جست‌وجوی استاد و پژوهشگر

Ying Liuمشاهده پروفایل

دانشیار

• Computer Vision
• Deep Learning
• Image and Video Coding
• +۴ مورد دیگر

Dr. Ying Liu is an Associate Professor in the Department of Computer Science and Engineering at Santa Clara University's School of Engineering. She serves as the Secretary/Treasurer of the APSIPA US Chapter and holds multiple leadership roles including APSIPA Distinguished Lecturer (2025-26) and Vice Chair of the APSIPA US Local Chapter. Her research focuses on deep learning applications for visual data processing and compression. Education: Ph.D., Electrical Engineering, SUNY at Buffalo, 2012 M.S., Electrical Engineering, SUNY at Buffalo, 2008 B.S., Telecommunications Engineering, Beijing University of Posts and Telecommunications, 2006 Dr. Liu's research spans deep learning-based image/video processing , coding for machines , and generative AI . Her work integrates convolutional neural networks, transformers, and generative models to advance video compression and machine vision systems. Current projects include vision-language models and point cloud coding, with emphasis on computational efficiency for real-world deployment. Analysis of her 15 most recent publications reveals a strong focus on neural video compression (40%), image coding for machines (30%), and generative AI applications (20%), with increasing emphasis on transformer architectures and multi-task frameworks since 2022. Her research bridges theoretical innovation with practical industrial applications in manufacturing and autonomous systems. Scientific Awards: Researcher of the Year Award, School of Engineering, Santa Clara University (2024) APSIPA Distinguished Lecturer Appointment (2025-26) Dr. Liu actively mentors PhD students in the Video and Image Processing (VIP) Laboratory, with four current advisees including Pengli Du (first PhD graduate in 2024). Her research is supported by significant grants including an NSF ERI award ($500K, 2022-2025), NVIDIA Academic Hardware Grant, and multiple industry-funded projects with Kwai Inc. totaling over $300K. She also secures internal university funding through Kuehler Undergraduate Research Grants and School of Engineering Research Grants. The VIP Laboratory develops deep learning solutions for the projected 13 billion global cameras by 2030, focusing on applications for mobile video sharing, surveillance, and autonomous vehicles. Current projects utilize CNNs, GANs, RNNs, and transformers for visual coding efficiency.

Kok Lim Lowمشاهده پروفایل

مدرس ارشد

• Computer Graphics
• Computational Art
• Real-Time Rendering
• +۲ مورد دیگر

Dr. Kok Lim Low serves as a Senior Lecturer in the Department of Computer Science at the School of Computing, National University of Singapore (NUS), where he has established himself as a leading researcher in computer graphics and computational art. With over two decades of academic service, he bridges technical innovation with creative applications while maintaining exceptional teaching standards. His educational foundation includes: Ph.D. in Computer Science from the University of North Carolina at Chapel Hill (2006) M.Sc. in Computer Science from the National University of Singapore (1997) B.Sc. (Honours) in Computer Science from the National University of Singapore (1996) Dr. Low's research centers on computational approaches to visual media, with three interconnected pillars: Computational Art explores algorithmic generation of artistic papercraft and pop-up books; Real-Time Rendering develops GPU-accelerated global illumination techniques; and Computational Photography enhances image aesthetics through depth adaptation and recomposition. His work consistently merges mathematical rigor with artistic sensibility, producing methods that automate creative processes while preserving aesthetic integrity. Analysis of his recent publications reveals an evolving trajectory from core graphics research toward computer science education innovation. While maintaining strong output in computational art (evident in his 2014-2015 pop-up design papers), his 2021-2023 work demonstrates significant contributions to CS1 pedagogy through educational tool development and curriculum design, reflecting his dual commitment to research and teaching excellence. His scientific recognition includes: Three Faculty Teaching Excellence Awards from NUS School of Computing (2014, 2016, 2017) Best Paper Award at Computer Graphics International Conference (2015) Honorable Mention at ACM CHI Conference (2011) As an educator, Dr. Low has advised Ph.D. and Master's students while serving on numerous thesis committees. He teaches foundational courses like Programming Methodology to freshmen alongside advanced topics including Graphics Rendering Techniques, demonstrating equal commitment to novice and advanced learners. His student mentorship extends to undergraduate research projects across the computing curriculum. Dr. Low operates within NUS Computing's collaborative research ecosystem, where his interdisciplinary work connects computer science with art and design disciplines. His laboratory contributions focus on developing practical computational tools that transform creative workflows while advancing theoretical understanding of visual media processing.

Charith Abhayaratneمشاهده پروفایل

مدرس ارشد

• Signal Processing
• Machine Learning
• Multimedia Security
• +۷ مورد دیگر

Dr. Charith Abhayaratne is a Senior Lecturer and EEE Foundation Year Tutor at the School of Electrical and Electronic Engineering, University of Sheffield. He leads the Communications Research Group and serves as the accreditation team lead for the school. With qualifications including a PhD from the University of Bath and a B.E. from the University of Adelaide, his research focuses on signal processing, machine learning, multimedia security, and video coding. His work explores blockchain for content protection, visual salience in robotics, human activity recognition, and advanced video coding techniques (HDR, UHD, 360° video). His research has been funded by Innovate UK, EPSRC, and industry partners. Education: B.E. (Electrical and Electronic Engineering), The University of Adelaide, Australia (1998) PhD (Electronic and Electrical Engineering), University of Bath, UK (2002) PGCertHE (Higher Education), University of Sheffield (2008) Fellow of the Higher Education Academy (FHEA), Member of the Institution of Engineering and Technology (MIET), Member of IEEE (MIEEE) Research Interests: His work spans multimedia security (data hiding, blockchain), computer vision (visual salience, object recognition), and video coding (HDR/UHD). Current projects include robotic vision applications, assisted living through activity recognition, and international standards development (JPEG/MPEG). He has contributed to scalable video standards and serves on technical committees for IEEE, EURASIP, and APSIPA. Awards & Service: Recipient of the Alain Bensoussan Fellowship (ERCIM, 2002) Associate Editor for IEEE Transactions on Image Processing, IEEE Access, and Elsevier JISA Member of EPSRC Peer Review College and British Standards Institution (BSI) Grants & Labs: Active grants from Innovate UK and EPSRC support projects in multimedia security and video coding. His lab leads interdisciplinary work in AI-driven visual analytics and secure media distribution frameworks.

• Image Compression
• Cryptography
• Privacy-Preserving Systems
• +۵ مورد دیگر

Ja-Ling Wu is a distinguished Professor in the Department of Electrical Engineering at National Taiwan University's College of Electrical Engineering and Computer Science. With an extensive publication record spanning over four decades (1984-2025), Professor Wu has established himself as a leading researcher in multimedia systems, image processing, and security technologies. His academic career demonstrates consistent productivity with 255 indexed publications showing no signs of slowing down, with numerous papers published in 2024 and 2025. Professor Wu's research interests center on image compression, cryptography, privacy-preserving systems, and machine learning applications. His work bridges theoretical foundations with practical implementations, particularly in multimedia security and efficient data representation. Over his career, he has developed innovative approaches to image and video coding, data hiding techniques, and secure computation methods that have influenced both academic research and industry applications. Analysis of his recent publications (2023-2025) reveals a strategic evolution of his research toward contemporary challenges in AI security, with increasing focus on learned image compression, privacy-preserving machine learning, and the integration of cryptographic techniques with deep learning systems. His work demonstrates a consistent ability to adapt to emerging technological landscapes while maintaining core expertise in multimedia processing. Professor Wu has mentored numerous students who have become active researchers in their own right, with many continuing to collaborate with him on cutting-edge projects. His leadership in the field is evident through his sustained publication output across top venues including IEEE Transactions, ACM Multimedia, and specialized cryptography conferences.

• Media Theory
• Cultural Studies
• Sound Studies
• +۵ مورد دیگر

Anna Nacher is a Professor at Jagiellonian University’s Institute of Audiovisual Arts, Department of Audiovisual Media, and serves as the Head of her department. Her research spans media theory through cultural studies, sound studies, e-literature, and video games as artistic strategies, with a focus on post-digital imaging, platformed internet dynamics, and non-representational media frameworks. Education : Not explicitly detailed in the text. Research Interests : She investigates the intersections of transmedia storytelling, data visualization, and socio-political narratives, particularly in migration studies and climate crisis contexts. Her work bridges physical and digital spaces, emphasizing "code/space" relationships and the aesthetics of networked media. Article Trends : Recent publications explore pandemic-era digital literature, hashtag movements, and eco-critical practices. Themes include digital humanities, interactive media, and the use of computational tools to analyze migration, environmental change, and social activism. Scientific Awards : Fulbright Scholar (2019/2020) Laureate of Granty na Granty II competition (2021) Advising & Grants : She supervises PhD students (e.g., Marta Snoch on scent in audiovisual media) and collaborates internationally, including with UCLA Art|Sci Center on the Breath Library project. Her grants include participation in the "elit and COVID-19" project and leadership in "Post-Digital Imaging" (2017-2019). Labs & Teams : She works with Victoria Vesna’s UCLA Art|Sci Center, contributes to the Electronic Literature Organization, and engages in interdisciplinary teams for projects like Breath Library and Electronic Literature Organization conferences.

• Artificial Intelligence
• Educational Technology
• Game-Based Learning
• +۳ مورد دیگر

Carlos José Villagrá Arnedo is a full-time Professor in the Department of Computer Science and Artificial Intelligence at the University of Alicante, where he has been employed since 1999. He holds a PhD in Computer Engineering (2016) and a Bachelor's in Computer Science from the Polytechnic University of Valencia (1994). He coordinates the Digital Creation and Entertainment program and previously served as Head of Studies for Multimedia Engineering. His research integrates Artificial Intelligence , Educational Technology , and Game-Based Learning , with specific focus areas including learning analytics, adaptive educational systems, programming pedagogy, and accessibility in gaming. Recent work explores mental model analysis using AI and low-level programming approaches to enhance learning outcomes. His publications demonstrate a consistent emphasis on predictive learning models, educational gamification, and inclusive technology design. Key trends include AI-driven analytics (2020-2024), programming error analysis (2018-2023), and accessible game development (2017-2019). Research Projects: Integrating Adaptive Flipped Learning in Physical Education Students (2024-2025) Smart Learning Research Group (2024) Semantic Web for Cultural Heritage (2019-2021) European Collaborative Learning for Robot Skill Acquisition (2016-2018) He has directed or co-directed 75+ undergraduate/master's theses in the last five years and leads the Smart Learning Research Group focused on intelligent educational technologies.

Jörn Ostermannمشاهده پروفایل

استاد

• Video Coding
• Computer Vision
• Machine Learning
• +۹ مورد دیگر

Prof. Jörn Ostermann is a Full Professor and Head of the Institut für Informationsverarbeitung at Leibniz Universität Hannover since 2003, with prior roles at AT&T Bell Labs and AT&T Labs-Research. He served as Dean of the Faculty of Electrical Engineering and Computer Science (2011–2013) and member of the Senat (since 2020). His research spans video coding, computer vision, machine learning, 3D modeling, and computer-human interfaces , with applications in SAR imaging, predictive maintenance, children's speech analysis, and cochlear implants. Key projects include Next Generation Video Coding , Conditional Coding for Learned Compression , and GreenAutoML4FAS . Notable trends in his recent publications (2025–2023) include Neural network-based video compression Uncertainty estimation in speech recognition Zero-delay coding for cochlear implants Domain adaptation for aerial image segmentation 3D mesh compression standards Error concealment in VVC coding Scientific recognitions: AT&T Standards Recognition Award (1998) ISO Award (1998) IEEE Fellow (2005) Distinguished Lecturer, IEEE CAS Society (2002/2003) MPEG Convenor (2020–2023) He co-authored a graduate textbook on Video Communications , holds >30 patents, and has led >20 research projects. His work bridges academic research and industrial standardization, particularly in MPEG and IEEE committees.

Ketan Mayer-Patelمشاهده پروفایل

دانشیار

• Multimedia Systems
• Networking
• Multicast Applications
• +۳ مورد دیگر

Ketan Mayer-Patel serves as Associate Professor and Director of Undergraduate Studies within the Department of Computer Science at the University of North Carolina at Chapel Hill. His academic credentials include: Ph.D. in Computer Science, University of California, Berkeley (1999) Research spans multimedia systems, networking, and multicast applications with current emphasis on model-based video coding, dynamic media coding models, and networking solutions for semantically related media streams. His work bridges theoretical frameworks with practical implementations in distributed multimedia environments. Scientific Awards: No awards documented in source material Advising and grant activities are not detailed in available information, though his role as Director of Undergraduate Studies indicates significant academic leadership responsibilities.

Tianxing Heمشاهده پروفایل

استادیار

• AI Safety
• AI-driven Simulation
• Large Language Models
• +۵ مورد دیگر

Tianxing He is an Assistant Professor at Tsinghua University's Institute for Interdisciplinary Information Sciences (IIIS), also known as the Yao Class, which he joined in September 2024. He also works part-time at Shanghai Qi Zhi Institute where he recruits for research-oriented positions and video game development roles. His academic journey includes a postdoc at the University of Washington under Yulia Tsvetkov, a PhD at MIT supervised by James Glass, and bachelor's and master's degrees at Shanghai Jiao Tong University in the ACM honored class under Prof. Kai Yu. Dr. He's research spans AI safety and AI-driven simulation with particular focus on large language models. His work examines LLM capabilities in cryptography (AICrypto benchmark), security vulnerabilities (jailbreaking techniques), multi-agent system integrity, and socially impactful applications like vaccine hesitancy simulation (VACSIM framework). He has developed visualization tools like MiniAgents-Pro using Unity for generative agent simulation and created watermarking techniques such as SemStamp and k-SemStamp for detecting machine-generated text. His publication record shows consistent contributions to top-tier conferences including ACL, EMNLP, NeurIPS, and ICLR, with recent work focusing on evaluating LLM capabilities across diverse domains. The research demonstrates sophisticated understanding of both the technical aspects of language models and their broader societal implications, particularly in security and ethical considerations. Scientific Awards: The Best Paper Award at the Efficient Natural Language and Speech Processing Workshop (NeurIPS ENLSP 2022) for "PCFG-based Natural Language Interface Improves Generalization for Controlled Text Generation" Dr. He actively mentors students and recruits research interns, PhD candidates, and post-bachelor researchers. He plans to teach an undergraduate NLP course in Fall 2025 and organizes the IIIS AI Safety Lunch, a monthly gathering in Beijing for those working on AI safety. His recruitment efforts target students interested in LLM social simulation, AI+game development, and AI safety research, emphasizing the need for strong self-motivation and research passion. He leads research initiatives including the IIIS AI Safety Lunch series and has developed multiple visualization and simulation frameworks. His work sits at the intersection of AI safety, language modeling, and practical applications, with team collaborations spanning multiple institutions including MIT, University of Washington, and Shanghai Jiao Tong University.

Jacques Caretteمشاهده پروفایل

دانشیار

• Mechanized Mathematics
• Correct-by-Construction Software
• Metaprogramming
• +۷ مورد دیگر

Jacques Carette is an Associate Professor at McMaster University , affiliated with the Department of Computing and Software . His research bridges formal and applied domains, including Mechanized Mathematics , Correct-by-Construction Software , and Game Design , with a focus on User Experience and Visual Scaling in games. He actively explores Reversible Computing , Quantum Programming , and DSLs for software generation. Research Interests: Mechanized Mathematics : Formalizing mathematical theories for software correctness. Game Design : Visual scale impact on user experience and cognitive components in gaming. Reversible & Quantum Computing : Reversible program transformations and quantum algorithm design. Software Engineering : Metaprogramming, code generation, and productivity analysis. Trends in Articles : His work spans Quantum Computing , Game Design , Formal Methods , and Software Sustainability . Recent publications emphasize DSLs , reversible models , and emotional computational models in games. Contact Information: Email: c@rtte@mcmaster.ca

Jason Clarkeمشاهده پروفایل

مدرس

• Visual Perception
• Time Perception
• Attention
• +۴ مورد دیگر

Jason Clarke is a Lecturer in Psychology at the University of West London, affiliated with the School of Human and Social Sciences. He holds a B.A. (Hons) in Classical Studies from University College London, an M.A. and Ph.D. in Psychology from The New School for Social Research. His career includes roles as a Postdoctoral Teaching and Research Fellow in the Sensation and Perception Laboratory at The New School (2014–2017), Visiting Assistant Professor at SUNY Farmingdale (2018–2020), and part-time lecturing at institutions like the City University of New York and Princeton University. Clarke’s research focuses on cognitive processes underlying visual perception, time perception, and consciousness. He integrates predictive processing frameworks (e.g., Free Energy Principle) to explore how expectation and attention shape conscious experience. His book, *Constructing Experience: Expectation and Attention in Perception* (2024), synthesizes empirical findings on inattentional blindness and change blindness. Key research directions include the role of generative models in perception and the quantum/classical probability debate in cognition. Education : B.A. Classical Studies, University College London M.A. Psychology, The New School for Social Research Ph.D. Cognitive Psychology, The New School for Social Research Teaching : Cognitive Psychology Cognitive Neuroscience Sensation and Perception His PhD students Becky Tyler (attention-expectation interactions) and Gergely Gerstmayer (gravity’s impact on time perception) extend his work into applied domains like spaceflight adaptation and virtual reality. Clarke’s research aligns with UN SDGs 3 (Health), 4 (Education), and 9 (Innovation). Clarke has contributed to courses across undergraduate and postgraduate programs at UWL, including BSc Psychology, MSc Psychology of Mental Health, and PhD Psychology.

Mariya Tonevaمشاهده پروفایل

استاد

• Computational Neuroscience
• Natural Language Processing
• Machine Learning
• +۲ مورد دیگر

Mariya Toneva is a Tenure-track Professor (W2) at the Max Planck Institute for Software Systems in Saarbrücken, Germany, where she leads the Bridging AI and Neuroscience (BrAIN) group. Her research integrates machine learning, natural language processing, and neuroscience to develop computational models of language processing in the brain and improve NLP systems through brain alignment. Her research vision focuses on bidirectional benefits: 1) Using brain data to develop better language models that align with human cognition, and 2) Using insights from language models to understand human language processing. Current projects investigate how episodic memory can enhance long-term LLM agents and how speech models can better reflect neural processing hierarchies. Toneva's recent publications demonstrate significant contributions in brain-LLM alignment, with work appearing at ICLR, CogSci, TMLR, EMNLP, and INTERSPEECH. Her research group systematically examines why language models align with brain recordings and develops methods to improve this alignment through brain-tuning techniques. She actively seeks PhD students and postdoctoral researchers for projects involving neuropixel data analysis of speech processing and multimodal transformer architectures. Toneva regularly presents keynotes at major conferences (e.g., ELLISxUniReps Speaker Series) and participates in workshops on NeuroAI and cognitive modeling. Her interdisciplinary approach combines techniques from machine learning, natural language processing, and cognitive neuroscience to address fundamental questions about language representation in both artificial and biological neural systems.

Janina Wildfeuerمشاهده پروفایل

دانشیار

• Multimodality
• Semiotics
• Text and Discourse Analysis
• +۶ مورد دیگر

Janina Wildfeuer is an Associate Professor in Communication and Information Studies at the University of Groningen, affiliated with the Jantina Tammes School of Digital Society, Technology, and AI. She holds editorial roles as Chief Editor of Visual Communication , Associate Editor at Frontiers in Communication, and Book Series Editor for Pathways to Multimodality (de Gruyter). Her research focuses on multimodal communication, including audiovisual media, social media, games, and AI-generated content, with an emphasis on societal impact like addressing hate speech and misinformation. She leads the Multimodality and AI research group and teaches courses on digital communication and multimodal analysis. Education: PhD in Multimodal Linguistics (University of Bremen, 2012), MA in Linguistics (University of Münster, 2008). Research Interests: Multimodal argumentation, TikTok analysis, AI-generated media, and first-aid communication via VR. Editorial Roles: Chief Editor of Visual Communication , Associate Editor at Frontiers, and Book Series Editor at de Gruyter. Teaching: Courses on multimodality, digital communication, and media analysis at both BA and MA levels. Labs/Groups: Leads the Multimodality and AI group and collaborates with the RESPONSUS team on communication ethics. Her work bridges theoretical frameworks with empirical studies, emphasizing interdisciplinary approaches to visual and digital media. Recent projects include analyzing short video content, TikTok’s corpus-based analysis, and the ethical implications of AI in media production.

• Natural Language Processing
• Computer Vision
• Artificial Intelligence
• +۳ مورد دیگر

Aditya Sharma is a researcher at the University of California Santa Barbara , focusing on Natural Language Processing , Computer Vision , and Artificial Intelligence . His work bridges vision-language models, medical AI evaluation, and knowledge graph reasoning. PhD : Advancing AI Understanding in Language & Vision (UCSB, 2024) Research Interests: • Vision-Language Models for geometric reasoning and mixed reality • Medical LLM evaluation and hallucination reduction • Temporal knowledge graph reasoning and multimodal systems Article Trends: Recent publications emphasize vision-language integration (e.g., GeoCoder, OCTO+), LLM reliability in medical contexts (MedHELM), and temporal reasoning (TwiRGCN). He explores applications in dark web security , healthcare diagnostics , and energy-efficient computing .

Lei Jiaoمشاهده پروفایل

استاد

• Artificial Intelligence
• Machine Learning
• Tsetlin Machines
• +۷ مورد دیگر

Lei Jiao is a Professor in the Department of Information and Communication Technology at the University of Agder's Faculty of Engineering and Science. Previously serving as an Associate Professor from May 2014 to October 2022, Dr. Jiao has established himself as a leading researcher in artificial intelligence, with particular expertise in Tsetlin Machines and their applications across diverse domains. PhD in Information and Communication Technology, University of Agder (2008-2012) Master of Engineering in Communication and Information System, Shandong University (2005-2008) Bachelor of Engineering in Telecommunication Engineering, Hunan University (2001-2005) Dr. Jiao's research spans multiple cutting-edge areas including interpretable artificial intelligence, wireless communication protocols, network resource allocation, and signal processing. His work on Tsetlin Machines has pioneered new approaches to machine learning that emphasize interpretability while maintaining high performance. The research group he contributes to at the University of Agder focuses on Autonomous and Cyber-Physical Systems (ACPS), Battery recycling, and the Centre for Artificial Intelligence Research (CAIR). Analysis of Dr. Jiao's recent publications reveals a strong emphasis on interpretable AI systems, particularly through Tsetlin Machines. His work spans applications in GNSS jammer detection, crowd anomaly detection, DNA sequence classification, and hardware acceleration of machine learning models. The research consistently demonstrates how logical, rule-based approaches can provide transparent alternatives to traditional neural networks while maintaining competitive performance. Supervised numerous PhD students including Vojtech Halenka, Ahmed K. Kadhim, and Sindhusha Jeeru Mentored over 30 Master's thesis projects covering topics from Tsetlin Machines to signal processing and computer vision Collaborates extensively with Ole-Christoffer Granmo and other leading researchers in the AI field Dr. Jiao actively contributes to advancing the field through supervision of doctoral candidates, collaboration on major research projects, and development of novel machine learning approaches that balance performance with interpretability. His work bridges theoretical foundations with practical applications across telecommunications, computer vision, and natural language processing domains.