturer and Managing Director of the Energy Data Analytics Lab at Duke University. His work merges machine learning, statistical signal processing, and remote sensing to solve critical energy system challenges, particularly focusing on integrating renewable energy (wind and solar) into power grids through advanced modeling of energy storage reliability and cost trade-offs. He teaches the course IDS 705: Principles of Machine Learning .

Nils Petter Aspvikمشاهده پروفایل

پژوهشگر

• Physical Activity
• Objective Measurement of Physical Activity
• Youth Sports
• +۳ مورد دیگر

Nils Petter Aspvik is a researcher at the Department of Sociology and Political Science: Sports Science at the Norwegian University of Science and Technology (NTNU), Trondheim . His work focuses on physical activity in populations, objective measurement methods, youth sports, and coach-athlete communication dynamics.

Mohamed Alyمشاهده پروفایل

استاد

• Geospatial Technologies
• Remote Sensing
• Geohazard Assessment
• +۳ مورد دیگر

Mohamed Aly is a Professor at the University of Arkansas, affiliated with the Department of Geosciences, Center for Advanced Spatial Technologies (CAST), Arkansas Center for Space & Planetary Sciences, and Environmental Dynamics (ENDY) Program. His research integrates Synthetic Aperture Radar Interferometry (InSAR), GIS, GNSS, and machine learning for geohazard assessment and environmental monitoring. Education: PhD in Geology (Radar Interferometry), Texas A&M University MS in Geology (Remote Sensing & GIS), Zagazig University Research focuses on InSAR for crustal deformation, machine learning in geospatial analysis, wildfire and landslide susceptibility modeling, and geothermal process monitoring. Recent publications emphasize multisensor data fusion and Google Earth Engine applications. Scientific awards include NASA EPSCoR Early Career Investigator, Fulbright College Teaching Commendation, and Academic Excellence from Texas A&M. He mentors students in geohazard research and geospatial technologies.

Mario Selvaggioمشاهده پروفایل

استادیار

• Shared control/autonomy
• Robot teleoperation
• Passivity-based control
• +۷ مورد دیگر

Mario Selvaggio is an Assistant Professor at the Department of Electrical Engineering and Information Technology, University of Naples Federico II. He actively contributes to robotics research through his involvement with PRISMA Lab and ICAROS , while co-founding spinoff companies BeyondShape and Herobots . His academic background includes a Ph.D. in Information Technology and Electrical Engineering (2020) under Prof. Bruno Siciliano, with previous degrees in Mechanical Engineering (2013, 2015). Ph.D. in Information Technology and Electrical Engineering (2020) Bachelor's and Master's in Mechanical Engineering (2013, 2015) His research interests focus on shared control/autonomy, robot teleoperation, passivity-based control, soft robotics, and robotic surgery. He has developed innovative solutions including: Shared-control teleoperation for soft growing robots Non-prehensile object transportation frameworks Advanced modeling of cable-suspended dual-arm systems Medical robotics with force-sensor equipped tools Virtual reality-based teleoperation architectures Recent publications (2021-2025) span topics from semi-autonomous aerial manipulation to cyber-physical measurement systems, with emphasis on human-robot interaction and industrial applications. He serves as Associate Editor for several IEEE conferences and journals. Scientific Awards IEEE RAS Technical Committee on Haptics grant ($2500, 2018) Second prize at Bioengineering Congress (2018) Finalist for 'Fabrizio Flacco' Best Paper Award (2020) Prof. Selvaggio teaches the Master's Course in Automation Engineering and Robotics (2024/2025) using Robot Operating System (ROS) curriculum. He actively collaborates with international research groups at IRISA/INRIA Rennes , Rainbow team , and University of California Santa Barbara (mechanical engineering department). His research combines theoretical advancements with practical implementations, demonstrated through extensive validation in simulated environments and real robotic platforms including KUKA LWR IIWA manipulators, dVRK systems, and humanoid platforms.

Earl R. Dorseyمشاهده پروفایل

استاد

• Parkinson's disease
• Telemedicine
• Neurological disorders
• +۳ مورد دیگر

Ray Dorsey serves as the David M. Levy Professor of Neurology at the University of Rochester's School of Medicine and Dentistry, holding a part-time faculty appointment in the Department of Neurology and the Center for Health and Technology (SMD). His pioneering work focuses on identifying and eliminating the root causes of Parkinson's disease through innovative care delivery models and digital health technologies. Dr. Dorsey's educational background includes: BS in Biological Science from Stanford University (1994) MD from University of Pennsylvania School of Medicine (1999) MBA in Health Care Management from The Wharton School at The University of Pennsylvania (1999) Neurology Residency at Hospital of the University of Pennsylvania (2002-2005) His research program centers on addressing what he terms the "Parkinson pandemic" - the rapidly growing global burden of Parkinson's disease. Dr. Dorsey has revolutionized neurological care through telemedicine applications, conducting the first national randomized controlled trial of virtual house calls for Parkinson's disease. His work demonstrates that remote consultations can effectively deliver specialized neurological care regardless of geographic location, addressing critical shortages of movement disorder specialists. He has pioneered the use of smartphones, wearable sensors, and machine learning algorithms to continuously monitor disease symptoms in real-world settings, enabling more frequent and objective assessments than traditional clinic visits. Analysis of Dr. Dorsey's publication record reveals a strategic progression from foundational epidemiological studies documenting the growing burden of neurological disorders toward innovative solutions using digital health technologies. His recent work increasingly focuses on practical implementation of virtual care models, patient-centered outcome measurement, and leveraging big data analytics for disease progression modeling. The interdisciplinary nature of his research bridges clinical neurology, health services research, data science, and healthcare policy. Among his notable recognitions: White House "Champion of Change" for Parkinson's Disease (2015) Dr. Dorsey plays a pivotal role in the University of Rochester's Center for Health + Technology (CHeT), which has coordinated over 150 clinical research studies involving 45,000+ participants that have led to 12 FDA-approved treatments. His work extends to advising on clinical trial design, data analysis strategies, and implementation of digital health tools in research settings. He has contributed to numerous studies examining healthcare resource utilization, drug development economics, and policy implications of neurological disorders. As a leader in CHeT Innovation, Dr. Dorsey oversees initiatives that deploy smartphones, wearables, and radio-wave sensors in fully virtual studies to enable trial participation from anywhere. His team has conducted over 30 studies involving virtual assessments with more than 3,500 participants, demonstrating these approaches are feasible, effective, and well-liked by both patients and providers.

Lorne A. Nelsonمشاهده پروفایل

استاد

• Interacting Binary Stars
• Type Ia Supernovae
• Millisecond Pulsars
• +۵ مورد دیگر

Lorne A. Nelson is a Professor of Physics at Bishop's University, where he joined as an Assistant Professor in 1988 and was promoted to full Professor in 1998. He has served as Chair of the Physics Department during two separate terms (1996-1998 & 1999-2001). His research focuses on the theoretical aspects of stellar evolution, particularly in binary systems containing compact objects such as white dwarfs, neutron stars, and black holes. Nelson received his Ph.D. from Queen's University in 1984. He subsequently held a postdoctoral fellowship at MIT's Center for Space Research, where he conducted pioneering work on brown dwarfs. From 1986-1988, he was a research fellow at CITA (Canadian Institute of Theoretical Astrophysics). Professor Nelson's research interests center on interacting binary stars, Type Ia supernovae, millisecond pulsars, and brown dwarfs. His work provides insights into the formation and evolution of binary systems, with applications to understanding dark matter, testing general relativity, and explaining exotic astronomical phenomena. He employs population synthesis and stellar evolution techniques to develop self-consistent models of binary evolution that can be tested against observational data from instruments like HST, Chandra, and Keck. Analysis of Nelson's publication record reveals a consistent focus on binary stellar evolution across four decades. His work demonstrates progression from foundational studies of brown dwarfs and very low-mass stars to sophisticated modeling of binary millisecond pulsars, cataclysmic variables, and Type Ia supernova progenitors. A recurring theme is the development of theoretical frameworks that connect stellar evolution with observable phenomena, particularly through population synthesis techniques that bridge theoretical predictions with observational constraints. Canada Research Chair in Astrophysics (2002) William & Nancy Turner (Chancellor's) Teaching Award (1996) Invited Contributor to Nature's News & Views (1995) Reinhardt Fellowship from CITA (1999) Invited Review Speaker at multiple international conferences Professor Nelson has advised numerous graduate students who have gone on to successful careers in academia and industry, including Kirk Buckley (NSERC PDF at Berkeley), Chris Burns (Assistant Professor at Swarthmore), and Drew MacCannell (PhD student at UCSD). His research has been supported by significant grants including the Canada Foundation for Innovation, NSERC, and the Ministère de la Recherche, de la Science et de la Technologie of Quebec. Nelson collaborates extensively with researchers at MIT, UCSB, Northwestern, and other institutions worldwide. Nelson leads the Bishop's University Interacting Binary Evolution Server, a valuable resource for the international astrophysics community that provides evolutionary tracks for low-mass interacting binaries. He also co-developed the Elix2 Beowulf cluster in collaboration with the Université de Sherbrooke, creating a high-performance computing environment for theoretical astrophysics research. His team produces detailed animations of binary evolution that serve both research and educational purposes.

Thomas Eiterمشاهده پروفایل

استاد

• Artificial Intelligence
• Knowledge Representation and Reasoning
• Computational Logic
• +۷ مورد دیگر

Thomas Eiter is a Full Professor at the Institute of Logic and Computation, Technical University of Vienna (TU Wien), where he serves as Head of Research Unit. He is a Full Member of the Division of Mathematics and Natural Sciences since 2022 and holds leadership roles within the university. His research focuses on knowledge representation and reasoning, computational logic, algorithms and complexity in AI, declarative problem solving, nonmonotonic logic programming and databases, and reasoning about actions and change. His work bridges theoretical foundations with practical applications in artificial intelligence, particularly in logic programming and knowledge-based systems. He has made significant contributions to Answer Set Programming (ASP), developing frameworks like DLV and HEX programs that enable sophisticated reasoning capabilities. His recent publications demonstrate a strong focus on stream reasoning (LARS framework), knowledge forgetting, modular reasoning systems, and the integration of logic programming with ontologies. His research shows consistent contributions to both theoretical foundations and practical implementations of AI systems over several decades. ACM Fellow (2020) Fellow of the European Association for AI (2006) Distinguished Paper Award of the 17th International Joint Conference on Artificial Intelligence (IJCAI, 2001) Prominent Paper Award of the Artificial Intelligence Journal (2013) Test of Time Award (10 years) of the International Conference on Logic Programming (2013) Eiter has led and participated in numerous research projects, both internationally funded (such as LogiCS@TUWien, Humane AI, AI4EU) and nationally funded (including projects like BILAI, TAIGER, and several FWF-funded initiatives). His research unit has received substantial support from European Commission programs (H2020) and Austrian funding agencies (FWF, FFG, WWTF). He is actively involved in the academic community as a member of the Austrian Academy of Sciences (ÖAW), Academia Europaea, and has served on the Executive Council of AAAI. His research unit maintains strong connections with international collaborators and has developed influential systems like the DLV answer set programming system.

Benjamin C. Pierceمشاهده پروفایل

استاد

• Programming Languages
• Type Systems
• Language-based Security
• +۵ مورد دیگر

Benjamin C. Pierce is the Henry Salvatori Professor of Computer and Information Science in the School of Engineering and Applied Science at the University of Pennsylvania. As a Fellow of the ACM, he has made significant contributions to programming language theory and formal methods. His academic leadership includes previous editorial roles as co-Editor in Chief of the Journal of Functional Programming and Managing Editor for Logical Methods in Computer Science. His research spans multiple interconnected domains in programming language theory, with particular emphasis on type systems and their applications to security and verification. Pierce's work bridges theoretical foundations with practical implementations, most notably through his development of the Unison file synchronization tool and contributions to the Clowdr virtual conference platform. His research interests form a cohesive trajectory from foundational type theory to applied security and verification techniques. Pierce's scholarly output shows consistent focus on property-based testing, type systems, and formal verification methods. His recent publications demonstrate evolving interests in differential privacy verification, synchronization technologies, and the practical challenges of implementing formal methods in real-world systems. The progression of his work reflects both theoretical depth and practical relevance to software development challenges. Fellow of the ACM Author of influential textbooks Types and Programming Languages and Software Foundations Lead designer of the Unison file synchronizer Co-developer of the Clowdr virtual conference platform Former editorial leadership for multiple prominent programming languages journals As an educator and mentor, Pierce has contributed to the Programming Languages Mentoring Workshop (PLMW) and has served on numerous conference program committees. His academic service extends to SIGPLAN leadership roles including SIGPLAN Vice Chair and Steering Committee membership. His textbook Software Foundations has become a standard resource for teaching formal methods and proof assistants.

Aljaž Božičمشاهده پروفایل

پژوهشگر

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

Aljaž Božič is a Research Scientist at Meta Reality Labs Research , focusing on neural rendering, 3D reconstruction, and AI-driven geometry modeling. He earned his Ph.D. in Computer Science from the Technical University of Munich (TUM) and holds a Master's in Computer Science from TUM and a Bachelor's in Mathematics from the University of Ljubljana . His research spans computer vision, graphics, and artificial intelligence , with a focus on neural rendering , generative AI , and 3D deformable object modeling , targeting applications in VR/AR and robotics. His work includes time-consistent dynamic scene reconstruction (SceNeRFlow), volumetric hair appearance modeling, and high-fidelity walkable VR spaces (VR-NeRF), alongside efficient NeRF distillation and calibration methods (Neural Lens Modeling). Key article trends include Transformer-based monocular reconstruction (TransformerFusion), neural parametric shape models (NPMs), and self-supervised non-rigid tracking (Neural Deformation Graphs). He has contributed to open-source projects like the TransformerFusion GitHub repository , emphasizing MIT-licensed tools for scene reconstruction. At TUM, he served as a Teaching Assistant for courses such as 3D Scanning and Spatial Learning and 3D Vision Seminar , bridging academic instruction with research innovation. His work integrates advanced neural networks with practical optimization techniques, advancing fields like RGB-D reconstruction (DeepDeform) and variational SLAM.

Giovanni Maria Farinellaمشاهده پروفایل

استاد

• First Person (Egocentric) Vision
• Computer Vision
• Pattern Recognition
• +۱ مورد دیگر

Giovanni Maria Farinella is a Full Professor at the Department of Mathematics and Computer Science, University of Catania, Italy. He is the Founder Member of the IPLAB Research Group at University of Catania since 2005, an Associate Member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006, and an Associate Member of the Italian National Research Council since 2018. He serves as Scientific Advisor of the NVIDIA AI Technology Centre and board member of the CINI Laboratory of Artificial Intelligence and Intelligent Systems. Dr. Farinella obtained his degree in Computer Science (summa cum laude) from the University of Catania in 2004 and was awarded a Doctor of Philosophy (Computer Vision) from the same institution in 2008. He has obtained the National Scientific Qualification to Associate Professor in 2013-2014 and to Full Professor in 2018. His primary research interests focus on First Person (Egocentric) Vision, Computer Vision, Pattern Recognition, and Machine Learning. Dr. Farinella has pioneered research in egocentric video analysis, object interaction detection, activity recognition, and scene understanding from a first-person perspective. His work bridges theoretical computer vision with practical applications in industrial settings, healthcare, and cultural heritage sites. His recent publications demonstrate a clear trajectory toward more sophisticated, real-time egocentric vision systems capable of understanding complex human activities, anticipating actions, and detecting procedural mistakes through integration of visual analysis, gaze tracking, and large language models. Dr. Farinella has published extensively in top-tier computer vision venues, with his most recent work focusing on egocentric action anticipation, mistake detection in procedural tasks, and the integration of multimodal large language models with visual understanding. His research shows strong emphasis on practical industrial applications while advancing fundamental computer vision techniques. PAMI Mark Everingham Prize 2017 Intel's 2022 Outstanding Researcher Award Dr. Farinella has served as Associate Editor for IEEE Transactions on Pattern Analysis and Machine Intelligence, Pattern Recognition - Elsevier, and International Journal of Computer Vision. He has held leadership roles as Area Chair for CVPR 2020/21/22/23, ICCV 2017/19/21/23, ECCV 2020, and as Program Chair of ECCV 2022. He founded and directs the International Computer Vision Summer School (since 2006) and the Medical Imaging Summer School (since 2014). As PI of the EGO4D project, he helped create one of the largest egocentric video datasets with over 3,670 hours of footage from 923 participants across 74 locations worldwide. His IPLAB research group leads multiple significant projects including VALUE, ENIGMA, and FIPEVIS, with strong industry collaborations.

• Cognitive Science
• Visual Perception
• Attention
• +۵ مورد دیگر

Dr. Elisabeth Hein is a Scientific Assistant and Post-doctoral Fellow at the Evolutionary Cognition Research Group within the Department of Psychology, Faculty of Science, University of Tübingen. She holds a PhD in Psychology (2006, University of Tübingen) and a Master’s in Cognitive and Experimental Psychology (2002, Université Louis Pasteur, Strasbourg). Her research focuses on object cognition , visual perception , and the role of attention and features in resolving motion correspondence in dynamic displays. She has secured multiple competitive grants from the Deutsche Forschungsgemeinschaft (DFG) and the Volkswagen-Stiftung . Education : PhD in Psychology, University of Tübingen (2006) Master’s in Cognitive and Experimental Psychology, Université Louis Pasteur, Strasbourg (2002) Licence in Psychology, Université Louis Pasteur, Strasbourg (2001) Her recent work explores cross-modal correspondence (auditory-visual parallels), scene-based motion processing , and the neural mechanisms of attention in perceptual integration. She has authored peer-reviewed publications in journals like Journal of Experimental Psychology , Attention, Perception & Psychophysics , and Journal of Vision . Scientific Awards : 2020 DFG Continuation Research Grant 2014 DFG Research Grant 2008 Volkswagen-Stiftung Fellowship 2002-2005 DFG Graduate Fellowship Elisabeth Hein serves as a peer reviewer for journals including Acta Psychologica and Psychonomic Bulletin & Review , and has organized conferences and committees such as the Vision Sciences Society and European Conference on Visual Perception . She also contributes to student advisory services and academic governance at the University of Tübingen.