Krishna Acharya

About Me

I'm a Ph.D. Candidate in Machine Learning at Georgia Tech, where I'm fortunate to be 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 Sequential Decision Making. I'm also excited about DP finetuning for LLMs, generation of private synthetic data, and robust recommender systems.

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

Recent News

• 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.
• Aug 2023: Completed my internship at Keysight, integrated calibration and conformal prediction functionality to their AI testing toolkit.
• May 2023: Passed my Ph.D. qualifying exam!

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. Oracle Efficient Algorithms for Groupwise Regret
   Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani
   ICLR 2024
2. Wealth Dynamics Over Generations: Analysis and Interventions
   Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani
   SaTML 2023
3. 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

Workshop Articles

1. Oracle Efficient Algorithms for Groupwise Regret
   Krishna Acharya, Eshwar Ram Arunachaleswaran, Sampath Kannan, Aaron Roth, Juba Ziani
   Optimization for Machine Learning(OPT) workshop at NeurIPS 2023 .

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. Machine Learning Intern, Keysight Technologies (Summer 2023)
2. Research Intern, Laboratoire d’informatique de Grenoble (Spring 2020)
3. Research Intern, Laboratoire informatique d’Avignon (Fall 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

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)