Akshit Kumar

I am a final year PhD student in the Decision, Risk and Operations division at Columbia Business School, where I am fortunate to be advised by Prof. Omar Besbes and Prof. Yash Kanoria. I am broadly interested in the operations of online platforms and marketplaces. In particular, I develop models and methods to optimize the operations of these platforms, with applications in order fulfillment, revenue management, matching markets and recommendation systems. In Summer of 2023, I had the opportunity of interning in the supply chain optimization group at Amazon where I worked on multi-objective optimization for order fulfillment problems. Prior to Columbia, I completed my Masters in Electrical Engineering from University of Michigan and before that I graduated with a B.Tech (Hons.) in Electrical Engineering from Indian Institute of Technology, Madras.

I am on the 2024-25 academic job market. Here is my CV.

News

Journal Publications

Dynamic Resource Allocation: Algorithmic Design Principles and Spectrum of Achievable Performances
Omar Besbes, Yash Kanoria, Akshit Kumar
Forthcoming in Operations Research
Second Place, 2024 Michael H. Rothkopf Junior Research Paper Prize
Finalist, 2023 INFORMS George Nicholson Student Paper Competition
Finalist, 2023 Jeff McGill RMP Best Student Paper Prize
An earlier version of this paper appeared as an extended abstract in the Proceedings of the 23rd ACM Conference on Economics and Computation, EC'22 with the title The Multi-secretary Problem with Many Types
arXiv|slides| poster | flash talk| EC talk

Working Papers

Feature-Based Dynamic Matching
Yilun Chen, Yash Kanoria, Akshit Kumar, Wenxin Zhang
Major Revision in Operations Research
First Place, 2024 Jeff McGill RMP Best Student Paper Prize
EC 2023 | ACM Conference on Economics and Computation
ssrn| slides|poster|nick arnosti's blog post

The Fault in Our Recommendations: On the Perils of Optimizing the Measurable
Omar Besbes, Yash Kanoria, Akshit Kumar
Journal version under preparation
RecSys 2024 | ACM Conference on Recommender Systems
arXiv|slides|yash kanoria's blog post|ai generated podcast summary

The Impact of Rankings and Personalized Recommendations in Marketplaces
Omar Besbes, Yash Kanoria, Akshit Kumar
Under preparation

Conference Proceedings

Breaking the Unit Throughput Barrier in Random Access Protocol Based Distributed Systems
Akshit Kumar, Parikshit Hegde, Rahul Vaze, Amira Alloum, Cédric Adjih
NCC 2023 | National Conference on Communications
ieee| arXiv

Low-cost aerial imaging for small holder farmers
Aditya Jain, Zerina Kapetanovic, Akshit Kumar, Vasuki Narasimha Swamy, Rohit Patil, Deepak Vasisht, Rahul Sharma, Manohar Swaminathan, Ranveer Chandra, Anirudh Badam, Gireeja Ranade, Sudipta Sinha, Akshay Uttama Nambi SN
COMPASS'19 | ACM SIGCAS Conference on Computing and Sustainable Societies
Best Paper Award

Speed scaling under QoS constraints with finite buffer
Parikshit Hegde, Akshit Kumar, Rahul Vaze
WiOpt'18 | International Symposium on Modeling and Optimization in Mobile, Ad hoc, and Wireless Networks

IIT Madras
2014 - 2018
Microsoft Research India
Summer 2016
STCS, TIFR
Summer 2017
Nokia Bell Labs
Summer 2018
University of Michigan
2018 - 2020
Columbia University
2020 - Present
Amazon
Summer 2023