Area of research
Aerospace Engineering · Computer Vision and Pattern Recognition
Research interest
Research interests include Computer science, Artificial intelligence, Neuroscience, Computer vision, Robot, and Psychology.
A brain-wide map of neural activity during complex behaviour
AutoTAMP: Autoregressive Task and Motion Planning with LLMs as Translators and Checkers
Scalable Multi-Robot Collaboration with Large Language Models: Centralized or Decentralized Systems?
How to Train Your Neural Control Barrier Function: Learning Safety Filters for Complex Input-Constrained Systems
Mice alternate between discrete strategies during perceptual decision-making
Extracting the dynamics of behavior in sensory decision-making experiments
Search and rescue under the forest canopy using multiple UAVs
Physics-informed reinforcement learning optimization of nuclear assembly design
Robust Object-based SLAM for High-speed Autonomous Navigation
Deep Inference for Covariance Estimation: Learning Gaussian Noise Models for State Estimation
Efficient inference for time-varying behavior during learning.
PubMed 2018cited by 26position: first
Safe Visual Navigation via Deep Learning and Novelty Detection
Bayesian Learning for Safe High-Speed Navigation in Unknown Environments
Stable population coding for working memory coexists with heterogeneous neural dynamics in prefrontal cortex
An analysis of wind field estimation and exploitation for quadrotor flight in the urban canopy layer
Inferring Maps and Behaviors from Natural Language Instructions
Asking for Help Using Inverse Semantics
Drift-free humanoid state estimation fusing kinematic, inertial and LIDAR sensing
Probabilistically safe motion planning to avoid dynamic obstacles with uncertain motion patterns
Indoor scene recognition by a mobile robot through adaptive object detection
State estimation for aggressive flight in GPS-denied environments using onboard sensing
Estimation, planning, and mapping for autonomous flight using an RGB-D camera in GPS-denied environments