جست‌وجوی استاد و پژوهشگر

Touradj Ebrahimiمشاهده پروفایل

استاد

• Image and Video Compression
• Media Security
• Multimedia Signal Processing
• +۵ مورد دیگر

Touradj Ebrahimi is a Full Professor at École Polytechnique Fédérale de Lausanne (EPFL), where he heads the Multimedia Signal Processing Group (MMSPG) within the School of Engineering's Institute of Electrical Engineering. He holds a Ph.D. in Electrical Engineering from EPFL and serves as the Convenor of the JPEG standardization committee. His research spans AI-powered imaging, multimedia signal processing, and media security. Research Interests: Professor Ebrahimi's work focuses on next-generation image/video compression (including JPEG AI and DNA-based storage), quality of experience in immersive media, trustworthy media authentication (JPEG Trust), and explainable AI for biometric systems. His group pioneers methods for point cloud compression, deepfake detection, and privacy-preserving multimedia. Publication Trends: Recent articles emphasize AI-driven compression standards, quality assessment for emerging media (point clouds, HDR), and explainability in computer vision. Key themes include JPEG AI standardization, DNA storage for visual data, and robustness evaluation of deepfake detectors. Awards & Honors: IEEE Star Innovator Award in Multimedia IEEE and Swiss National ASE Awards ISO Certificates for MPEG-4/JPEG 2000 contributions Best Paper Award (IEEE Trans. Consumer Electronics) Fellow of IEEE and SPIE Leadership: He founded RayShaper SA, Genista SA, and Emitall SA. Represents Switzerland in ISO/IEC JTC1/SC29 and ITU, advising European Commission initiatives and venture capital firms on multimedia technologies. Facilities: Leads the MMSPG lab at EPFL, focusing on intelligent multimedia systems. The group collaborates globally on standardization (JPEG, MPEG) and EU projects.

Shiqi Wangمشاهده پروفایل

دانشیار

• Semantic and Visual Communication
• AI Generated Content Management
• Information Forensics and Security
• +۳ مورد دیگر

Shiqi Wang is an Associate Professor in the Department of Computer Science at City University of Hong Kong. He holds a Ph.D. from Peking University (2014) and a B.Sc. from Harbin Institute of Technology (2008). His career includes postdoctoral and research roles at the University of Waterloo, Nanyang Technological University, and Microsoft Research Asia. He specializes in semantic/visual communication, AI content management, and image/video quality assessment. Education: Ph.D. in Computer Application Technology (2014), Peking University B.Sc. in Computer Science and Technology (2008), Harbin Institute of Technology Research focuses on Large Visual-Language Models (LVLMs) , Generative Face Video Coding , and Information Forensics . Recent work includes video coding innovations, AI-driven quality assessment, and bias mitigation in facial analysis. Awards include the IEEE Multimedia Rising Star Award (2021) , NSFC Excellent Young Scientist Fund (2020) , and multiple best paper awards at IEEE conferences. He serves as Associate Editor for IEEE Transactions on Image Processing and leads MPEG standardization efforts for generative video coding. Professional activities include TPC roles at ICML, CVPR, and ACM Multimedia. His lab actively collaborates on standards for generative AI and multimedia systems, with a focus on ethical AI and cross-domain applications.

• Image and Video Quality Estimation
• Video Transport over Networks
• Video Analytics
• +۳ مورد دیگر

Amy R. Reibman is the Elmore Family School of Electrical and Computer Engineering's Elmore Professor of Electrical and Computer Engineering at Purdue University. She holds a PhD (1987), MSEE (1984), and BSEE (1983) from Duke University. Her research focuses on image/video quality assessment, video transport over networks, and video analytics with applications in agriculture, healthcare, and surveillance. She is an IEEE Fellow and recipient of the 1998 Leonard G. Abraham Prize Paper Award. Reibman teaches ECE 302: Probabilistic Methods in ECE (undergraduate) and ECE 634: Digital Video Systems (graduate). Her work integrates quality estimation into real systems and explores video analytics for activities like animal behavior analysis, hand hygiene monitoring, and farming automation. She collaborates with industry (e.g., AT&T Labs) and publishes widely in IEEE journals and conferences. Research Highlights: Video quality for IoT, first-person video stability, and agricultural video analytics. Grants/Projects: Supported by NSF and industry partnerships (e.g., video transport optimization). Her lab develops tools for stress-testing quality estimators and has contributed foundational work on packet loss resilience in video coding. Current projects include cattle intake monitoring and honeybee hive detection.

Jorma Laaksonenمشاهده پروفایل

مدرس ارشد

• Artificial Intelligence
• Machine Learning
• Computer Vision
• +۴ مورد دیگر

Jorma Laaksonen is a Senior Lecturer at the Department of Computer Science, Aalto University (School of Science). His research focuses on artificial intelligence, machine learning, computer vision, and multimedia systems, with notable contributions to cross-lingual evaluation, hyperspectral imaging, and audio-visual attention mechanisms. He holds a Doctoral degree in Engineering and Technology from Helsinki University of Technology (1997). Education: Doctoral degree, Engineering and Technology, Helsinki University of Technology (1997) Licentiate degree, Engineering and Technology, Helsinki University of Technology (1991) Master's degree, Engineering and Technology, Helsinki University of Technology (1990) His research interests span AI-driven visual computing, human-computer interaction, and multimedia systems. Key projects include USSEE (audio-visual scene understanding) and ARTISDIG (AI for forest spectral analysis). He has published over 280 papers and supervised multiple theses. Awards include the IEEE Best Paper Award (2017) and Microsoft's Best Practice Award (2016). Recent work includes cross-cultural language modeling, efficient text-to-video retrieval, and open-world video instance segmentation. He leads the Lecturer Laaksonen Jorma group and actively participates in editorial roles and doctoral thesis evaluations.

Kazimierz Chorośمشاهده پروفایل

استاد

• digital image and video processing
• content-based video indexing and retrieval
• computer animations
• +۴ مورد دیگر

Kazimierz Choroś is a Professor at the Department of Applied Informatics , Faculty of Information and Communication Technology , Wrocław University of Science and Technology. He held leadership roles as Deputy Director of the Institute of Informatics (2008-2014) and Deputy Dean of the Faculty of Computer Science and Management (2016-2020). Research interests: digital image/video processing, content-based video indexing, computer animations, multimedia systems, web systems analysis, and information systems design. Organizer and Chair of the International Conference on Multimedia & Network Information Systems (MISSI 2022) Chair of Special Session WebSys 2020 at ICCCI 2020 Other activities: Since 1993, member and former President (1993-2002) of the SAGE Association (Polish Graduates of French Grandes Ecoles). Since 1982, member of the Polish Numismatic Society, author of dozens of numismatic publications, and Editor-in-Chief of Wrocławskie Zapiski Numizmatyczne (2003-present). Contact: Email: kazimierz.choros@pwr.edu.pl Phone: +48-71.320.3799 Office: Building D2, Room 201/1 Address: Wrocław University of Science and Technology, Wyb. Wyspiańskiego 27, 50-370 Wrocław, Poland

Sandra Haleمشاهده پروفایل

استاد

• Legal interpreting
• Forensic linguistics
• Court interpreting
• +۷ مورد دیگر

Professor Sandra Hale is a distinguished academic at the University of New South Wales (UNSW), serving in the School of Humanities & Languages within the Faculty of Arts, Design & Architecture. As a pioneer in legal interpreting research, she has established herself as a world leader in forensic linguistics and court interpreting studies. Her educational background is impressive, including a Bachelor of Arts (Interpreting & Translation), NAATI Spanish interpreter/translator & Conference interpreter certification, Diploma of Education (Italian & Spanish), Master of Applied Linguistics, PhD in Court interpreting/forensic linguistics (the first of its kind in Australia, awarded in 2001), and a Doctorate Honoris Causa in Interpreting and Translation Studies from the University of Antwerp. Hale's research has fundamentally shaped our understanding of legal interpreting, with particular focus on quality, accuracy, codes of ethics, role expectations, and the impact of interpreters on legal proceedings. She was among the first researchers globally to conduct large data-based studies of court interpreted proceedings, developing innovative research methods that have been widely adopted. Her work bridges interpreting studies, forensic linguistics, cognitive psychology, and legal studies, examining how interpreters affect judicial outcomes through micro-analysis of courtroom discourse and experimental studies. Recent publications demonstrate continued innovation in studying interpreter performance across various settings including police interviews, courtrooms, and legal consultations, with particular attention to interpreter mode, location, and working conditions. Her scholarly contributions have been recognized through numerous prestigious awards including the Andrea Durbach Award for Human Rights Scholarship, election as Fellow of the Australian Academy of the Humanities, multiple Dean's Awards for teaching and research impact, and a Doctor Honoris Causa from the University of Antwerp. Professor Hale actively supervises PhD candidates and has secured substantial research funding through ARC Linkage grants, ARC Discovery grants, FBI grants, and NHMRC grants. Her projects address critical issues in interpreted proceedings, interpreter training methodologies, and communication with culturally and linguistically diverse populations in legal and healthcare settings. She has been instrumental in developing national standards for working with interpreters in courts and tribunals. Her leadership extends to professional organizations where she serves as Immediate Past President of AUSIT (The Australian Institute of Interpreters and Translators), Fellow of the Australian Academy of the Humanities, Advisory Board Member of Multicultural NSW, and member of the Judicial Council on Cultural Diversity subcommittee on the Recommended National Standards for Working with Interpreters in Courts and Tribunals.

• Signal Processing
• Biomedical Signal Processing
• Image Reconstruction
• +۱۲ مورد دیگر

Rabab K. Ward is a Professor in the Department of Electrical and Computer Engineering at the University of British Columbia, Faculty of Applied Science, Vancouver, Canada. She is a leading figure in signal processing with extensive contributions to biomedical engineering, image reconstruction, and machine learning. She served as President of the IEEE Signal Processing Society (2016–2017) and continues to be actively involved in research and leadership. Her research focuses on signal processing , biomedical signal analysis , compressed sensing , medical image fusion and reconstruction , and deep learning for healthcare applications . She has pioneered methods in EEG and CT image processing, epileptic seizure detection, and 3D human pose estimation. The recent publications highlight her work in 3D face and human modeling , GAN-based forensics , brain-computer interfaces , and medical video analysis . Her research integrates advanced machine learning with practical engineering solutions for clinical and robotic systems. Her scientific awards include being an IEEE Fellow , Distinguished Lecturer of the IEEE Signal Processing Society , and serving as President of the IEEE Signal Processing Society . She has advised numerous students and researchers in areas such as compressed sensing , EEG signal processing , image reconstruction , and deep learning . Her collaborative work includes significant grants and projects in biomedical engineering , neurotechnology , and autonomous systems . Dr. Ward is associated with research labs and teams focused on signal processing for healthcare , medical imaging , and intelligent systems at UBC, fostering interdisciplinary collaboration in engineering and medicine.

• Computer Vision
• Machine Learning
• Data Mining
• +۵ مورد دیگر

Vassilis Athitsos is a Professor in the Computer Science and Engineering department at the University of Texas at Arlington . He holds a PhD in Computer Science from Boston University (2006), an MS in Computer Science (1997), and a BS in Mathematics (1995) from the University of Chicago. Education: PhD, Computer Science (2006), Boston University MS, Computer Science (1997), University of Chicago BS, Mathematics (1995), University of Chicago His research focuses on Computer Vision , Machine Learning , Data Mining , and applications in Gesture & Sign Language Recognition , Face Recognition , and Human Activity Analysis . Recent work includes depth-based 3D hand pose estimation, GAN applications for image restoration, and multimodal systems for cognitive assessment in children. Key research trends include depth video analysis , GAN-based translation , action segmentation , and medical imaging applications . He has received multiple scientific awards including the NSF CAREER Award (2011) and ACM Ten-Year Technical Impact Award (2023). Grants: NSF CAREER: $651,563 (2011-2017) NSF Collaborative Research: $1.37M (2016-2023) NSF PFI: $1.03M (2017-2023) NSF MRI: $879,890 (2013-2018) NSF CI-P: $116,000 (2014-2017) Grants from Private/State Sectors: Macnica Americas: $42,813 (2022-2023) Macnica Americas: $88,320 (2017-2018) Gordian Health: $9,001 (2013) Texas State Grant: $50,000 (2010) He has advised over 40 graduate students and served on numerous dissertation, thesis, and doctoral committee roles . His teaching includes Machine Learning , Computer Vision , and Research in Computer Science courses at the graduate level, along with undergraduate programming and algorithms classes.

Weija Shangمشاهده پروفایل

استاد

• Parallel Processing
• Computer Architecture
• Parallelizing Compiler
• +۷ مورد دیگر

Weija Shang is a Professor at the School of Engineering, Santa Clara University, where she has been since 1994. She previously served at the Center for Advanced Computer Studies, University of SW Louisiana (1990–1993). Her research spans parallel processing, computer architecture, parallelizing compilers, algorithm theory, and non-linear optimization. PhD in Computer Engineering, Purdue University (1990) MS in Computer Engineering, Purdue University (1984) BS in Computer Engineering, Changsha Institute of Technology (1982) Her publications focus on parallel computing , GPGPU optimization , FPGA design , and video coding techniques. Key themes include supernode transformations , media distribution algorithms , and stack optimization in recursive programs. Scientific awards include: Clare Boothe Luce Professor (1994–2000) NSF Research Initiation Award (1991) NSF Career Award (1995) She has supervised numerous research projects in parallel programming and compiler design, contributing to high-performance computing and distributed systems through collaborations with institutions like Xilinx and NASA.

Apurva Ratan Murtyمشاهده پروفایل

استادیار

• Visual Intelligence
• Neurodevelopmental Disorders
• fMRI
• +۴ مورد دیگر

Apurva Ratan Murty is an Assistant Professor at the School of Psychology, Georgia Institute of Technology. His research focuses on uncovering neural codes and algorithms underlying human vision by integrating biological studies with artificial intelligence models. The Murty Lab employs advanced neuroimaging techniques (fMRI, MEG, EEG) and computational methods (deep learning, generative AI) to explore perceptual development, neurodevelopmental disorders, and invariant object representations. He holds a PhD from the Indian Institute of Science (IISc) and completed postdoctoral research at MIT's McGovern Institute. Education: PhD in Neuroscience, Indian Institute of Science (IISc), Bangalore, India (Adviser: S.P. Arun) Postdoctoral Research: MIT's Center for Brains, Minds, and Machines (Advisers: Nancy Kanwisher, James DiCarlo) Research Interests: The lab investigates how visual information transforms into perception through neural circuits, emphasizing cross-disciplinary approaches to bridge biological and artificial vision systems. Key themes include modeling neurodevelopmental disorders, analyzing fMRI data with AI, and developing biologically constrained computational frameworks. Awards: NIH K99/R00 Pathway to Independence Award Young Systems Scientist Award, National Systems Society of India Institute Medal, Indian Institute of Science Labs & Teams: The Murty Lab actively recruits PhD students, postdocs, and undergraduates. The lab's work is showcased at murtylab.com , emphasizing translational research in vision science and neurotechnology.

Abhijit Mahalanobisمشاهده پروفایل

دانشیار

• Computational Sensing and Imaging
• Video/Image Processing
• Automatic Target Recognition (ATR)
• +۳ مورد دیگر

Dr. Abhijit Mahalanobis is an Associate Professor at the University of Central Florida (UCF), affiliated with the Center for Research in Computer Vision (CRCV). Previously, he served as a Senior Fellow at Lockheed Martin and held academic positions at the University of Arizona and the University of Maryland. He earned his B.S. from UC Santa Barbara (1984) and M.S./Ph.D. from Carnegie Mellon University (1985/1987). His research focuses on computational sensing, imaging systems, and automatic target recognition (ATR). Notable contributions include work on correlation filters, compressive sensing, and 3D imaging. He has published over 170 papers, holds four patents, and co-authored a book on pattern recognition. Dr. Mahalanobis has received prestigious awards such as the IEEE Fellow (2015), OSA Fellow (2004), and SPIE Fellow (1997). He has been honored with the Lockheed Martin NOVA Award (2005), Scientist of the Year (2006), and Innovator of the Year (1999). He has served on editorial boards for journals like Applied Optics and Pattern Recognition , and chairs for OSA and SPIE conferences. His research spans topics including infrared target detection, compressive sensing architectures, and deep learning for target recognition. The CRCV lab, under his leadership, develops advanced algorithms for defense and surveillance applications.

• Fractional-Order Systems
• Chaotic Systems
• Field-Programmable Gate Array (FPGA) Implementations
• +۵ مورد دیگر

Ahmed Gomaa Radwan is a Professor at Cairo University's Department of Engineering Mathematics and Physics, Egypt. His research spans fractional-order systems , chaotic dynamics , FPGA implementations , and bio-impedance modeling , with numerous publications in IEEE Access, Microelectronics Journal, and Circuits Systems Signal Processing. Key collaborators include Lobna A. Said , Wafaa S. Sayed , and Ahmed Soltan . His work emphasizes chaos-based encryption , fractional calculus , and hardware accelerators for real-world applications. Publications highlight trends in fractional-order chaotic systems , memristor technology , and secure image processing , often involving CNTFET designs and nonlinear resonators .

Saksham Suriمشاهده پروفایل

پژوهشگر

• Computer Vision
• Machine Learning
• Diffusion Models
• +۱۲ مورد دیگر

Saksham Suri is a Researcher at Meta Reality Labs , focusing on efficient foundation models and computer vision . He earned his PhD in Computer Science from the University of Maryland, College Park , advised by Prof. Abhinav Shrivastava . Prior to this, he completed his B.Tech in Computer Science and Engineering at IIIT Delhi , where he worked at the IAB Lab and Precog research group. His research interests center around computer vision and machine learning , particularly in reducing supervision requirements and leveraging synthetic data (e.g., from diffusion models and GANs ) for tasks like object detection , image segmentation , lip synchronization , and video instance segmentation . He has proposed novel architectures and loss functions to enhance recognition through generation, addressing challenges in sparsely annotated object detection , autoregressive generative models , and efficient feature transforms for Vision Transformers . Notable publications include LARP (ICLR 2025, under review), UVIS (CVPR Workshop 2024), Gen2Det (CVPR Workshop 2024), LiFT (ECCV 2024), GRIT (WACV 2024), and Diff2Lip (WACV 2024). These works span topics in video tokenization , synthetic data for detection , lightweight feature transforms , and audio-conditioned lip synchronization . He has collaborated with researchers such as Rama Chellappa , Mayank Vatsa , Richa Singh , C.-C. Jay Kuo , and Larry Davis . His academic contributions include open-source code repositories for projects like LARP , SparseDet , ViT Analysis , and LiFT . He has also served as an Area Chair for CVPR (2018–2021) and contributed to educational resources for courses like CS188 at UC Berkeley.

• Video coding
• Video analysis
• Video adaptation
• +۳ مورد دیگر

Fernando Manuel Bernardo Pereira is a Full Professor at the Telecommunications Institute of Instituto Superior Técnico (IST), Lisbon. His research focuses on video coding, multimedia representation standards, and advanced multimedia systems. He actively contributes to academic and industry collaborations on standards like JPEG Pleno and security frameworks for media annotation. Key Affiliations : Instituto Superior Técnico, Telecommunications Institute Roles : Full Professor, Researcher in Multimedia Communication His scientific interests span video analysis, adaptation techniques, and multimedia services. Recent work emphasizes deep learning applications in point cloud coding, quality metrics for 3D data, and explainable AI in facial recognition systems. He collaborates internationally on projects involving light field technology and trustworthy media systems. Publications reflect a focus on cutting-edge areas like neural network-based image coding, compression artifact analysis, and capsule networks for expression recognition. While no awards are explicitly listed, his prolific publication record indicates significant contributions to the field. No advising students or grant details are provided in the text. His research teams likely engage in collaborative efforts given his work on standards and multi-institutional responses to industry calls for evidence.

• Artificial Intelligence
• Machine Learning
• Neural Networks
• +۶ مورد دیگر

E. Alonso is a Professor in the Department of Computer Science at City, University of London, with extensive contributions to artificial intelligence, machine learning, and cognitive science. His work spans theoretical foundations of AI, practical applications in power systems, automotive diagnostics, and ethical considerations in generative AI. Faculty member at City, University of London since at least 2010 Active researcher with publications extending through 2025 Collaborates extensively with researchers in AI, power systems, and cognitive science Regular presenter at major AI conferences including IJCAI, AAAI, and IEEE conferences Professor Alonso's research focuses on the intersection of theoretical AI and practical applications. His work in neural networks spans reinforcement learning, time series forecasting, and multi-agent systems. He has made significant contributions to understanding the mathematical foundations of AI systems, particularly in agent representations and learning mechanisms. His recent work increasingly addresses the ethical and legal implications of AI, particularly concerning copyright issues in generative AI training and moral value alignment in democratic AI systems. Analysis of Professor Alonso's recent publications (2023-2025) reveals a strong trend toward practical AI applications with theoretical grounding. His work spans multiple domains including power systems optimization using graph neural networks, automotive diagnostics with specialized neural architectures, and creative AI approaches to generalization. A notable pattern is his ability to bridge theoretical AI concepts with real-world engineering problems, particularly in energy systems and automotive applications. His research increasingly incorporates ethical considerations, reflecting the growing importance of responsible AI development. Professor Alonso has supervised numerous students who have gone on to publish with him in top venues. His collaborative approach is evident in the diverse range of co-authors across different disciplines. While specific grant information isn't detailed in the provided materials, his sustained publication record across multiple domains suggests successful funding acquisition for his research programs. His work appears connected to the Centre for Computational and Animal Learning Research, suggesting involvement in interdisciplinary teams exploring the connections between biological learning systems and artificial intelligence. Recent collaborations with researchers in medical imaging and radiotherapy implementation further demonstrate the breadth of his research impact across different application domains.