جست‌وجوی استاد و پژوهشگر

Tianhao Wangمشاهده پروفایل

استادیار

• Differential Privacy
• Machine Learning Privacy
• Data Security
• +۳ مورد دیگر

Tianhao Wang is an Assistant Professor in the Department of Computer Science at the University of Virginia School of Engineering and Applied Science. His work focuses on advancing differential privacy and machine learning privacy, with particular expertise in privacy-preserving technologies for data synthesis, adversarial machine learning, and secure AI systems. His research interests span differential privacy mechanisms, secure data sharing, and mitigating privacy risks in modern AI systems. He explores how to protect sensitive information in machine learning models, synthetic data generation, and network analysis while maintaining utility. Recent work highlights include developing benchmarks for private image synthesis (DPImageBench), safeguarding text data from misuse (ExpShield), and analyzing privacy threats in pre-trained language models. His publications reflect a strong emphasis on both theoretical foundations and practical applications of privacy-preserving techniques. Dr. Wang's contributions address cutting-edge challenges in AI ethics, secure machine learning, and privacy engineering, with implications for healthcare, cybersecurity, and data-driven decision-making systems.

Chenliang Xuمشاهده پروفایل

دانشیار

• Computer Vision
• Audio-Visual Learning
• Vision and Language
• +۵ مورد دیگر

Chenliang Xu is an Associate Professor in the Department of Computer Science at the University of Rochester, affiliated with the Goergen Institute for Data Science and Artificial Intelligence (GIDS-AI). His research focuses on computer vision, audio-visual learning, and trustworthy AI. He holds a PhD from the University of Michigan (2016), with prior degrees from Nanjing University of Aeronautics and Astronautics and the University at Buffalo. Notable awards include the Best Paper Award at ACCV 2024 and the James P. Wilmot Distinguished Professorship. His work spans interdisciplinary topics such as video understanding, multimodal reasoning, and robust AI. Key research contributions include audio-visual scene synthesis, bias mitigation in models, and applications in public health. He has secured over $3M in grants, including NIH funding for AI-driven video description tools and public health initiatives. Prof. Xu advises a dynamic research group with 11 PhD students and numerous collaborators. His lab explores cutting-edge projects like egocentric audio-visual understanding, generative AI for avatars, and multimodal defense mechanisms. He teaches courses in machine vision, deep learning, and advanced computer vision.

Wenzhuo Zhouمشاهده پروفایل

استادیار

• Machine Learning
• Artificial Intelligence
• Reinforcement Learning
• +۱۶ مورد دیگر

Wenzhuo Zhou is an Assistant Professor in the Department of Statistics at the University of California, Irvine (UCI), affiliated with the Donald Bren School of Information & Computer Sciences. His research bridges machine learning theory and practice, focusing on reinforcement learning, deep representation learning, and large language models. He emphasizes developing efficient, reliable AI algorithms to address challenges in healthcare, finance, and robotics. Research Interests: Statistical foundations of learning algorithms Sample efficiency and model generalization Alignment of AI models with human preferences Applications in healthcare (e.g., cancer, diabetes, Alzheimer’s), finance, and robotics Collaborations involve domain experts in medical research, semantic search, and financial systems. His team adapts existing methods and develops new pipelines for real-world problem-solving. No scientific awards or grants are explicitly listed in the provided text. Advising details are mentioned but without specific student names. The Center for Statistical Consulting is part of his professional environment.

Ziquan Liuمشاهده پروفایل

مدرس

• Reliable Machine Learning
• Uncertainty Quantification
• Computer Vision
• +۴ مورد دیگر

Dr. Ziquan Liu is a Lecturer (Teaching & Research) at Queen Mary University of London's School of Electronic Engineering and Computer Science, affiliated with the Centre for Multimodal AI. He holds a PhD from City University of Hong Kong (2023) and dual B.Sc./B.Eng. degrees from Beihang University (2017). His research focuses on trustworthy machine learning, adversarial robustness, and uncertainty quantification in foundation models. He has served as a reviewer for top conferences like NeurIPS, ICLR, and CVPR, earning an Outstanding Reviewer Award in 2021. His teaching includes modules on machine learning for visual data analysis and principles of machine learning. He supervises PhD students in AI safety and reliability, with notable work on conformal prediction, adversarial attacks, and multimodal learning. His research outputs span top venues such as ICML, CVPR, and NeurIPS, addressing challenges in algorithmic fairness, model certification, and cross-modal alignment.

Stephen Leeمشاهده پروفایل

استادیار

• Computer Systems
• Cyber-Physical Systems
• Data Mining and Data Science
• +۳ مورد دیگر

Stephen Lee is an Assistant Professor in the Department of Computer Science at the University of Pittsburgh, affiliated with Pitt Cyber. His research focuses on distributed systems, cyber-physical systems, and sustainability, emphasizing energy efficiency and cost optimization. Dr. Lee holds a PhD from the University of Massachusetts Amherst, a Master’s from Chennai Mathematical Institute, and a Bachelor’s from St. Stephen’s College, Delhi. He actively seeks students for his research group. Education: PhD, Computer Science, University of Massachusetts Amherst Master’s, Chennai Mathematical Institute Bachelor’s, St. Stephen’s College, Delhi Research Interests: Dr. Lee’s work integrates distributed systems, machine learning, and optimization to enhance sustainability. Key areas include IoT-enabled energy systems, emission-aware computing, and privacy-preserving frameworks. He leads projects like GreenWhisk (serverless emission reduction) and Sat2map (3D building modeling from satellite imagery). Recent Achievements: Best Paper Award in IEEE TPS 2024 DOE-funded Cyber Energy Center (2024) MCSI Seed Grant for Pitt building sustainability (2024) NSF Grant on sustainable distributed infrastructures (2023) Grants & Advising: Secured over $2M in grants, including NSF and DOE funding. Advises on energy-efficient systems and IoT security. Teaches CS 2510 (Operating Systems) and CS 1699 (Systems & Sustainability). Labs & Teams: Directs the Sustainable Systems Research Group, focusing on decarbonizing IT and optimizing renewable energy systems. Collaborates with industry partners on smart grid solutions and edge-cloud systems.

Svetlana Yanushkevichمشاهده پروفایل

استاد

• Biometric Technologies
• Machine Learning
• Signal Processing
• +۳ مورد دیگر

Dr. Svetlana Yanushkevich is a Professor in the Department of Electrical and Software Engineering at the Schulich School of Engineering, University of Calgary. She is also a Full Member of the Hotchkiss Brain Institute and the Mathison Centre for Mental Health Research and Education. Her research focuses on biometric technologies, decision support systems, biomedical applications, and computational intelligence. She leads the Biometric Technologies Laboratory, developing strategies for risk assessment in biometric systems and healthcare monitoring through machine reasoning and signal processing. Education : BSc/MSc in Electrical Engineering (1989), State University of Informatics and Radioelectronics, Minsk PhD in Electrical Engineering (1992), same institution Dr. Habilitated in Technical Sciences (1999), Warsaw University of Technology Research Interests : Dr. Yanushkevich’s work spans biometric system design (e.g., gait analysis, facial attributes), decision support via probabilistic models (Bayesian networks, causal inference), biomedical applications (stroke rehabilitation, wearable sensors), and computational intelligence for data science. She emphasizes fairness, bias mitigation, and trustworthiness in AI systems, particularly in healthcare and accessibility contexts. Recent Research Trends : Her recent publications address causal modeling for accessibility barriers, UAV operator cognitive workload, and medical device optimization in radiation therapy. She explores AI ethics, stress contagion in human-robot teams, and cross-spectral biometric systems. Awards & Recognition : 2024 FEIC Fellow (Engineering Institute of Canada) 2019 Research Excellence Award (Schulich School of Engineering) 2001 Senior IEEE Membership Advising & Grants : She coordinates courses like ENCM 509 (Biometric Systems Design) and ENEL 610 (Biometric Technologies). Her research is supported by grants focusing on healthcare AI, accessibility technologies, and computational epidemiology. Labs & Collaborations : Her Biometric Technologies Lab collaborates with institutions like Hokkaido University and the IEEE Computational Intelligence Society. Projects include wearable health monitoring, decision support platforms, and AI-driven epidemiological modeling.

Amanda D. Lotzمشاهده پروفایل

استاد

• Media Industries
• Internet Distribution
• Television Studies
• +۴ مورد دیگر

Amanda D. Lotz is a Professor in the Digital Media Research Centre at Queensland University of Technology (QUT), leading the Transforming Media Industries and Cultures research program. Her work focuses on media industries, internet distribution, and the evolving role of television in society. She holds fellowships from the International Communication Association and the Queensland Academy of Arts and Sciences. Her research examines global streaming services, media policy, and the business strategies shaping contemporary media landscapes. Dr. Lotz earned a Ph.D. in Radio-Television-Film from the University of Texas at Austin, with prior academic roles at Washington University in St. Louis, Denison University, and the University of Michigan (2004–2018). Her expertise spans books like The Television Will Be Revolutionized and Media Disrupted , exploring streaming’s impact on traditional media. She advises on policy, consults for media organizations, and hosts the Media Business Matters podcast. Her research highlights the fragmentation of television audiences, the rise of subscriber-funded platforms, and challenges to cultural policy. Key projects include analyzing Australian TV drama production and the global implications of internet distribution. Her recent work addresses generative AI and metaverse media, emphasizing the transformative role of funding models (advertiser, consumer, government) in media priorities. Awardees include the Mellon Post-Doctoral Fellowship and recognition for her teaching. She actively contributes to global media discourse via interviews with major outlets (BBC, NPR, CNN) and serves as a resource for industry workshops on adapting to digital disruption.

Reimar Lenzمشاهده پروفایل

دانشیار

• Digital Image Processing
• Microscopy Technology
• Videometry
• +۳ مورد دیگر

Prof. Dr.-Ing. Reimar Lenz is an Associate Professor at the Technical University of Munich (TUM) within the TUM School of Computation, Information and Technology. His research focuses on digital image acquisition, cooled cameras for microscopy, color image reconstruction, and videometry. He founded CCD Videometrie GmbH in 1999 and co-developed the 'Arriscan' film scanner, earning a Technical Oscar in 2010. Education: Studied electrical engineering at Technical University of Stuttgart and TUM (diploma 1980). PhD in 1986, habilitation in videometry/image processing (1989). IBM postdoc (1987-1988). Key achievements include the microscanning patent (1990), high-resolution museum cameras (MARC project), and CMOS sensor innovations. Awards include the Academy Scientific & Engineering Award (2010) and Heinz Maier-Leibnitz Medal. Manages CCD Videometrie GmbH and holds adjunct roles. Active in both academia and industry, bridging sensor technology and digital imaging applications.

• machine learning
• robotics
• machine vision
• +۹ مورد دیگر

Dr. Hamidreza Mohades Kasaei is an Associate Professor in the Department of Artificial Intelligence at the University of Groningen, Netherlands. He holds positions in both the Faculty of Science and Engineering and the Faculty of Medical Sciences/UMCG, focusing on Robotics and image-guided minimally-invasive surgery. His work bridges theoretical advances in machine learning with practical robotic applications. Dr. Kasaei's research focuses on developing algorithms for adaptive perception systems through interactive environment exploration and open-ended learning. His specific interests include 3D object perception, grasp affordance detection, object manipulation, and active perception. He has evaluated his research on various robotic platforms including PR2, UR5e, Kinova, Franka robotic arms, and humanoid robots. His work enables robots to learn from past experiences and intelligently interact with non-expert human users using data-efficient techniques. Analysis of his recent publications reveals strong trends toward increasingly sophisticated manipulation capabilities, particularly in dual-arm coordination and handling dense clutter. There's a clear progression toward integrating language models with robotic control systems, as seen in works like 'Lifelong Robot Library Learning' and 'Towards Open-World Grasping with Large Vision-Language Models.' His research consistently addresses real-world challenges in agricultural robotics, assistive technologies, and service robotics applications. Gratama Science Award (2022) Google Research Scholar Award in Machine Learning (2023) Outstanding Associate Editor for IEEE Robotics and Automation Letters (2023) Dr. Kasaei has successfully supervised multiple PhD students including Zhenxing Zhang (thesis on 'Generative Adversarial Networks for Diverse and Explainable Text-to-Image Generation') and Hamed Ayoobi (thesis on 'Explain What You See: Argumentation-Based Learning and Robotic Vision'). His research is supported by significant grants including the Google Research Scholar Award for 'Continual Robot Learning in Human-centered Environments' and various conference organization roles including workshops at RSS 2023 and NeurIPS 2022. He leads the Lifelong Interactive Robot Learning Lab (IRL-Lab), which focuses on six key research directions: Perception and Perceptual Learning, Object Grasping and Manipulation, Lifelong Interactive Robot Learning, Dual-Arm Manipulation, Dynamic Robot Motion Planning, and Exploiting Multimodality. The lab develops cutting-edge approaches for robots to learn in open-ended fashion through interaction with non-expert human users, with applications in assistive robotics for people with disabilities.

Bettina Krausمشاهده پروفایل

استاد

• Architectural Design
• Transformation of Existing Structures
• Building in Existing Contexts
• +۶ مورد دیگر

Professor Bettina Kraus is a prominent architect and academic currently serving as Professor of Design in the Department of Architecture at the State Academy of Fine Arts Stuttgart, where she also chairs the Department of Architecture and serves as a Member of the Senate. Her academic career spans multiple prestigious institutions including TU Berlin, BTU Cottbus, and UdK Berlin, alongside an active architectural practice in Berlin. Her research and teaching focus on the elasticity of existing structures and their potential to adapt to changing programmatic or climatic conditions. Kraus explores how the morphology of architectural types and objects is influenced by context, function, and construction. Her methodology involves transformation strategies based on associative thinking and constructive action, integrating existing and new structures while questioning traditional notions of beauty and perfection. This approach allows her to reinterpret existing structures for contemporary and future requirements while reflecting local cultural identity. Kraus's architectural work demonstrates a consistent focus on transformation, adaptive reuse, and the integration of historical and contemporary elements. Her recent projects include residential buildings in Berlin (Lindenstraße 34-35, Brunnenstraße 19), cultural spaces, and urban interventions that have received numerous awards including the Berlin Architecture Prize (2023) and the Iconic Architecture Award (2019). Berlin Architecture Prize, Award 2023 (Lindenstraße 34.5) Berlin Architecture Prize, Prize 2023 (Malplaquetstraße 19) Iconic Architecture Award, Winner 2019 (Spreestudios) German Design Award 2014 (Medienhaus Schwäbischer Verlag) Architecture Prize Amsterdam, Prize 2010 (4 Towers Osdorp) As an educator, Professor Kraus has mentored numerous award-winning students including Theresa Weigand (ABK Stuttgart), Tom Seeger, and Ralf Hinrichs. Her academic research centers on two key parameters: Program and Typology (examining the Nolli Plan as a typological archive), and Difference and Interface (exploring material properties and surface experiments). Her work has been published extensively in architectural journals and as book chapters, with her most recent publication 'False Friends' currently in progress. Professor Kraus maintains an active architectural practice (Kraus Fischnaller Architects Partnership) in Berlin while contributing to the Board of the Berlin Architecture Prize since 2025.

• Computer Vision
• 3D Pose Estimation
• Human Motion Tracking
• +۴ مورد دیگر

Georgios Pavlakos is an Assistant Professor in the Department of Computer Science at the University of Texas at Austin. Previously, he held postdoctoral positions at UC Berkeley and research roles at the Max Planck Institute and Facebook Reality Labs. Education: PhD in Computer Science from the University of Pennsylvania (advisor: Kostas Daniilidis), undergraduate studies at the National Technical University of Athens (collaboration: Petros Maragos). His research focuses on Computer Vision , particularly advancing 3D/4D human reconstruction, motion tracking, and action recognition using deep learning and transformers. His work bridges theoretical innovation with practical applications in dynamic scene modeling and human-centric AI. Recent publications highlight trends in human-centric 4D modeling , motion decoupling , and 3D pose-driven action recognition . Collaborative efforts at institutions like UC Berkeley and Facebook Reality Labs underscore his interdisciplinary approach.

• Data Mining
• Machine Learning
• Product Recommendation
• +۵ مورد دیگر

Christian Desrosiers is a Research Professor at the Department of Software Engineering and IT, École de technologie supérieure (ÉTS), with a Ph.D. from Polytechnique Montréal. His research focuses on data mining, machine learning, and computer vision, particularly in medical imaging and optical network analysis. Research Units: Zebra Research Chair in Computer Vision for Industrial Applications, LIVE – Interventional Imaging Laboratory, LIVIA – Imaging, Vision and Artificial Intelligence Laboratory Research Axes: Intelligent and autonomous systems, Health technologies His expertise spans medical image analysis, domain adaptation, and computer vision. Recent publications highlight advancements in 3D point cloud learning, MRI harmonization, domain generalization, and real-time segmentation networks. Scientific awards include the prestigious Zebra Research Chair. He has co-supervised over 30 graduate students in topics ranging from optical network diagnostics to brain imaging and machine learning applications.

• Machine Learning
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Prof. Tomaso Fontanini is a researcher at the Department of Engineering and Architecture, University of Parma. His academic contributions span multiple disciplines, including computer science, artificial intelligence, and computer vision. 2025/2026: Deep Learning and Generative Models (Master's in Computer Engineering) 2024/2025: Processing Systems (Bachelor's in Prevention Techniques) 2023/2024: Processing Systems (Bachelor's in Prevention Techniques) 2022/2023: Processing Systems (Bachelor's in Prevention Techniques) Research Focus: His work primarily explores generative models, image synthesis, and style transfer with a strong emphasis on semantic control and attention mechanisms. Recent research has advanced state space models for efficient style transfer (Mamba-ST), semantic image synthesis via class-adaptive cross-attention, and diffusion model acceleration through U-shape architectures. Scientific Contributions: Publications include breakthroughs in controllable face synthesis, mask-based generative modeling, and video anomaly detection. His work bridges theoretical advancements in neural architectures with practical applications in remote sensing and educational technology. 2025: FLAV (audio-video generation), Swin2-MoSE (remote sensing) 2024: MARS (text-based person search), MCGM (mask conditioning) 2023: FrankenMask (face part editing), Student attendance systems

Weina Li Chenمشاهده پروفایل

استادیار بالینی

• Educational Technologies
• Learning Design
• Online and Hybrid Learning
• +۵ مورد دیگر

Weina Li Chen serves as a Clinical Assistant Professor within the Education Division of Pepperdine University's Graduate School of Education and Psychology, teaching courses in the Master of Arts in Teaching English to Speakers of Other Languages (MA TESOL) and Master of Science in Leadership programs. With approximately ten years of teaching experience across diverse educational settings, she brings practitioner expertise to her academic role while maintaining active engagement in professional development and program design. Her academic credentials include: Ph.D. from Pepperdine University M.A. from Pepperdine University M.A. from University of York, England B.A. from Heilongjiang University, China Dr. Chen's research focuses on educational technologies and innovative learning design , with specialized expertise in online/hybrid learning environments, world language acquisition (particularly English as a Second Language), and teacher leadership development. She investigates how digital tools can enhance student engagement, social presence, and language proficiency through practical applications. Her work bridges academic research with classroom implementation, frequently resulting in practitioner workshops and conference presentations that translate theoretical concepts into actionable teaching strategies for language educators. Analysis of her 14 publications (2019-2023) reveals consistent emphasis on technology-mediated language learning. She explores platforms like Flip, Canva, and WeChat to create interactive communities and support speaking practice, with recurring themes including social-emotional learning integration and digital storytelling. Her research demonstrates a practitioner-scholar approach, targeting both pre-service and in-service teachers through workshops that address real-world classroom challenges in language education. As an educational leader, Dr. Chen founded and served as president of CABE Mandarin, an organization promoting Mandarin language education. She has designed multiple language programs for schools and universities, demonstrating commitment to expanding language learning opportunities. While specific grant funding details and student advisee names are not documented in available materials, her conference presentations and program development initiatives indicate active community engagement and professional contribution to the fields of TESOL and educational technology.

Patrik Kovačovskýمشاهده پروفایل

استاد

• Sculpture in 3D virtual space and architecture
• Multimedia Art
• Digital Installations
• +۲ مورد دیگر

Patrik Kovačovský is a Professor and Studio Manager at the Department of Sculpture, Object, Installation at the Academy of Fine Arts in Bratislava. He works at the intersection of sculpture, architecture, and digital space, focusing on innovative artistic research and practice. Academy of Fine Arts in Bratislava (Department of Sculpture, 1990–1996) Art.D. studies, Academy of Fine Arts, 2001–2003 His research integrates traditional sculpture with virtual reality and architectural contexts, producing installations that explore memory, cosmic themes, and cultural identity. Recent works include Fluid Pictures (2011) and Kosmos (2006). 1996 Young Artist of the Year, Slovak National Gallery 2000 Annual Award, Galéria Klatovy/Klenová 2008 Visegrad Artist Residency 2010 Prohelvetia Residency in Zurich