Gaurav R. Ghosal

University of California, Berkeley

Papers

1

Total Citations

6

H-Index

1

About

Dr. Gaurav R. Ghosal is a rising researcher at the intersection of robotics, artificial intelligence, and human-robot interaction, with a primary focus on preference-based reward learning. His work addresses a fundamental challenge in autonomous systems: how to efficiently and accurately infer a human user's intended task objectives through simple comparative queries. Dr. Ghosal's most notable contribution is his development of a generalized acquisition function for actively synthesizing preference queries, which maximizes information gain about the underlying reward function parameters. This approach significantly improves data efficiency in teaching robots complex behaviors, reducing the number of human demonstrations or queries needed. His 2024 paper on this topic has already garnered 6 citations, reflecting its timely impact on the field. By enabling robots to ask more informative questions, Dr. Ghosal's research accelerates the deployment of assistive and autonomous systems that can learn from non-expert users, making human-robot collaboration more intuitive and accessible. His work represents a key step toward robots that truly understand and adapt to human preferences.

Research Focus

Key Achievements

1
H-Index
1
Papers
6
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
A Generalized Acquisition Function for Preference-based Reward Learning
6 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago