Aditya Petety

Bio

I am a fifth-year Ph.D. candidate (Aug 2021 – present) in the Department of Computer Science and Engineering at UC Santa Cruz, advised by Prof. Sungjin Im.

Research Interests

I work on combining machine-learned models with theoretical algorithms to improve real-world performance while maintaining worst-case guarantees. I am also interested in other frameworks for beyond worst-case analysis, such as resource augmentation and random-order arrival models.

News

• June 2026Started as a PhD Software Engineering Intern at Google
• Jan 2025Presented our paper on online scheduling via gradient descent at SODA '25.
• Jun 2024Our SPAA '24 paper on load and graph balancing received the Outstanding Paper Award.

Publications

1. SODA '25
   Online Scheduling via Gradient Descent for Weighted Flow Time Minimization with Qingyun Chen and Sungjin Im

   The 36th ACM-SIAM Symposium on Discrete Algorithms
2. SPAA '24
   Online Load and Graph Balancing for Random Order Inputs with Sungjin Im, Ravi Kumar, Shi Li, and Manish Purohit

   Outstanding Paper Award
3. ICML '22
   Parsimonious Learning-Augmented Caching with Sungjin Im, Ravi Kumar, and Manish Purohit
4. SOFSEM '21
   Parameterized Complexity of d-Hitting Set with Quotas with Sushmita Gupta and Sagar Singh
5. AAAI '20
   Attribute Noise Robust Binary Classification with Sandhya Tripathi and N Hemachandra

Professional Service

Reviewer: SPAA 2024, STOC 2024, ITCS 2024, SODA 2023, APPROX 2022