Learning and Intelligent Systems (LIS) @ MIT

@MIT_LISLab

PIs: Leslie Pack Kaelbling, Tomás Lozano-Pérez AI/ML/Robotics Research @MIT_CSAIL Website: lis.csail.mit.edu

Joined November 2020

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Learning and Intelligent Systems (LIS) @ MIT
@MIT_LISLab
Jun 3
Exciting to see the launch of the NVIDIA Isaac GR00T Reference Humanoid Robot. Open, research-focused humanoid platforms can help accelerate progress across the robotics community. Looking forward to the innovations this enables. A great contribution from NVIDIA Robotics!
NVIDIA Robotics
@NVIDIARobotics
Jun 1
NVIDIA announces the first open humanoid robot reference design built for robotics research. The NVIDIA Isaac GR00T Reference Humanoid Robot combines the @UnitreeRobotics H2 humanoid robot, @SharpaRobotics Wave five-fingered hands for dexterous manipulation, Jetson Thor onboard
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Learning and Intelligent Systems (LIS) @ MIT
@MIT_LISLab
Apr 24
Congrats to the newest PhD grad from the lab @nishanthkumar23 🤖
Nishanth Kumar
@nishanthkumar23
Apr 23
PhDone and officially a robot doctor! Thanks to incredible advisors Leslie and Tomás @MIT_LISLab and my secret bonus advisor @tomssilver - I’m so so lucky to have gotten to do research with them. I’m excited to keep working on making useful generalist robots a reality 🤖🚀
Learning and Intelligent Systems (LIS) @ MIT
@MIT_LISLab
Mar 11
Check out a new robot manipulation system from members of the group combining foundation models with TAMP!
Nishanth Kumar
@nishanthkumar23
Mar 11
State-of-the-art robot policies often need hundreds of hours of data. What if we needed none? Introducing TiPToP: a manipulation system that zero-shots open-world tasks from pixels and language using vision foundation models and GPU-parallelized Task and Motion Planning (TAMP).
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Learning and Intelligent Systems (LIS) @ MIT
@MIT_LISLab
Nov 25, 2025
Check out new work from @nishanthkumar23 in the group on learning and planning with symbolic world models!
RoboPapers
@RoboPapers
Nov 24, 2025
Reasoning over long horizons would allow robots to generalize better to unseen environments and settings zero-shot. One mechanism for this kind of reasoning would be world models, but traditional video world models still tend to struggle with long horizons, and are very data
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Learning and Intelligent Systems (LIS) @ MIT
@MIT_LISLab
Nov 23, 2025
tune in soon for a podcast episode covering new work from the group!
RoboPapers
@RoboPapers
Nov 21, 2025
Full episode dropping soon! Geeking out with @nishanthkumar23 on From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models pix2pred.csail.mit.edu Co-hosted by @micoolcho @chris_j_paxton
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