Srijita Das

About

Srijita Das is a leading researcher at the intersection of artificial intelligence and human-robot interaction, with a primary focus on Human-in-the-Loop (HITL) Reinforcement Learning. Her seminal 2024 survey, "Human-in-the-Loop Reinforcement Learning: A Survey and Position on Requirements, Challenges, and Opportunities," has already garnered 131 citations, establishing it as a foundational reference in the field. In this work, Das repositions reinforcement learning as an inherently collaborative paradigm, arguing that even autonomous agents must be designed with continuous human oversight and feedback. She systematically outlines the critical requirements, technical challenges, and emerging opportunities for integrating human expertise into RL systems, bridging the gap between theoretical algorithms and real-world deployment. Earlier, Das demonstrated her engineering acumen with her 2018 work on a "Mimicking Robotic Arm," where she designed and executed a mechanical arm using Arduino-UNO that replicates human motion via a Human-Machine Interface. This project showcased her ability to translate complex AI concepts into tangible, functional hardware. Through her research, Das is shaping how future AI systems learn safely and effectively alongside humans, making her work essential reading for students and researchers in interactive AI and robotics.

Research Focus

Key Achievements

Top Papers

1. 1
   Human-in-the-Loop Reinforcement Learning: A Survey and Position on Requirements, Challenges, and Opportunities

   131 citations · 2024
2. 2
   Mimicking Robotic Arm

   4 citations · 2018

Key Collaborators

Contact & Links