Notable Awards & Grants
- GRAPH4HEALTH — ANR Project (2023)
- Google Faculty Research Award (2019/20)
- LMS Schemes 1 & 4 (2018 & 19)
- Adobe Research Award (2018)
- E.M. Gold Best Paper Award, ALT 2013
Selected Publications & Preprints
- A. Khaleghi, On Restless Linear Bandits, IEEE Transactions on Information Theory, vol. 71, no. 4, pp. 2982-2990, 2025. [pdf]
- S. Grunewälder, A. Khaleghi, Estimating the Mixing Coefficients of Geometrically Ergodic Markov Processes, 2024.
- G. Blower, A. Khaleghi, M. Kuchemann-Scales, Hasimoto frames and the Gibbs measure of periodic nonlinear Schrödinger Equation, Journal of Mathematical Physics, vol. 65, issue 2, 2024. [pdf]
- A. Khaleghi, G. Lugosi, Inferring the mixing properties of an ergodic process, IEEE Transactions on Information Theory, vol. 69, no. 6, pp. 4014-4026, 2023. [pdf]
- S. Grunewälder, A. Khaleghi, Oblivious Data for Fairness with Kernels, Journal of Machine Learning Research, (208): 1-36, 2021. [code]
- A. Khaleghi, D. Ryabko, Clustering piecewise stationary processes, In Proceedings of the IEEE International Symposium on Information Theory, 2020. [pdf]
- S. Grunewälder, A. Khaleghi, Approximations of the Restless Bandit Problem, Journal of Machine Learning Research, 20:1-37, 2019. [pdf]
- A. Khaleghi, D. Ryabko, J. Mary, P. Preux, Consistent Algorithms for Clustering Time Series, Journal of Machine Learning Research, 17(3):1-32, 2016. [pdf]
- A. Khaleghi, D. Ryabko, Nonparametric Multiple Change Point Estimation in Highly Dependent Time Series, Theoretical Computer Science, 620:119-133, 2016. [pdf]
- - A shorter version of this article received the E.M. Gold best paper Award at the 24th International Conference on Algorithmic Learning Theory.
- A. Khaleghi, D. Ryabko, Asymptotically Consistent Estimation of the Number of Change Points in Highly Dependent Time Series, In Proceedings of the International Conference on Machine Learning, 2014. [pdf][code]
- A. Khaleghi, D. Ryabko, Locating Changes in Highly-Dependent Data with an Unknown Number of Change-Points, In Proceedings of Neural Information Processing Systems, 2012. [pdf] [poster][code]
- A. Khaleghi, D. Ryabko, J. Mary, P. Preux, Online Clustering of Processes, In Proceedings of Artificial Intelligence & Statistics, 2012. [pdf] [poster]
- A. Khaleghi, D. Silva, F. R. Kschischang, Subspace Codes, Lecture Notes in Computer Science, 2009. [pdf]
- A. Khaleghi, F. R. Kschischang, Projective Space Codes for the Injection Metric, In Proceedings of the Canadian Workshop on Information Theory 2009. [poster]
Dissertations
- PhD: On Some Unsupervised Learning Problems for Highly Dependent Time Series, INRIA Lille / Univ. Lille I, 2013. [pdf]
- MSc: Projective Space Codes for the Injection Metric, Univ. of Toronto, 2009. [pdf]
Former PhD Students
- Moe Kuchemann-Scales (2020 - 2025) co-supervised with Gordon Blower Mathematics and Statistics, Lancaster University
