جست‌وجوی استاد و پژوهشگر

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

Gerard Pons-Moll is a Professor at the University of Tübingen, endowed by the Carl Zeiss Foundation, and heads the Emmy Noether independent research group 'Real Virtual Humans'. He is a core faculty member at the Tübingen AI Center, a senior researcher at the Max Planck Institute for Informatics (MPII), and faculty at the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and the Saarland Informatics Campus. His research focuses on computer vision, graphics, and machine learning, particularly in creating virtual human models and analyzing human motion from video and sensor data. Education: PhD (with distinction) in 2014 from Leibniz University of Hannover, Master's in Telecommunications Engineering (Northeastern University, 2008), and B.S./M.Sc. in Telecommunications Engineering from the Technical University of Catalonia (2002–2008). Research Interests: 3D human modeling, pose estimation, human-object interaction, and applications in industry and research. His work emphasizes real-world applications like virtual avatars and motion capture systems. Awards: Emmy Noether Grant (2018), German Pattern Recognition Award (2019), Google Faculty Research Award (2019), and multiple best paper awards at top conferences (BMVC’13, Eurographics’17, 3DV'18, CVPR'20). Advising & Grants: Served as program chair of 3DV 2021, area chair for ECCV, CVPR, and IJCAI. Active in reviewing for DFG, ANR, and ISF. Supervises research in areas like neural rendering frameworks (Blendify) and synthetic data generation (STAGE). Labs/Teams: Leads the Emmy Noether group and collaborates with MPII, Tübingen AI Center, and IMPRS-IS on projects like XNect (real-time 3D motion capture) and Human 3Diffusion (avatar creation).

Jennifer Hicksمشاهده پروفایل

استاد پژوهشی

• Biomechanical Modeling
• Machine Learning in Biomechanics
• Musculoskeletal Dynamics
• +۳ مورد دیگر

Jennifer Hicks is the Executive Director of the Wu Tsai Human Performance Alliance at Stanford University, focusing on collaborative research to advance understanding of human performance through biomechanical modeling and machine learning. She also serves as Director of Research for the NIH-funded Mobilize Center and Restore Center, integrating engineering tools into rehabilitation science. Her work emphasizes predictive modeling of surgical outcomes, mobile health data analysis, and exoskeleton design. Dr. Hicks leads software development for the OpenSim project, guiding its user-centric evolution and promoting open-source biomedical tools. Her research spans musculoskeletal dynamics, wearable technology, and clinical applications of AI. Key contributions include smartphone-based motion capture (OpenCap) and foundational datasets like AddBiomechanics. She co-develops training programs for interdisciplinary teams and advocates for large-scale health data utilization. Dr. Hicks' efforts bridge academia and industry, supporting translational research in neurorehabilitation, sports performance, and chronic disease management.

• Virtual Reality
• Human-Computer Interaction
• Computer Vision
• +۴ مورد دیگر

Robert S. Allison is a Professor in the Department of Electrical Engineering & Computer Science at York University's Lassonde School of Engineering. His research focuses on human perceptual responses in virtual environments, stereoscopic vision, and eye movement analysis. He is affiliated with the York Centre for Vision Research, Sensorium (Digital Arts & Technology), and the Centre for Innovation in Computing at Lassonde. His research interests include depth perception in natural and virtual environments, human-computer interface design for VR, machine vision applications, and the measurement of human motion. He has supervised multiple graduate students and contributed to over 260 publications. His work spans topics like cybersickness mitigation, display lag effects, and perceptual adaptation in VR. Key grants include NSERC-funded projects on perception in virtual environments and collaborations with institutions like the Australian Research Council. His teaching includes courses on human perception in human-computer interaction and digital logic design. Recent articles highlight advancements in understanding motion perception, VR-induced sickness, and multisensory integration. He collaborates widely, with affiliations including the VISTA program and York's Connected Minds initiative.

Chung-Hsing Yehمشاهده پروفایل

دانشیار

• Multicriteria Decision Analysis
• Applied Artificial Intelligence
• Intelligent Decision Support Systems
• +۶ مورد دیگر

Chung-Hsing Yeh is an Associate Professor at Monash University's Faculty of Information Technology, Department of Data Science & AI. He holds a visiting professorship at National Cheng Kung University, Taiwan, and has extensive experience in academic roles including Chief Examiner and Lecturer for numerous IT and business-related courses. His research focuses on multicriteria decision analysis, applied artificial intelligence, fuzzy logic, neural networks, and sustainable operations management. He has led collaborative projects on e-waste recycling, supply chain optimization, and public health policy, funded by organizations like the Ministry of Science and Technology (Taiwan) and the Australian Research Council. Education: PhD in Operations Research/Information Systems, Monash University (1988) MSc in Management Science, National Cheng Kung University (1982) BSc (Engineering) in Industrial Design, National Cheng Kung University (1977) Research Interests: His work spans decision support systems, optimization modeling, transport research, and recycling operations. Notable contributions include algorithms for production scheduling, AI-driven solutions for healthcare, and sustainable e-waste management strategies. Awards: Listed in Marquis Who's Who in the World Listed in Who's Who in Finance and Industry Listed in Who's Who in Science and Engineering Grants & Projects: Led 6 major projects, including 'Maximizing E-waste Recycling Profitability' (2019–2020) and 'Smoke-Free Policy Effectiveness' (2007–2010). Active in grant review roles for ARC and the Netherlands Organisation for Scientific Research. Teaching: Overseeing courses such as Fundamentals of Artificial Intelligence, Business Intelligence Modelling, and Management Information Systems.

• Computer Science
• Artificial Intelligence
• Machine Learning
• +۱۲ مورد دیگر

Hao Liu is a researcher affiliated with institutions like Chinese Academy of Sciences , Beihang University , and Stanford University . His work spans Computer Science , Artificial Intelligence , and Robotics . Key affiliations: National Space Science Center (Beijing), School of Astronautics (Beihang), Key Laboratory of Pervasive Computing (Tsinghua) Research interests include Machine Learning , Image Processing , Graph Neural Networks , and Wireless Communication Optimization His recent publications focus on: Advanced control systems for fuzzy models Medical imaging via hyperspectral analysis Transformer-based approaches in NLP and vision Quantum-safe and edge computing protocols

• Machine Learning
• Computer Vision
• Signal Processing
• +۶ مورد دیگر

Dongwook Kim is affiliated with the Korea Advanced Institute of Science & Technology (KAIST) as a faculty member in the Department of Business and Technology Management under the College of Business. His research spans multiple domains including machine learning, robotics, signal processing, and biomedical engineering. Key contributions in Computer Vision (CNN-based semantic segmentation, 3D point cloud analysis) Significant work in Hardware Design (energy-efficient processors, neuromorphic computing) Interdisciplinary expertise in Medical Imaging (bone age assessment, retinal biomarkers) and Cybersecurity (attack detection, network analytics) Publications since 2015 demonstrate sustained innovation in AI applications , Signal Processing , and Smart City Governance . His work often integrates theoretical advances with practical implementations in real-world systems. No scientific awards or student mentorship details are explicitly documented in the provided records.

• Video Coding
• Machine Learning
• FPGA Acceleration
• +۳ مورد دیگر

Jarno Vanne is a Professor at the Department of Computing Sciences, Faculty of Information Technology and Communication Sciences at Tampere University. His research focuses on video coding standards, real-time systems, and hardware acceleration, particularly in the context of FPGA implementations and open-source tools. He leads projects involving VVC (Versatile Video Coding), V-PCC (Volumetric Video Coding), and HEVC (High Efficiency Video Coding), with an emphasis on efficiency, low latency, and machine learning integration. Key research interests include point cloud compression, saliency-guided encoding, parallelization schemes, and real-time video communication protocols. His work often addresses challenges in multi-party video streaming, embedded systems, and encryption mechanisms for privacy protection. He has contributed to open-source projects like the UVG dataset, Kvazaar encoder, and CiThruS simulation frameworks. Recent publications highlight advancements in VVC intra encoding optimizations, machine learning-driven partitioning schemes, and FPGA-accelerated solutions for edge computing. His research bridges theoretical video coding algorithms with practical implementations, aiming to improve compression efficiency while maintaining real-time performance.

Julie Dorseyمشاهده پروفایل

استاد

• Computer Graphics
• Photorealistic Image Synthesis
• Material and Texture Modeling
• +۴ مورد دیگر

Julie Dorsey is the Frederick W. Beinecke Professor of Computer Science at Yale University, where she teaches computer graphics. She joined Yale in 2002 after holding tenured positions at MIT in both the Department of Electrical Engineering and Computer Science and the School of Architecture. She earned undergraduate degrees in architecture and graduate degrees in computer science from Cornell University. Research Areas: Photorealistic image synthesis Material and texture modeling Interactive visualization of complex scenes Sketch-based design interfaces Acoustical and lighting design algorithms Recent Article Trends focus on AI-driven graphics techniques, 3D hair modeling, depth sensing, and cultural heritage preservation. These works reflect her interdisciplinary approach bridging computer science, art, and physics. Scientific Awards: MIT Edgerton Faculty Achievement Award NSF Career Award Alfred P. Sloan Research Fellowship Radcliffe Institute Fellowship (2010-11) Whitney Humanities Center Fellowship (2010-12) Editorial Contributions: She serves as Editor-in-Chief of ACM Transactions on Graphics and has held editorial roles at Computers and Graphics, Foundations and Trends in Computer Graphics and Vision, and SIGGRAPH 2006 Papers Chair. Labs & Collaborations: Leads Yale's Computer Graphics Group, contributes to interdisciplinary projects at the intersection of computing and the arts, and collaborates with researchers in biomedical and industrial AI applications.

• Cloud Computing
• Green Computing
• High-Performance Computing
• +۷ مورد دیگر

Jordi Guitart Fernández is a Professor at the Department of Computer Architecture, Barcelona School of Informatics (FIB), Universitat Politècnica de Catalunya (UPC). He is also affiliated with the Barcelona Supercomputing Center (BSC-CNS), a leading national supercomputing facility. He leads the CROMAI research group, focusing on Computing Resources Orchestration and Management for AI. His work bridges high-performance computing, cloud systems, and artificial intelligence. Research Interests: Cloud Computing and Edge Computing Green and Energy-Efficient Computing Containerization and Virtualization for HPC Resource Orchestration and Management Autonomic and Self-Adaptive Systems Machine Learning Workflow Management AI-Driven System Optimization His recent publications reveal a strong focus on intelligent management of computing resources across cloud, edge, and HPC environments using machine learning and agent-based frameworks. He investigates performance, efficiency, and reliability in containerized AI and HPC workloads, particularly within Kubernetes and distributed infrastructures. His work increasingly integrates human-in-the-loop and trustworthiness aspects into AI systems. Scientific Awards: CLOUD Conference 2025 Best Paper Award VISIGRAPP 2025 Best Student Paper Award Premi Extraordinari de Doctorat 2025 - Àmbit d'Enginyeria de les TIC Test of Time Award Honorable Mention (e-Energy) Reconeixement als Mèrits Docents d'Especial Qualitat Top reviewers for Polytechnic University of Catalonia (Computer Science) - September 2017 Advising and Grants: He has advised doctoral students, including Peini Liu. He leads and participates in numerous competitive R+D+i projects, such as CROMAI and DALEST, funded by national and European programs like HORIZON 2020 and the Spanish State Research Plans. His work is supported by grants focused on knowledge generation and industrial leadership in computing technologies. Labs and Teams: He is the leader of the CROMAI - Computing Resources Orchestration and Management for AI research group at UPC. He also collaborates closely with the Barcelona Supercomputing Center (BSC-CNS), contributing to large-scale computing initiatives and strategic research agendas in Europe.

Kenneth A. Reinertمشاهده پروفایل

استاد

• International Economics
• Trade Policy
• Economic Development
• +۹ مورد دیگر

Kenneth A. Reinert is Professor of Public Policy at the Schar School of Policy and Government, George Mason University. He previously served as Director of the Global Commerce and Policy Program from 2007 to 2010 and again from 2013 to 2022, demonstrating sustained leadership in global economic policy education. His educational background includes a Ph.D. in Economics from the University of Maryland. Prior academic and professional roles include Associate Professor of Economics at Kalamazoo College and Senior International Economist at the U.S. International Trade Commission. Reinert's research centers on international economics, trade policy, economic development, globalization, and the universal provision of basic goods . His work bridges theoretical and applied economics, with a strong emphasis on policy relevance and human development. He explores how trade and economic integration affect inequality, sustainability, and access to essential services in developing nations. His recent publications reveal a thematic evolution from technical trade analysis toward broader critiques of economic nationalism and visions for equitable global development. Books like No Small Hope and The Lure of Economic Nationalism reflect a growing focus on ethical dimensions of globalization and inclusive economic frameworks. Scientific Awards: School of Public Policy Distinguished Teaching Award (2003) Reinert has advised major international institutions through consulting roles with the World Trade Organization, World Bank, OECD Development Centre, and U.S. Department of Commerce , indicating sustained engagement with global policy formulation. While no formal grants are listed, these affiliations imply participation in funded policy research initiatives. He has mentored students and early-career scholars, though specific advisees are not named in the provided texts. He currently serves as editor of Cambridge Elements in International Economics and has led major editorial projects, including the Princeton Encyclopedia of the World Economy and the Handbook of Globalisation and Development , positioning him as a key contributor to academic discourse in global economic policy.

Nikolaus Kriegeskorteمشاهده پروفایل

استاد

• Computational Neuroscience
• Artificial Neural Networks
• Visual Perception
• +۳ مورد دیگر

Nikolaus Kriegeskorte is a Professor of Psychology and Neuroscience, and Director of Cognitive Imaging at the Mortimer B. Zuckerman Mind Brain Behavior Institute at Columbia University. He is affiliated with the Departments of Psychology, Neuroscience, and Electrical Engineering. Institution: Columbia University Academic Roles: Professor of Psychology and Neuroscience; Director of Cognitive Imaging Email: nk2765@columbia.edu Location: Jerome L. Greene Science Center, 3227 Broadway, L3-064 Research Focus: The lab explores the cognitive neuroscience of vision, modeling biological visual systems with artificial neural networks. Key areas include developing statistical inference and visualization techniques to bridge theory and experimental data, understanding representational geometry in neural systems, and optimizing deep learning frameworks for neuroscience. Recent Publications: Highlighted work spans neural network modeling of visual perception, representational similarity analysis, and the topology of brain representations. The lab's methods, such as the TorchLens Python package, enable transparent extraction and visualization of hidden layer activations in neural networks. Grants: Projects are supported by funding from the National Science Foundation (NSF) - Cognitive Neuroscience and the National Institutes of Health (NIH) - NIMH. Laboratory: The Visual Inference Lab (kriegeskortelab.zuckermaninstitute.columbia.edu) is located at Quad 3D, Zuckerman Institute, 3227 Broadway.

Huaizu Jiangمشاهده پروفایل

استادیار

• Computer Vision
• Computer Graphics
• Natural Language Processing
• +۵ مورد دیگر

Huaizu Jiang is an Assistant Professor at Khoury College of Computer Sciences, Northeastern University. His research bridges computer vision, graphics, and natural language processing to develop AI systems that understand and reconstruct 3D visual environments. Prior to joining Northeastern, he was a Postdoc Researcher at Caltech and Visiting Researcher at NVIDIA. He holds a Ph.D. from UMass Amherst (advised by Prof. Erik Learned-Miller), and M.E./B.E. degrees from Xi'an Jiaotong University. His research focuses on fundamental challenges in 3D scene understanding, including geometry reconstruction, semantic interpretation, novel view synthesis, motion generation, and optical flow estimation. Core interests span video processing, human-object interactions, multimodal reasoning, and efficient edge-device implementations. Recent publications emphasize diffusion models for motion/scene generation, transformer-based 3D perception, and video interpolation. Key trends include multi-view consistency techniques, text-to-3D synthesis, and efficient real-time algorithms for robotics applications. Awards & Honors: Winner of the VQA Challenge 2020 He advises 15+ graduate students on projects spanning 3D reconstruction, motion synthesis, and vision-language models. His group collaborates with institutions like NVIDIA and Caltech, focusing on generative AI for dynamic scene understanding.

• Artificial Intelligence
• Computer Gaming and Animation
• Computer Graphics
• +۴ مورد دیگر

Yingying Wang is an Assistant Professor in the Computing and Software department at McMaster University , where she joined in January 2022. Her research focuses on generating expressive animations for AR/VR applications and games through interdisciplinary approaches combining Computer Graphics , Artificial Intelligence , and Human Behavior Analysis . Education : Bachelor and Master degrees from Nanjing University , Ph.D. from University of California, Davis (2017) Her research explores: Generative models for human motion style transfer Physics-based motion simulation Audio-driven character synthesis Dance choreography for virtual characters Cartoon animation perception Conversational character gesture synthesis Markerless hand motion capture Recent publications focus on 3D hand pose estimation , motion style transfer , gesture-locomotion coordination , and personality perception in virtual agents . Key methodologies include deep learning , multimodal data analysis , and real-time animation systems . Scientific contributions recognized through: $240,000 Labarge Catalyst Grant in Mobility in Aging (interdisciplinary team award) US Patent 10,796,482 (3D hand pose estimation) US Patent 9,811,937 (gesture-locomotion coordination) Teaching includes graduate and undergraduate courses in Computer Animation (CAS 737), Computer Graphics (COMPSCI 3GC3/SFWRENG 3GC3), and Software Development (COMPSCI 2ME3). Research group actively recruits Ph.D. and Master's students in graphics + deep learning domains.

Eva Cetinicمشاهده پروفایل

پژوهشگر

• Deep Learning
• Explainable AI
• Digital Art
• +۵ مورد دیگر

Dr. Eva Cetinic is a DSI Bridge Postdoc Fellow at the University of Zurich, conducting research at the intersection of deep learning, explainable AI, and digital art and humanities. Previously, she held postdoctoral positions at Durham University and the Center for Digital Visual Studies at the University of Zurich, and worked as a Professional Associate and Postdoc at the Rudjer Boskovic Institute in Croatia from 2015 to 2021. Her educational background includes: PhD in Computer Science, University of Zagreb (2019) Dr. Cetinic's research focuses on computational image understanding and multimodal learning for visual art and culture, investigating how text-image models encode socio-cultural patterns and impact artistic creation. Her work critically examines ethical and societal implications of AI while bridging computer science, digital humanities, and art history through interdisciplinary methodologies. Her publication trends (2019-2025) reveal concentrated analysis of generative AI's cultural impact, particularly text-to-image systems. She systematically investigates bias propagation (gender, cultural), user interaction dynamics, and creative processes while developing technical frameworks for art analysis - moving beyond technical capabilities to address real-world implications in artistic and cultural contexts. She currently leads the UZH-funded project 'From Hype to Reality: Artificial Intelligence in the Study of Art and Culture' in collaboration with the University of Cambridge, establishing cross-institutional frameworks for responsible AI adoption. Her research methodology emphasizes practical implementation within humanities workflows through international networks like DARIAH. As a DSI Bridge Postdoc Fellow, Dr. Cetinic operates within the University of Zurich's Digital Society Initiative ecosystem, connecting computational research with the Center for Digital Visual Studies and global digital humanities infrastructures to examine AI's transformative role in cultural production and interpretation.

• Anthropology of Science and Technology
• Computer Supported Collaborative Work
• Digitalization
• +۹ مورد دیگر

Vidar Hepsø is a Professor at the Department of Computer Technology and Informatics, Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology (NTNU). His work bridges anthropology of science and technology with practical challenges in digitalization, energy transition, and remote operations. Research focuses on digital infrastructures, socio-technical systems, and human factors in oil and gas industries Active in NTNU Applied Information Technology and NTNU Energy Transition Initiative Publications emphasize open-source ecosystems, autonomous systems, and environmental monitoring His scholarly output spans computer-supported collaborative work, IT infrastructure governance, and risk-informed anomaly detection in subsea systems. He leads projects connecting digital innovation with offshore wind and petroleum geoscience.