David V. Pynadath

About

David V. Pynadath is a leading researcher in human-robot interaction and multi-agent systems, with a focus on trust calibration and theory of mind in autonomous systems. His work bridges artificial intelligence, robotics, and cognitive science to enable effective human-robot teamwork. Pynadath's most influential contributions include foundational research on trust calibration within human-robot teams, as demonstrated by his highly cited 2016 paper (200 citations) on automatically generated explanations for trust accuracy. He co-edited the seminal book "Plan, Activity, and Intent Recognition: Theory and Practice" (156 citations), which remains a key resource in the field. His early work on the TEAMCORE infrastructure (1999) and distributed robot-agent-person teams (2003, 131 citations) established frameworks for coordinating heterogeneous entities in complex environments. Pynadath has also explored how embodiment, explanations, and expectations shape trust and performance in human-robot teams, and his recent survey on robots with Theory of Mind (2022) highlights his ongoing impact. With over 600 total citations, his research continues to inform the design of autonomous systems that can dynamically model and adapt to human teammates, advancing the frontier of human-agent collaboration.

Research Focus

Key Achievements

Top Papers

1. 1
   Trust calibration within a human-robot team: Comparing automatically generated explanations

   200 citations · 2016
2. 2
   Plan, Activity, and Intent Recognition: Theory and Practice

   156 citations · 2014
3. 3
   A prototype infrastructure for distributed robot-agent-person teams

   131 citations · 2003
4. 4
   Is It My Looks? Or Something I Said? The Impact of Explanations, Embodiment, and Expectations on Trust and Performance in Human-Robot Teams

   47 citations · 2018
5. 5
   Teamwork in Cyberspace: Using TEAMCORE to Make Agents Team-Ready

   44 citations · 1999
6. 6
   Robots with Theory of Mind for Humans: A Survey

   14 citations · 2022
7. 7
   A Markovian Method for Predicting Trust Behavior in Human-Agent Interaction

   14 citations · 2019
8. 8
   Exploring the Implications of Virtual Human Research for Human-Robot Teams

   12 citations · 2015
9. 9
   Intelligent Agents for Virtual Simulation of Human-Robot Interaction

   11 citations · 2015
10. 10
    Getting Robots, Agents and People to Cooperate: An Initial Report

    10 citations · 2003

Key Collaborators

Contact & Links