About Me

I am a final-year Ph.D. candidate in Computer Science at UT Austin. I am fortunate to be advised by Prof. Shuchi Chawla. Before that, I studied Electrical and Computer Engineering at the National Technical University of Athens, where I worked with Prof. Dimitris Fotakis. Prior to starting my PhD, I completed two research internships at the LIP6 Institute at Sorbonne University. I am affiliated with the LDOS program.

My research focuses on algorithms for sequential decision-making under uncertainty, particularly on how algorithms can effectively exploit predictions, stochastic structure, and costly information. Much of my work lies at the intersection of theoretical computer science, economics, and operations research, and includes learning-augmented algorithms, stochastic optimization, and models of costly information acquisition such as Pandora’s Box.

You can reach me at christou@cs.utexas.edu and can find the latest version of my CV here (last updated: October 2026). Starting in Fall 2026, I will be on the postdoc market!

News

[October 2027] Our latest work on Stochastic Weighted Caching with Per-Request Predictions is now posted on ArXiv. We show that weighted paging admits a constant competitive ratio when requests are drawn from a fixed (arbitrary) distribution and the algorithm is supplied with perfect next-arrival predictions. Previous work establishes that none of these conditions suffice alone.

[September 2026] Our recent work on Online Batching with Lookahead got accepted in SIGMETRICS 2027! It will be made available on ArXiv very soon!

[July 2026] I am co-organizing a tutorial on Costly Information Models for Online Selection at EC in Rome together with Robin Bowers. I will also be presenting a poster on Pricing Pandora's Boxes at the Foundations of Data Economics workshop.

[June 2026] I successfully completed my Thesis Proposal Exam and will be advancing to candidacy!

[January 2026] I will be attending SODA in Vancouver to present our work on Combinatorial Selection with Costly Information.

[December 2025] I will be attending WINE at Rutgers to present our recent work on Commitment Gap via Correlation Gap.

[December 2025] I will be visiting UMass to give a talk on Costly Information Models at the Computer Science Theory Seminar.

[October 2025] I will be presenting a poster on Costly Information Models at the Young Researchers Workshop in Cornell.

[June 2025] I will be giving an invited talk about the role of the Gittins index in sequential decision-making at the 2025 INFORMS APS (Applied Probability Society) Conference in Atlanta, Georgia.

[May 2025] I will be serving as the head TA and teaching Linear Algebra and Discrete Mathematics to high-school students at the FinDS summer-school program organized by EnCORE.

Conference Publications

• Online Batching with Lookahead: Adversarial Limits and Stochastic Gains | SIGMETRICS 2027

With: Jiayi Chen, Nihal Sharma, Aditya Akella, Shuchi Chawla, Sanjay Shakkottai

• Combinatorial Selection with Costly Information | SODA 2026

With: Shuchi Chawla, Amit Harlev, Ziv Scully

• Commitment Gap via Correlation Gap | WINE 2025

With: Shuchi Chawla, Trung Dang

• A Multi-Dimensional OCRS for Revenue Maximization | SODA 2025

With: Shuchi Chawla, Trung Dang, Zhiyi Huang, Gregory Kehne, Rojin Rezvan

• Online Time-Windows TSP with Predictions | Approx 2024

With: Shuchi Chawla

• Efficient Online Clustering with Moving Costs | NeurIPS 2023

With: Stratis Skoulakis, Volkan Cevher

• Memoryless Algorithms for the Generalized k-server Problem on Uniform Metrics  | WAOA 2020

With: Dimitris Fotakis, Grigoris Koumoutsos

Journal Publications

• A Simple Rounding Scheme for Multistage Optimization | Published at TCS

With: Evripids Bampis, Bruno Escoffier, Alexander Kononov, Nguyen Kim Thang

• Online Learning for Min-Max Discrete Problems | Published at TCS

With: Evripids Bampis, Bruno Escoffier, Nguyen Kim Thang

Preprints

• Pricing Pandora's Boxes: Revenue Maximization in Sequential Information Acquisition  

With: Shuchi Chawla, Trung Dang, Zhiyi Huang

• Stochastic Weighted Caching with Per-Request Predictions

With: Shuchi Chawla 

Teaching

In Fall 2025, I was a co-instructor for the graduate course Approximation Algorithms and Complexity at UT Austin, taught by Prof. Shuchi Chawla. In Summer 2025, I served as a co-organizer, co-instructor, and head TA for the FinDS summer program for high school students, led by Prof. Rajiv Gandhi and organized by EnCORE. I have also served as a TA for several undergraduate courses (Algorithms and Complexity, Discrete Mathematics, Principles of Machine Learning) and the graduate course Data-Driven Algorithmic Design.