I'm Peter. I'm a researcher at NVIDIA.

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About Me

Who Am I?

Hello! I'm Peter Xenopoulos.

I'm a research scientist at NVIDIA where I study applications of artificial intelligence and machine learning in esports. To put it succinctly, I investigate how to use data and machine learning to better understand human performance in competitive environments. You can see my profile on NVIDIA Research for more.



Adversarial environments are fun! It is exciting to understand human performance in fields like esports and sports, which involve skill mastery, communication and training. The data we produce in these environments lends itself to other computer science domains nicely, as well.
It's important to work on projects you enjoy. I started a few projects as a student that not only improved my coding ability but also brought me in contact with people who were nice enough to help me along the way. Find what you like and work on that -- it will come much easier.
Find a recent paper of mine, and you'll see an email. Otherwise, join the Awpy Discord.


Research Areas



[ PDF] ggViz: Accelerating Large-Scale Esports Game Analysis

CHI PLAY (2022). Xenopoulos, P., Rulff, J., & Silva, C.

[ PDF] ESTA: An Esports Trajectory and Action Dataset

arXiv preprint (2022). Xenopoulos, P., & Silva, C.

[ PDF] Analyzing the Differences between Professional and Amateur Esports through Win Probability

WWW (2022). Xenopoulos, P., Freeman, W. R., & Silva, C.

[ PDF] Optimal Team Economic Decisions in Counter-Strike

AI for Sports Analytics Workshop (IJCAI, 2021). Xenopoulos, P., Coelho, B., & Silva, C.

[ PDF] Bandit Modeling of Map Selection in Counter-Strike: Global Offensive

AI for Sports Analytics Workshop (IJCAI, 2021). Petri, G., Stanley, M. H., Hon, A. B., Dong, A., Xenopoulos, P., & Silva, C.

[ PDF] Valuing Player Actions in Counter-Strike: Global Offensive

Big Data (2020). Xenopoulos, P., Doraiswamy, H., & Silva, C.

[ PDF] Gale: Globally Assessing Local Explanations

PMLR (2022). Xenopoulos, P., Chan, G., Doraiswamy, H., Nonato, L. G., Barr, B., & Silva, C.
 Spotlight Talk

[ PDF] Calibrate: Interactive Analysis of Probabilistic Model Output.

TVCG (2022). Xenopoulos, P., Rulff, J., Nonato, L. G., Barr, B., & Silva, C.

[ PDF] Graph Neural Networks to Predict Sports Outcomes

Big Data (2021). Xenopoulos, P., & Silva, C.

[ PDF] Market Interventions in a Large-Scale Virtual Economy

arXiv preprint (2022). Hogan-Hennessy, S., Xenopoulos, P., & Silva, C. (2022).