New
NSF CAREER award
UT Austin · Robotics & ML
We build learning, reasoning, and verification for fleets of robots and AI agents.
Research
What we work on
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Swarm Coordination & Fleet Learning
From cooperative planning to collective data collection.
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Edge–Cloud Systems for Embodied AI
Efficient perception and inference across networks.
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Neuro-Symbolic Video Understanding
Grounding foundation models in temporal logic.
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Trustworthy & Verifiable Machine Learning
Formal and cryptographic guarantees for AI models.
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Time-Series Generation & Forecasting
Conditional, constrained generation of temporal data.
Latest
News
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Oguzhan B.'s paper TensorCommitments: A Lightweight Verifiable Inference for Language Models was accepted to NeurIPS 2026! Read the blog post and explore the code. New
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Oguzhan B.'s paper AttentionViG: Cross-Attention-Based Dynamic Neighbor Aggregation in Vision GNNs was accepted to the Fifth Learning on Graphs Conference (LoG 2026)! Read the blog post.
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Sandeep Chinchali received the NSF CAREER award for "CAREER: Foundations of Cloud Robotics – Where Neural Networks Meet Physical Networks". Read the UT ECE announcement. award
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Po-han's paper UNCAP: Uncertainty-Guided Neurosymbolic Planning Using Natural Language Communication for Cooperative Autonomous Vehicles was nominated for the best paper award at AAMAS 2026!
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Po-han passed his PhD defense. defense
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Arnab's paper EntroLLM: Entropy Encoded Weight Compression for Efficient Large Language Model Inference on Edge Devices was presented at ICASSP 2026! Read the blog post and explore the code.
Lab life
Out in the field
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CoRL 2022, Auckland -
GLOBECOM 2025, Taipei -
CoRL 2022, Auckland -
RSS 2022, New York -
CoRL 2022, Auckland -
RSS 2022, Times Square -
CoRL 2022, Auckland -
CoRL 2022, Auckland
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