Aidin Niaparast

PhD Candidate in Algorithms, Combinatorics, and Optimization (ACO)

Tepper School of Business

Carnegie Mellon University

📧 aniapara@andrew.cmu.edu 🎓 Google Scholar 💻 GitHub 🔗 LinkedIn

Hi! I am a fifth-year Ph.D. candidate in the interdisciplinary Algorithms, Combinatorics, and Optimization (ACO) doctoral program at the Tepper School of Business, Carnegie Mellon University. I am fortunate to be advised by Prof. R. Ravi and Prof. Benjamin Moseley. My work centers on optimization under uncertainty, focusing on online and learning-augmented algorithms.

News I am on the job market in 2025–26 — please reach out if you think my work would be a good fit!

Honors and Awards

Tepper School of Business Presidential Fellowship, Carnegie Mellon University (2024–2025)
Neural Information Processing Systems Spotlight Paper (top 3% of accepted papers, 2023)
William Larimer Mellon Fellowship, Carnegie Mellon University (2022–2026)
Ranked 1st in the National University Entrance Exam in Iran for M.Sc. in Computer Science (2021)
Silver Medal in Iranian National Olympiad in Informatics (2015)

Publications

Incremental Approximate Single-Source Shortest Paths with Predictions

Samuel McCauley, Benjamin Moseley, Aidin Niaparast, Helia Niaparast, Shikha Singh

International Colloquium on Automata, Languages, and Programming (ICALP), Link
Putting Off the Catching Up: Online Joint Replenishment Problem with Holding and Backlog Costs

Benjamin Moseley, Aidin Niaparast, R. Ravi

ACM-SIAM Symposium on Discrete Algorithms (SODA), Link
Binary Search with Distributional Predictions

Michael Dinitz, Sungjin Im, Thomas Lavastida, Benjamin Moseley, Aidin Niaparast, Sergei Vassilvitskii

Neural Information Processing Systems (NeurIPS), Link
Incremental Topological Ordering and Cycle Detection with Predictions

Samuel McCauley, Benjamin Moseley, Aidin Niaparast, Shikha Singh

International Conference on Machine Learning (ICML), Link
Online List Labeling with Predictions

Samuel McCauley, Benjamin Moseley, Aidin Niaparast, Shikha Singh

Neural Information Processing Systems (NeurIPS), Link
Spotlight; top 3% of accepted papers
Timeliness Through Telephones: Approximating Information Freshness in Vector Clock Models

Da Qi Chen, Lin An, Aidin Niaparast, R. Ravi, Oleksandr Rudenko

ACM-SIAM Symposium on Discrete Algorithms (SODA), Link
On a Question of Haemers Regarding Vectors in the Nullspace of Seidel Matrices

Saieed Akbari, Sebastian M. Cioabă, Samira Goudarzi, Aidin Niaparast, Artin Tajdini

Linear Algebra and Its Applications, Link

Teaching

Carnegie Mellon University

Instructor: Optimization for Business (Summer 2024)
Teaching Assistant:
- Machine Learning Fundamentals (Spring 2024)
- Optimization for Business (Spring 2023, Fall 2023, Fall 2024)
- End-to-End Business Analytics (Fall 2023, Fall 2024, Fall 2025)

Sharif University of Technology

Teaching Assistant:
- Combinatorial Optimization (Fall 2020)
- Data Structures (Fall 2020)
- Information Theory and Coding (Fall 2020)
- Combinatorics and its Applications (Spring 2020)
- Discrete Structures (Spring 2020)
- Analysis of Algorithms (Spring 2019)

Olympiad Teaching

Delivered 1000+ hours of instruction in Algorithms, C++, Combinatorics, and Graph Theory to high-school students preparing for the Iranian National Olympiad in Informatics, the gateway to the International Olympiad in Informatics (IOI).