About Me

I am a Research Scientist at Meta, where I work on generative recommendation systems. I earned my Ph.D. in Computer Science and Engineering from Texas A\&M University, College Station, advised by Dr. Guni Sharon as part of the Pi Star Lab. My research interests lie at the intersection of reinforcement learning, combinatorial optimization, recommendation systems, and machine learning.

In the summer of 2023, I was a visiting student at the University of Alberta and the Alberta Machine Intelligence Institute (Amii), where I worked with Dr. Nathan Sturtevant and Dr. Levi Lelis. Earlier, in the summer of 2017, I was a visiting student at the Indian Institute of Technology (IIT) Roorkee, working with Dr. Biplab Banerjee.

Contact Details

  Email:
sumedhpendurkar@tamu.edu
  Address:
EABC, Room 107B, 588 Lamar St, College Station, TX 77840

Education Details

  Texas A&M University, College Station
  CGPA: 4/4
  Doctor of Philosophy (Ph.D.), Computer Science
  College of Engineering, Pune
  CGPA: 9.12/10
  Bachelor of Technology, Computer Engineering

CV

News

[06/2025] I joined Meta as a Research Scientist - working on generative recommendation systems!
[06/2025] I defended my PhD dissertation on Learnable Guiding Functions for State-Space Search Algorithms!
[01/2025] I am joining Decompute Inc. as a AI researcher intern for spring 2025
[12/2024] 1 paper accepted at AAAI workshop on Multi-Agent Path Finding!
[05/2024] I passed my prelims exam and PhD thesis proposal!
[03/2024] 1 paper on curriculum generation for ML-guided state-space search algorithm accepted at Annual Symposium on Combinatorial Search (SoCS)!
[10/2023] 1 paper on unscalability of completely informed heuristic estimation conditionally accepted at Transactions of Machine Learning Research (TMLR)!
[06/2023] 1 paper accepted at the IBPSA Conference on Buildings and Simulations!
[02/2023] I will be visiting the Dept. of Computer Science at the University of Alberta with Dr. Nathan Sturtevant and Dr. Levi Lelis for the summer!
[02/2023] Received Travel Grant from Dept. of Computer Science and Engineering at Texas A\&M University for travel to AAMAS 2023
[01/2023] 1 full paper (acceptance rate: 23.3%) accepted at AAMAS 2023!
[10/2022] 1 paper accepted at workshop
[08/2022] Teaching Assistant for CSCE 689 (Special Topics) - Deep Reinforcement Learning Fall 2022
[05/2022] 1 extended abstract accepted at SOCS
[01/2022] I will be joining Niantic as a machine learning scientist intern for summer 2022
[01/2022] Teaching Assistant for CSCE 633 - Machine Learning for Spring 2021
[08/2021] Teaching Assistant for CSCE 676 - Data Mining and Analysis for Fall 2021
[06/2021] 1 Paper on Regret Minimization using Imitation Learning (JIRL) accepted in IROS!
[04/2020] Pi-star Skyblazers (Sheelabhadra Dey and Me) win the 2020 TAMIDS Data Science Competition Graduate Divison [View Code] [View Presentation Video]

Publications

Simpson C., Pendurkar S., Sharon G. Goal Distribution in Conflict-Based Search for Multi-Agent Pathfinding and its Implications to Monte-Carlo Sampling AAAI workshop on Multi-Agent Path Finding (MAPF), 2025

Pendurkar S., Lelis L., Sturtevant N., Sharon G. Curriculum Generation for Learning Guiding Functions in State-Space Search Algorithms. Proceedings of the 17th International Symposium on Combinatorial Search, 2024

Pendurkar S., Huang T., Juba B., Zhang J., Koenig S., Sharon G. The (Un)Scalability of Informed Heuristic Function Estimation in NP-Hard Search Problems. Transactions of Machine Learning Research, 2023

Pendurkar S., Chow C., Luo J., Sharon G. Bilevel Entropy based Mechanism Design for Balancing Meta in Video Games. Proceedings of the 22nd International Conference on Autonomous Agents and Multi-Agent Systems, 2023

Anis M., Pendurkar S., Yi Y., Sharon G. Comparison Between Popular Genetic Algorithm (GA)-based Tool and Covariance Matrix Adaptation – Evolutionary Strategy (CMA-ES) for Optimizing Indoor Daylight. In Proceedings of Building Simulation 2023: 18th Conference of IBPSA, 2023.

Pendurkar S., Huang T., Koenig S., Sharon G. The (Un)Scalability of Heuristic Approximators for NP-Hard Search Problems.In I (Still) Can't Believe It's Not Better! NeurIPS 2022 Workshop

Pendurkar S., Huang T., Koenig S., Sharon G. A Discussion on the Scalability of Heuristic Approximators. In Proceedings of the International Symposium on Combinatorial Search, 2022

Dey S., Pendurkar S., Hanna J., Sharon G. A Joint Imitation-Reinforcement Learning Framework for Reduced Baseline Regret. International Conference on Intelligent Robots and Systems (IROS) 2021, 2021.

Pendurkar S., Banerjee B., Saha S., Bovolo F. Single Image Super-Resolution for Optical Satellite Scenes using Deconvolution Network. International Conference on Image Analysis and Processing (ICIAP) 2019, 2019.

Saha S., Sudhakaran S., Banerjee B., Pendurkar S. Semantic Guided Deep Unsupervised Image Segmentation, . International Conference on Image Analysis and Processing (ICIAP) 2019, 2019.

Pendurkar S., Kolpekwar S., Dhoot S., Haribhakta Y., Banerjee B. Attention Based Multi-Modal Fusion Architecture for Open-Ended Video Question Answering Systems. Third International Conference on Computing and Network Communications (CoCoNet'19), 2019.

G.Juvekar, S.Desai, A.Godse, S.Pendurkar et al., Maximizing Cubesat telemetry throughput by adaptive channel coding, 68th International Astronautical Congress, Adelaide, Australia, 2017

S.Desai, G.Juvekar, S.Pable, S.Malwadkar, D.Shaha, A.Gadkari, S.Pendurkar et al., Design of low cost ground station without the use of a front-end amplifier , 68th International Astronautical Congress, Adelaide, Australia, 2017

S.Pable, A.Gadkari, D.Shaha, G.Juvekar, S.Desai, S.Pendurkar et al., Application of Solar Sail as a Reflector for Nano Satellite Antenna System , 68th International Astronautical Congress, Adelaide, Australia, 2017

Blogs