Assistant Professor
Harish is an Assistant Professor in the School of Interactive Computing at Georgia Institute of Technology. He is also a core faculty member of Georgia Tech’s Institute for Robotics and Intelligent Machines (IRIM).
He works on structured algorithms that help robots reliably operate and collaborate in unstructured environments alongside humans. His research interests span the areas of robot learning, human-robot interaction, and multi-agent systems. Harish’s work has been recognized by the ASME DSCC Best Student Robotics Paper Award (2015), IEEE CSS Video Contest Award (2015), UTC Institute for Advanced System Engineering Graduate Fellowship (2016-2018), and Georgia Tech’s College of Computing Outstanding Post-Doctoral Research Award (2019) and Outstanding Research Scientist Award (2020).
Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation
A Sampling-based Approach for Heterogeneous Coalition Scheduling with Temporal Uncertainty
Concurrent Constrained Optimization of Unknown Rewards for Multi-Robot Task Allocation
Inferring Implicit Trait Preferences from Demonstrations of Task Allocation in Heterogenous Teams
Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration
Learning Trait Preferences for Task allocation in Heterogeneous Multi-Agent Teams
Leveraging Cognitive States in Human-Robot Teaming
Constrained Reinforcement Learning for Dexterous Manipulation
Fast Anticipatory Motion Planning for Close-Proximity Human-Robot Interaction
Neural Geometric Fabrics: Efficiently Learning High-Dimensional Policies from Demonstration
Resource-Aware Adaptation of Heterogeneous Strategies for Coalition Formation
GRSTAPS: Graphically Recursive Simultaneous Task Allocation, Planning, and Scheduling
Resilient Coalition Formation in Heterogeneous Teams via Imitation Learning
Desperate Times Call for Desperate Measures: Towards Risk-Adaptive Coalition Formation
An Interleaved Approach to Trait-Based Task Allocation and Scheduling
Predicting Individual Human Performance in Human-Robot Teaming
STRATA : Unified Framework for Task Assignments in Large Teams of Heterogeneous Agents
Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations
Human-in-the-Loop Robot Control for Human-Robot Collaboration
Approximated Dynamic Trait Models for Heterogeneous Multi-Robot Teams
Anticipatory Human-Robot Collaboration via Multi-Objective Trajectory Optimization
STRATA : Unified Framework for Task Assignments in Large Teams of Heterogeneous Agents
Recent Advances in Robot Learning from Demonstration
Learning Hierarchical Task Networks with Preferences from Unannotated Demonstrations
Taking Recoveries to Task : Recovery-Driven Development for Recipe-based Robot Tasks
Skill Acquisition via Automated Multi-Coordinate Cost Balancing
Learning position and orientation dynamics from demonstrations via contraction analysis