I am a Postdoctoral Researcher at Microsoft Research India, working broadly on efficient and intelligent retrieval systems.
Prior to Microsoft, I completed my PhD in the Department of Computer Science at Duke University, advised by Pankaj K. Agarwal. My doctoral research focused on algorithmic problems in machine learning and large-scale data processing, such as clustering, distribution learning, search, and query optimization. In particular, I designed robust algorithms that remain effective under noise, uncertainty, and imperfect information. I also spent Summer 2024 as a Visiting Scientist at Cornell University, collaborating closely with Sainyam Galhotra.
* Equal contribution; authors are listed in alphabetical order.
† Equal leading contribution.
Aryan Esmailpour†, Rahul Raychaudhury†, Sainyam Galhotra, and Stavros Sintos. Clustering with Weak Distance Oracles. Annual Conference on Neural Information Processing Systems (NeurIPS), 2026.
Rahul Raychaudhury, Aryan Esmailpour, Sainyam Galhotra, and Stavros Sintos. Metric k-clustering using only Weak Comparison Oracles. International Conference on Learning Representations (ICLR), 2026
Rahul Raychaudhury, Haibo Xu, Pankaj K. Agarwal, Stavros Sintos, Jun Yang. Coresets for Robust Query Optimization. ACM Symposium on Principles of Database Systems (PODS), 2026.
Rahul Raychaudhury, Wen-Zhi Li, Syamantak Das, Sainyam Galhotra, and Stavros Sintos. Metric Clustering and Graph Optimization Problems using Weak Comparison Oracles. Annual Conference on Learning Theory (COLT), 2025.
Mohsen Dehghankar, Rahul Raychaudhury, Stavros Sintos, and Abolfazl Asudeh. Fair Set Cover. ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD), 2025.
Pankaj K. Agarwal, Sariel Har-Peled, Rahul Raychaudhury, Stavros Sintos.* Fast Approximation Algorithms for Piercing Boxes by Points. ACM-SIAM Symposium on Discrete Algorithms (SODA), 2024.