Christian Ikeokwu

I’m a 2nd-year PhD student in the Theory Group and Berkeley AI Research (BAIR), fortunate to be advised by Christian Borgs and Jennifer Chayes.

I’m broadly interested in theoretical computer science, artificial intelligence and mathematical economics. Most recently, graph theory, algorithmic game theory, statistical learning and their various intersections.

I also think about how tools and techniques from TCS, AI and economic design can yield insights about important societal problems.

Before Berkeley, I graduated from Oberlin College with a BA in Mathematics and Computer Science, and I’m extremely grateful for the mentorship of Adam Eck and Sam Taggart during my undergraduate years.

news / upcoming

Jun 19, 2023	I have been selected to join the Berkeley AI Policy Hub this coming Fall!
May 2, 2023	I’m presenting at the Rising Stars in MS&E Workshop at Stanford, CA.
Jul 14, 2022	I was awarded a Hearts to Humanity Eternal (H2H8) graduate research grant for my work in graph theory and AI.

selected publications

AAAI
An Algorithmic Introduction to Savings Circles

Rediet Abebe, Adam Eck, Christian Ikeokwu, and Samuel Taggart

In Proceedings of the AAAI Conference on Artificial Intelligence, 2022

Abs arXiv Bib PDF

Rotating savings and credit associations (roscas) are informal financial organizations common in settings where communities have reduced access to formal financial institutions. In a rosca, a fixed group of participants regularly contribute sums of money to a pot. This pot is then allocated periodically using lottery, aftermarket, or auction mechanisms. Roscas are empirically well-studied in economics. They are, however, challenging to study theoretically due to their dynamic nature. Typical economic analyses of roscas stop at coarse ordinal welfare comparisons to other credit allocation mechanisms, leaving much of roscas’ ubiquity unexplained. In this work, we take an algorithmic perspective on the study of roscas. Building on techniques from the price of anarchy literature, we present worst-case welfare approximation guarantees. We further experimentally compare the welfare of outcomes as key features of the environment vary. These cardinal welfare analyses further rationalize the prevalence of roscas. We conclude by discussing several other promising avenues
@inproceedings{aeit22, title = {An Algorithmic Introduction to Savings Circles}, author = {Abebe, Rediet and Eck, Adam and Ikeokwu, Christian and Taggart, Samuel}, booktitle = {Proceedings of the AAAI Conference on Artificial Intelligence}, volume = {36}, number = {5}, pages = {4744--4751}, year = {2022}, }