Workshops & Tutorials Organized

• 3rd Workshop on Learning Efficient Abstractions for Planning (LEAP)

  Co-chair · CoRL 2025
• 8th Workshop on Generalization in Planning (GenPlan)

  Co-chair · AAAI 2025
• 2nd Workshop on Learning Efficient Abstractions for Planning (LEAP)

  Co-chair · CoRL 2024
• 1st Workshop on Learning Efficient Abstractions for Planning (LEAP)

  Co-chair · CoRL 2023
• Tutorial on “Integrated Task and Motion Planning: Foundations and Research Frontiers”

  Co-organizer · IJCAI 2023

Reviewing & Program Committees

Area Chair / Associate Editor

CoRL 2026, ICRA 2026

Journal reviewer

IJRR, RA-L, AIJ, JAIR, T-RO

Conference reviewer / PC member

RSS 2026, ICAPS 2026, ICRA 2026, AAAI 2026, IROS 2025, CoRL 2025, AAAI 2025, ICLR 2025, ICLR 2024, RSS 2024, IROS 2024, NeurIPS 2023, AAMAS 2022, ICRA 2022, ICRA 2021, ICAPS 2021, AAAI 2021, RSS 2021, IJCAI 2021, AAAI 2020

Workshop reviewer / PC member

NYRL 2025, RSS 2025 (RoboReps), CoRL 2025 (LEAP), AAAI 2025 (GenPlan), CoRL 2024 (LEAP), CoRL 2023 (LEAP), NeurIPS 2023 (GenPlan)

Teaching

• CSE 571 — Artificial Intelligence (graduate)

  Graduate Teaching Assistant · Arizona State University · Fall 2018, Spring 2019, Spring 2023

  Led tutorials on ROS, first-order logic, and PDDL. Led development of the ROS-based course projects and auto-grader used to evaluate student implementations of search, automated planning, and reinforcement learning.

• CSE 205 — Object-Oriented Programming

  Graduate Teaching Assistant · Arizona State University · Spring 2022

  Ran four hours of recitations each week on object-oriented programming in Java, and designed midterms, assignments, and grading rubrics.

Mentoring

• Benned Hedegaard

  Ph.D. student, Brown University — learning for task and motion planning
• Ziyi Yang

  Ph.D. student, Brown University — foundation models for learning interpretable robot models
• Yichen Wei

  M.Sc. student, Brown University — learning for task and motion planning
• Ahmed Jaafar

  Research assistant, Brown University — robot learning (now AFRL)
• Jayesh Nagpal

  Ph.D. student, ASU — learning abstractions for task and motion planning
• Kyle Atkinson

  B.Sc. thesis, ASU — hierarchical planning (now Raytheon Technologies)
• Abhyudaya Srinet

  M.Sc. thesis, ASU — learning abstractions for motion planning (now MiM-Essay)
• Deepak Kala Vasudevan

  M.Sc. thesis, ASU — generalization in planning (now Amazon Robotics)
• Kiran Prasad

  Learning abstractions for motion planning (now Amazon Robotics)

Honors & Awards

• SCAI Doctoral Fellowship, Arizona State University
  2022, 2023
• Best Paper Award, ICRA 2025 Workshop on Language and Semantics of Task and Motion Planning
  2025
• Best Demo Award, AAMAS 2022
  2022
• GPSA, SCAI, and ASU Graduate College travel grants (IJCAI 2023)
  2023
• Excellence Award, Gujarat Technological University
  2016, 2017