Krishna Acharya

About Me

I'm a Ph.D. Candidate in Machine Learning at Georgia Tech, advised by Prof. Juba Ziani. Before Georgia Tech, I completed my M.S. and B.S in Computer Science at ENS de Lyon and BITS-Pilani Goa.

I'm passionate about Trustworthy ML: algorithms that preserve privacy, are fair to subpopulations and make good sequential decisions. My research is in Differential privacy(DP), Fairness and Recommender systems.

I have industry experience as an Applied Science intern with Amazon in the Personalized recommendations team, and as a Machine learning intern at Keysight in the AI explainability team.

In my free time, I enjoy hiking, climbing 🧗 and board games.

Recent News

• July 2024: Started my Applied science internship with Amazon in the personalized recommendations team.
• May 2024: Our work on One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits is accepted to UAI 2024.
• April 2024: Successfully proposed my Ph.D thesis!
• March 2024: Our paper on Personalized Differential Privacy for Ridge Regression is accepted to the ICLR 2024 workshop on Privacy regulation and protection.
• Jan 2024: Our work on Oracle Efficient Efficient Algorithms for Groupwise Regret is accepted to ICLR 2024.

Publications

Preprints

1. Personalized Differential Privacy for Ridge Regression
   Krishna Acharya, Franziska Boenisch, Rakshit Naidu, Juba Ziani
   Privacy Regulation and Protection workshop at ICLR 2024


2. Producers Equilibria and Dynamics in Engagement-Driven Recommender Systems
   Krishna Acharya, Varun Vangala, Jingyan Wang, Juba Ziani
   

Conference Articles

1. One Shot Inverse Reinforcement Learning for Stochastic Linear Bandits
   Etash Kumar Guha, Jim Thannikary James, Krishna Acharya, Vidya Muthukumar, Ashwin Pananjady
   UAI 2024
2. Oracle Efficient Algorithms for Groupwise Regret
   Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani
   ICLR 2024
3. Wealth Dynamics Over Generations: Analysis and Interventions
   Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani
   SaTML 2023
4. Analysis of QoE for Adaptive Video Streaming over Wireless Networks with User Abandonment Behavior.
   Rachid El-Azouzi, Krishna Acharya, Sudheer Poojary, Albert Sunny, Majed Haddad, Eitan Altman, Dimitrios Tsilimantos, Stefan Valentin
   WCNC 2019

Theses

1. Online Learning Algorithms for Fair Ad Auctions
   Krishna Acharya
   Master Thesis, École Normale Supérieure de Lyon

Manuscripts

1. Approximation of Banzhaf indices and its application to voting games
   Krishna Acharya, Himadri Mukherjee, Jajati Keshari Sahoo
   

Internships

1. Applied Science Intern, Amazon, Personalized recommenders (2024)
2. Machine Learning Intern, Keysight, AI Explainability (2023)
3. Research Intern, Laboratoire d’informatique de Grenoble (2020)
4. Research Intern, Laboratoire informatique d’Avignon (2018)

Teaching

1. TA, ISyE 4803 : Online Learning and Decision Making (Spring 2024)
2. TA, ISyE 2027 : Probability with Applications (Spring 2022)
3. TA, ISyE 3133 : Engineering Optimization (Fall 2021)

Academic Service

Reviewer: AAAI, ICLR, KDD, NeurIPS

Awards

1. Kiplinger Fellowship (Fall 2021, Spring 2022)
2. University of Lyon Scholarship of Excellence (Fall 2019, Spring 2020)
3. Merit Scholar - BITS Pilani (2015, 2016)