About Me

Hi, I am Neel Karia, a PhD candidate in Industrial Engineering and Operations Research at Columbia University supported by the Presidential Fellowship and guided by Cliff Stein. I also collaborate with researchers from IBM Research.

Previously, I was a Research Fellow at Microsoft Research India. Before that, I was a Computer Science and Engineering undergrad at IIT Kharagpur from 2017 to 2021. I am enthusiastic about theoretical computer science and optimization, especially their applications to scheduling algorithms, algorithmic game theory, and machine learning. In the past, I have dabbled in natural language processing and information retrieval.

My LinkedIn Profile, CV, Google Scholar, and contact details are attached below.

Peer-reviewed publications

"Energy-Efficient Scheduling for AI/ML Workloads on Multi-Instance GPUs with Dynamic Repartitioning" - With E. Lipe et. al. - CCGRID 2025
"Compiling the Votes of a Subelectorate for Multi-Winner Voting Rules" - ADT 2024, with Jérôme Lang.
"FilteredDiskANN: Graph Algorithms for Approximate Nearest Neighbor Search with Filters" - WWW 2023, with S. Gollapudi, et. al.
"How Hard is Safe Bribery?" - Theoretical Computer Science 2023, with Faraaz Mallick and Palash Dey (The conference version previously appeared in AAMAS 2022).

Peer-reviewed short papers

"INDEPROP: Information-preserving De-Propagandization of News Articles" - AAAI 2022 (as a student abstract), with Aaryan Bhagat, Faraaz Mallick and Ayush Kaushal.
"Compilation Complexity of Multi-Winner Voting Rules" - AAAI 2021 (as a student abstract), with Jérôme Lang.

Workshop papers

"Leveraging Multi-Staged Language Models for Extracting Measurements, their Attributes and Relations" - SemEval@ACL/IJCNLP 2021, with Ayush Kaushal and Faraaz Mallick.

Working papers/Preprints

Pacing Equilibria with Sensitivity. With Christian Kroer and Jay Sethuraman
Multidimensional Fair Division. With Faraaz Mallick and Rohit Vaish

Service

Reviewer at AAAI 2026, NeurIPS 2025, ICALP 2024, SODA 2024, and ESA 2022

Teaching

Teaching Assistant for the Machine Learning for FE and OR course (IEOR E4525 at Columbia University), Fall 2023

Past Experience

From 2021-2022, I was a Research Fellow in the Algorithms group at Microsoft Research India.
I spent the summer of 2020 as a Summer Analyst in the Controllers Division of Goldman Sachs.
I worked as a Data Scientist at Equifax during the summer of 2019.
I was the only student from my batch and one of the fifteen engineering students from India to receive the Aditya Birla Scholarship from 2017 to 2021.
I represented India and won medals at International Olympiads in the fields of Astronomy, Astrophysics and Earth Sciences from 2014 to 2017.