About

The Laboratory for AI, Robotics, and Automation (LARA) at UC Davis is at the forefront of research in artificial intelligence and robotics, focusing on the development of autonomous systems that can learn, adapt, and operate in complex environments. Our interdisciplinary research spans across cutting-edge technologies, including machine learning, reinforcement learning, and robotic systems, with applications in automation, autonomous vehicles, and human-robot interaction.

Autonomous Systems
Industrial Automation
Health Diagnostics

Latest Work

InterACT: Inter-dependency Aware Action...

InterACT: Inter-dependency Aware Action...

Inter-dependency Aware Action Chunking with Hierarchical Attention Transformers for Bimanual Manipulation.

John Doe
Jane Smith
Performance of Automated ML in Predicting...

Performance of Automated ML in Predicting...

Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.

Alice Green
Bob Brown
Targeted Collapse Regularized Autoencoder...

Targeted Collapse Regularized Autoencoder...

Targeted collapse regularized autoencoder for anomaly detection: black hole at the center.

Emma White
Liam Johnson
Hierarchical End-to-End Autonomous...

Hierarchical End-to-End Autonomous...

Hierarchical end-to-end autonomous navigation through few-shot waypoint detection.

Sophia Martin
Oliver Clark
CarDreamer: Open-Source Learning Platform...

CarDreamer: Open-Source Learning Platform...

CarDreamer: Open-Source Learning Platform for World Model based Autonomous Driving.

Michael Hall
Amelia Thomas
Assessing Driver Compliance and Traffic Flow...

Assessing Driver Compliance and Traffic Flow...

Assessing the impact of driver compliance on traffic flow and safety in work zones amid mixed autonomy scenarios.

William Wright
Ava Lee
Performance of Automated ML in Predicting...

Performance of Automated ML in Predicting...

Performance of Automated Machine Learning in Predicting Outcomes of Pneumatic Retinopexy.

James Harris
Charlotte Walker
Active Vision Might Be All You Need...

Active Vision Might Be All You Need...

Exploring active vision in bimanual robotic manipulation: Might be all you need.

Henry Davis
Emily Wilson
Targeted Collapse Regularized Autoencoder...

Targeted Collapse Regularized Autoencoder...

Targeted collapse regularized autoencoder for anomaly detection in black hole models.

Jack Garcia
Ella Rodriguez
Deep Bayesian-Assisted Keypoint Detection...

Deep Bayesian-Assisted Keypoint Detection...

Deep Bayesian-Assisted Keypoint Detection for Pose Estimation in Assembly Automation.

Logan Martinez
Grace Thompson
Regularized Cycle Consistent GAN for Anomaly...

Regularized Cycle Consistent GAN for Anomaly...

Regularized cycle consistent generative adversarial network for anomaly detection.

Daniel Lopez
Mia King
Memory-Augmented GANs for Anomaly Detection...

Memory-Augmented GANs for Anomaly Detection...

Memory-augmented generative adversarial networks for anomaly detection.

David Scott
Layla Turner
Anomaly Detection with Domain Adaptation...

Anomaly Detection with Domain Adaptation...

Anomaly detection with domain adaptation in industrial systems.

Sebastian Rivera
Zoey Baker
Attention Transformers for Bimanual Manipulation

Attention Transformers for Bimanual Manipulation

Attention Transformers for Bimanual Manipulation

Sebastian Rivera
Zoey Baker

Frequently asked questions

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Crafted with ❤️ by Mohnish Gopi