The Next Generation of Machine Learning
Every company is asking the same questions right now: what can AI agents do? Are they safe? And what will they cost at scale.
MIT CSAIL is working on answers. Our faculty lead the field in agentic security, cost, alignment, interaction, and deployment. We're inviting companies to join our Agentic AI Research Initiative and help our researchers shape what comes next.
AI agent adoption is outpacing understanding. Companies are shipping pilots without clear budgeting, evaluation, or security plans, and no one yet knows how to align agents with human values or predict their behavior in multi-agent environments. Meanwhile, CSAIL researchers are pushing the boundary of what’s possible with AI agents in ways few R&D departments can match. Their efforts benefit from industry input to align academic inquiry with real commercial needs.
CSAIL Alliances Research Initiatives bring together a small cohort of companies around a pressing technological challenge. The model is deliberately two-way: partners bring problems and CSAIL faculty bring curiosity, creativity, and academic rigor to explore solutions. Participating companies also get broad exposure to CSAIL research, talent, and networking, surfacing innovation companies might never find on their own.
Join at the ground floor and have direct input into the initiative's direction, themes, and events.
- Set the agenda of research by identifying the most pressing issues that MIT is uniquely positioned to address,
- Vote on proposals from CSAIL researchers that align best with your organization’s priorities,
- Gain a front-row seat as new results and insights emerge from the lab,
- Enjoy broad access to CSAIL, including cutting-edge CS and AI research, access to world class talent, workshops on CSAIL-created open source technology, opportunities to interact with CSAIL startups, and preferential access to professional education resources,
- Interact with other forward-thinking companies, exchanging ideas, challenges, and lessons learned.
Because this space is moving so fast, we're convening a fall conference focused on Agentic AI. CSAIL faculty will speak on the latest research with interactive Q&A panels, industry speakers, and networking opportunities. Founding member companies will be personally welcomed to campus and highlighted during the event.
Shape how the world’s leading AI lab approaches Agentic AI systems.
Contact Glenn Wong at glennw@mit.edu to get involved.
CSAIL Director & EECS Professor
Interests: Robotics, Autonomy, Human-Robot Interaction, Multi-Agent Systems, Liquid AI, Agent Memory & Reasoning
Note: This is just a partial list of the CSAIL expertise related to Agentic AI. Any of our 120+ PIs are welcome to get involved with the initiative.
Pulkit Agarwal, EECS Associate Professor, MIT CSAIL
Interests: Robotics, Manipulation, Physics-Aware AI, Continuous Learning, Perception, Hardware Design, Reinforcement Learning
Jacob Andreas, EECS Associate Professor, MIT CSAIL
Interests: Natural Language Processing, AI Alignment, Multimodal Systems, Reinforcement Learning, Muti-Agent Systems
Michael Cafarella, Principal Research Scientist, MIT CSAIL
Interests: Database Systems, Information Extraction, Data Integration, Agent-Aided Design, AI Benchmarking, AI-Powered Analytics
Manya Ghobadi, EECS Associate Professor, MIT CSAIL
Interests: Efficient Systems for Machine Learning, High-Performance Cloud Infrastructure, Network Optimization
Dylan Hadfield-Menell, EECS Associate Professor, MIT CSAIL
Interests: AI Alignment, Multi-Agent Systems, Reinforcement Learning, Reward Optimization, AI Evaluation, Interpretability, Red Teaming, AI Governance
Phillip Isola, EECS Associate Professor, MIT CSAIL
Interests: Computer Vision, Machine Learning, Simulation, Video Generation, Multimodal Systems, Reward Optimization, Physics-Aware AI
Omar Khattab, EECS Assistant Professor, MIT CSAIL
Interests: Last-Mile AI, Natural Language Processing, Intelligent Systems, Declarative AI Programming, Prompt Optimization
Una-May O’Reilly, Senior Research Scientist, MIT CSAIL
Interests: Cybersecurity, Differential Privacy, Evolutionary Computation, Multi-Agent Systems, Adversarial Deep Learning, Red Teaming 
Vincent Sitzmann, EECS Associate Professor, MIT CSAIL
Interests: Physical AI, Video Generation, Robotics, Physics-Aware AI, Self-Supervised Learning, Diffusion Models
