Computer Science Department
University of Southern California
I’m Sid, a CS PhD student in the USC Theory Group, where I am fortunate to be advised by the wonderful Vatsal Sharan and Aleksandra Korolova. I am broadly interested in (1) algorithmic fairness, especially in the presence of uncertainty, finite resources, and ranking / two-sided marketplaces; and (2) theoretical machine learning. I am grateful to have my research supported by a National Defense Science and Engineering Graduate (NDSEG) Fellowship.
Here is my CV (Nov. 2023).
I completed my undergraduate degrees in math and CS at The University of Texas at Dallas (UTD), where I explored research in networking, theory, optimization, and reinforcement learning. Along the way, I was extremely fortunate to be advised by these amazing professors: Nick Ruozzi, Jason Jue, Brendan Juba, and Ben Raichel.
Regularization and Optimal Multiclass Learning
(αβ) Julian Asilis,
Siddartha Devic,
Shaddin Dughmi,
Vatsal Sharan,
Shang-Hua Teng
Preprint.
[arxiv]
Fairness in Matching under Uncertainty
Siddartha Devic,
David Kempe,
Vatsal Sharan,
Aleksandra Korolova
ICML 2023
Non-archival at ACM conference on Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 23)
[arxiv] [poster] [twitter thread] [video]
Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions
(αβ) Zihao Deng,
Siddartha Devic,
Brendan Juba
AISTATS 2022
Also appeared at Neurips 2021 Workshop on Ecological Theory of Reinforcement Learning
[arxiv]
Dynamic Bandwidth Allocation for PON Slicing with Performance-Guaranteed Online Convex Optimization
Genya Ishigaki, Siddartha Devic, Riti Gour, Jason P. Jue
IEEE GLOBECOM 2021
[arxiv] [poster]
Failout: Achieving Failure-Resilient Inference in Distributed Neural Networks
Ashkan Yousefpour,
Brian Q Nguyen,
Siddartha Devic,
Guanhua Wang,
Aboudy Kreidieh,
Hans Lobel,
Alexandre M Bayen,
Jason P. Jue
ICML 2020 Workshop on Federated Learning for User Privacy and Data Confidentiality
[arxiv]
DeepPR: Progressive Recovery for Interdependent VNFs with Deep Reinforcement Learning
Genya Ishigaki, Siddartha Devic, Riti Gour, Jason P. Jue
IEEE Journal on Selected Areas in Communications, 2020
Also appeared at IEEE GLOBECOM 2019
[arxiv]
The first year of my PhD, I served as a CS department senator within the USC Viterbi Graduate Student Association (VGSA), where I was able to bring goats to campus (amongst other things).
I served as President / VP for my undergrad’s ACM chapter, where I am most proud to have established a perpetual $30k endowed scholarship with club funds. Importantly, the scholarship may also grant eligible students an in-state tuition waiver! Students can apply here.
I also served as the undergrad representative on the UTD CS department head search committee during the 2020-2021 academic year.
If you are a UTD student interested in pursuing a PhD, you may find the grad school section I wrote of this guide helpful. Also check out this research internship / REU masterlist which I put together. You are welcome to reach out to me anytime for more info and/or if you’d like me to review your GRFP or NDSEG applications!
In my free time, I enjoy learning art, running, climbing/bouldering and hiking, calisthenics progressions, playing classical piano, swimming, skiing (when I can!), and binging npr tiny desk concerts.
Some other stuff from undergrad:
Give, even if you only have a little.
-Siddhartha Gautama