2nd NJIT Workshop on Multimedia Intelligence (MMI 2026)
May 21–22, 2026 ·
New Jersey Institute of Techno · Newark,
**Registration Open**
About
The NJIT Workshop on Multimedia Intelligence (MMI 2026) is a community-driven research event focused on advancing multimedia AI, multimodal learning, and intelligent data systems.The workshop brings together NJIT students and leading international researchers to exchange ideas, present emerging work, and explore new directions across vision-language models, multimedia retrieval, knowledge graphs, and human-centered AI.MMI serves as a foundation for building a long-term research community at NJIT, with the goal of evolving into a dedicated international conference on multimedia intelligence.
*Registration and participation are free.
*You must register to participate.
Workshop Vision
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Build a strong multimedia AI research community at NJIT
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Connect students with international researchers
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Explore emerging directions in multimodal intelligence
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Establish a foundation for a future international conference
Call for Participation
We invite students, researchers, and practitioners to participate.
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Multimodal AI and foundation models
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Multimedia retrieval
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Graph-based learning
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Knowledge graphs
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Human-centered AI
Invited Speakers
Prof. Shin'ichi Satoh
National Institute of Informatics (NII), JapanProf.
Shin'ichi Satoh is a Professor at the National Institute of Informatics (NII) in Tokyo, Japan, and a leading researcher in multimedia and computer vision.His research focuses on video analysis, multimedia information retrieval, and large-scale visual data understanding, with particular emphasis on extracting knowledge from broadcast video archives and complex visual datasets.Prof. Satoh has made significant contributions to image and video retrieval, multimedia databases, and visual content analysis, and he leads research efforts on intelligent systems that can interpret and organize visual information at scale.He earned his Ph.D. in Engineering from the University of Tokyo and has authored hundreds of publications across computer vision, machine learning, and multimedia computing, with impactful work spanning both foundational methods and real-world applications.At this workshop, Prof. Satoh brings deep expertise in multimedia AI and large-scale video understanding, offering insights into how intelligent systems can analyze and retrieve information from rich visual data sources.
Prof. Michael E. Houle
New Jersey Institute of Technology (NJIT), USA
Prof. Michael E. Houle is a Senior University Lecturer in Computer Science at the New Jersey Institute of Technology (NJIT), with extensive experience in machine learning, data mining, and algorithmic research.He earned his Ph.D. in Computer Science from McGill University and has held research and academic positions across Japan, Australia, and North America, including roles at the University of Sydney, IBM Tokyo Research Laboratory, and the National Institute of Informatics (NII) in Japan.Prof. Houle's research focuses on similarity search, high-dimensional data analysis, and intrinsic dimensionality, contributing foundational methods used in clustering, classification, and anomaly detection. His work on local intrinsic dimensionality (LID) has significantly influenced modern approaches to understanding complexity in machine learning and deep learning systems.He is a highly accomplished researcher with numerous publications and multiple best paper awards at leading venues such as ICDM, SISAP, and SDM, reflecting the impact of his contributions to data mining and AI.At this workshop, Prof. Houle brings deep expertise in theoretical and scalable machine learning, offering insights into how high-dimensional data can be effectively modeled, analyzed, and leveraged in modern AI systems.
Prof. Cathal Gurrin
Dublin City University (DCU), Ireland
Prof. Cathal Gurrin is a Full Professor in the School of Computing at Dublin City University (DCU), where he also serves as Assistant Head for International Engagement and Deputy Director of the ADAPT Centre.His research focuses on lifelogging, personal analytics, and multimedia information retrieval, with an emphasis on using wearable sensors and AI-driven data analysis to build assistive technologies that enhance human memory, health, and productivity.Prof. Gurrin is widely recognized as a pioneer in lifelogging, having continuously captured a personal digital record of his daily life since 2006 using wearable devices. His work explores how large-scale personal data can be organized, searched, and used to support real-world decision-making and cognitive assistance.He has led and contributed to numerous international research initiatives and is the founder and co-organizer of major benchmarking efforts such as the Lifelog Search Challenge, helping advance global research in multimedia retrieval and human-centered AI.At this workshop, Prof. Gurrin brings deep expertise at the intersection of AI, human-centered computing, and large-scale personal data systems, offering insights into how emerging technologies can augment human capabilities.
Prof. Chua Tat-Seng
National University of Singapore (NUS), Singapore
Prof. Chua Tat-Seng is the KITHCT Chair Professor in the School of Computing at the National University of Singapore (NUS). He is a leading researcher in artificial intelligence and has played a foundational role in shaping computing research at NUS, including serving as the Founding Dean of the School of Computing. He is the co-Director of NExT, a joint research center between NUS and Tsinghua University.His research spans multimodal AI, conversational search and recommendation systems, and responsible AI, with a strong focus on understanding and extracting insights from large-scale unstructured data such as text, images, and video.Prof. Chua has made significant contributions to multimedia information retrieval, social media analytics, and recommendation systems, influencing both academia and real-world applications in areas like e-commerce and intelligent systems.He is a highly prolific scholar with hundreds of publications and thousands of citations, and his recent work continues to push the boundaries of large language models, multimodal learning, and AI-driven recommendation technologies.At this workshop, Prof. Chua brings deep expertise in AI systems that integrate multiple data modalities, offering insights into the future of intelligent, human-centered information systems.
Organizers
Vincent Oria (NJIT, USA) and Shin'ichi Satoh (NII, Japan)
Co-organized by Mohammad Dindoost (GSA, NJIT)
Sponsors
