Starting in the fall, I will be a graduate student at UT Austin in the MSCS program. My interests lie broadly in the intersection of math and computer science, especially in discrete/combinatorial optimization and the design of approximation algorithms.
Previously, I spent a year as a research intern in the Data Sciences and Machine Intelligence group at the Pacific Northwest National Laboratory where I worked on developing fast algorithms for generalized matching problems. Before that, I graduated from the New Jersey Institute of Technology with a B.Sc. in Computer Science and Mathematical Sciences where I worked with Dr. Baruch Schieber on scheduling problems.
sbharg [at] utexas [dot] edu
[M1]
Streaming Algorithms for Weighted $k$-Disjoint Matchings
S M Ferdous, Bhargav Samineni, Alex Pothen, Mahantesh Halappanavar, Bala Krishnamoorthy
In Submission
[W2]
Appproximate Bipartite $b$-Matching using Multiplicative Auction
Bhargav Samineni, S M Ferdous, Mahantesh Halappanavar, Bala Krishnamoorthy
2024 Informs Optimization Society Conference
[W1]
Using Physics-Informed Regularization to Improve Extrapolation Capabilities of Neural Networks
David Davini, Bhargav Samineni, Benjamin Thomas, Amelia Tran, Cherlin Zhu, Kyung Ha, Ganesh Dasika, Laurent White
4th Workshop on Machine Learning and the Physical Sciences, NeurIPS (ML4PS 2021)