About the MMI Series
What is MMI?
The MultiMedia Intelligence Workshop Series (MMI) is an annual research event hosted at the New Jersey Institute of Technology (NJIT). It brings together students, faculty, and international researchers working at the intersection of multimedia, artificial intelligence, and multimodal learning.
Each edition is organized around a focused theme and features invited talks from leading researchers across institutions worldwide. Topics span multimedia retrieval, multimodal reasoning, vision-language systems, trustworthy AI, information access, intelligent systems, human-centered computing, and emerging directions in artificial intelligence.
MMI serves as a platform for exchanging ideas, building collaborations, and fostering connections between researchers from diverse backgrounds and disciplines.
Why Multimedia Intelligence?
Multimedia Intelligence explores how intelligent systems understand, retrieve, reason over, and interact with information across multiple modalities, including text, images, video, audio, graphs, and structured data.
As AI systems become increasingly multimodal, advances in machine learning, information retrieval, computer vision, natural language processing, human-computer interaction, and intelligent systems are becoming deeply interconnected. Multimedia Intelligence provides a natural framework for bringing these communities together and addressing challenges that span multiple forms of information and reasoning.
MMI aims to serve as a forum where researchers from these areas can exchange ideas, identify common challenges, and explore emerging directions in intelligent multimodal systems.
Community Focus
MMI is built around the belief that meaningful research communities are created through sustained interaction, collaboration, and mentorship.
Unlike traditional conferences that primarily focus on paper presentations, MMI emphasizes discussion, accessibility, and long-term relationship building. The workshop creates opportunities for students, faculty, and researchers at different career stages to interact directly, exchange ideas, and establish connections that extend beyond the event itself.
Each edition contributes to a growing international network of researchers working across Multimedia Intelligence and related disciplines.
Student Engagement
A central goal of MMI is to provide students with direct access to leading researchers and emerging research directions.
Through invited talks, discussions, networking opportunities, and future initiatives such as poster sessions and student showcases, MMI seeks to help students develop research connections, explore interdisciplinary topics, and engage with the broader scientific community.
By lowering barriers between students and established researchers, the workshop encourages mentorship, collaboration, and the development of future research leaders.
Core Principles
- Community before conference.
- Meaningful interactions between students and researchers.
- International collaboration and interdisciplinary exchange.
- Open discussion of emerging research directions.
- Accessibility, mentorship, and long-term relationship building.
- Advancing the field of Multimedia Intelligence through shared knowledge and collaboration.
Vision
MMI is built around community. The aim is to connect students with world-class researchers, spark collaborations that outlast the workshop, and grow a research network that strengthens with each edition.
The long-term vision is for MMI to evolve into a leading international forum for Multimedia Intelligence research, fostering collaboration among students, researchers, and practitioners worldwide.
As the community grows, future editions may expand to include poster sessions, tutorials, industry participation, student research showcases, collaborative initiatives, and other activities that strengthen engagement across the Multimedia Intelligence ecosystem.
Looking Ahead
Future editions of MMI will continue exploring emerging topics such as multimodal reasoning, trustworthy AI, agentic systems, human-centered AI, intelligent retrieval, and advances in multimedia understanding.
The workshop series seeks to create a sustainable research community that extends beyond annual events, enabling new collaborations, mentorship opportunities, and research partnerships across institutions worldwide.
MMI Community Snapshot
Researchers from North America, Europe, and Asia
Edition History
The series has held two editions to date:
Future editions will continue expanding the community while exploring new directions in Multimedia Intelligence research.
Series Coordination
Mohammad Dindoost
Mohammad Dindoost
Role: Series Coordination & Community Organization
Mohammad Dindoost is a Ph.D. Candidate and Research Assistant in Computer Science at the New Jersey Institute of Technology (NJIT), where he has been conducting research for over 3.5 years. His work focuses on large-scale graph analytics, Graph Neural Networks (GNNs), and graph-based machine learning, with an emphasis on designing scalable algorithms for massive datasets at the intersection of deep learning and high-performance computing.
His research bridges theoretical graph algorithms and practical systems capable of handling real-world data challenges, contributing to advances in graph coarsening and large-scale graph learning, areas increasingly relevant to multimedia retrieval, multimodal AI, and intelligent data systems. His work on evaluating the efficiency and novelty of large language models (LLMs) received the Outstanding Student Paper Award at IEEE HPEC 2025.
Beyond research, Mohammad serves as Vice President of Academic Affairs for the Graduate Student Association (GSA) at NJIT, where he helps organize interdisciplinary academic initiatives. He is the co-founder and series coordinator of the MMI Workshop, building a growing community of students and international researchers in Multimedia Intelligence. He has also served as a Program Committee Member and Reviewer for ACM ICMR 2025.
Institutional Support
