Education

Sharif University of Technology logo

B.Sc. in Mathematics

B.Sc. in Electrical Engineering

2010 - 2015

Princeton University logo

M.A. in Electrical and Computer Engineering

2015 - 2017

Ph.D. in Electrical and Computer Engineering

2017 - 2021

Awards and Honors

  • Leverhulme Early Career Fellowship, the Leverhulme Trust and the Isaac Newton Trust (2023-present)
  • Teaching Assistant Award, Department of Electrical and Computer Engineering, Princeton University (2019)
  • Anthony Ephremides Fellowship, Princeton University (2016)
  • Bronze Medal, Iranian Mathematical Olympiad (2009)
  • Diploma of Mathematics, Tournament of Towns Contest, Russian Academy of Sciences (2009)
  • Member of the Iranian National Elite Foundation (2009-present)

Publications

  • A. R. Asadi. (2025) Hierarchical Maximum Entropy via the Renormalization Group. (Submitted)
  • G. Aminian, A. R. Asadi, I. Shenfeld & Y. Mroueh. (2025) Theoretical Analysis of KL-regularized RLHF with Multiple Reference Models. arXiv preprint arXiv:2502.01203 (Submitted) [Link]
  • G. Aminian, I. Shenfeld, A. R. Asadi, A. Beirami & Y. Mroueh. (2025) Best-of-N through the Smoothing Lens: KL Divergence and Regret Analysis. Efficient Systems for Foundation Models Workshop at the International Conference on Machine Learning (ICML) 2025.
  • G. Aminian, A. R. Asadi, T. Li, A. Beirami, G. Reinert & S. N. Cohen. (2025) Generalization and Robustness of the Tilted Empirical Risk. International Conference on Machine Learning 2025. [Link]
  • A. Pensia, A. R. Asadi, V. Jog & P.-L. Loh. (2024) Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints. IEEE Transactions on Information Theory
  • A. R. Asadi. (2024) An Entropy-Based Model for Hierarchical Learning. Journal of Machine Learning Research, 25(187), pp. 1−45. [Link]
  • A. R. Asadi & P.-L. Loh. (2024) Entropic Regularization of Neural Networks: Self-Similar Approximations. Journal of Statistical Planning and Inference, 233, p.106181
  • A. R. Asadi & P.-L. Loh. (2023) On the Gibbs Exponential Mechanism and Private Data Generation. IEEE International Symposium on Information Theory (ISIT)
  • A. Pensia, A. R. Asadi, V. Jog & P.-L. Loh. (2023) Simple Binary Hypothesis Testing under Local Differential Privacy and Communication Constraints. 2023 Conference on Learning Theory (COLT). [Link]
  • A. R. Asadi & E. Abbe. (2020) Maximum Multiscale Entropy and Neural Network Regularization. arXiv preprint arXiv:2006.14614. [Link]
  • A. R. Asadi & E. Abbe. (2020) Chaining Meets Chain Rule: Multilevel Entropic Regularization and Training of Neural Networks. Journal of Machine Learning Research, 21(139), pp. 1-32. [Link]
  • A. R. Asadi, E. Abbe, & S. Verdú. (2018) Chaining Mutual Information and Tightening Generalization Bounds. Advances in Neural Information Processing Systems (NeurIPS), pp. 7245-7254. [Link]
  • A. R. Asadi, E. Abbe, & S. Verdú. (2017) Compressing Data on Graphs with Clusters. IEEE International Symposium on Information Theory (ISIT) pp. 1583-1587. [Link]
  • Majid Asadi, A. R. Asadi. (2014) On the Failure Probability of Used Coherent Systems. Communications in Statistics, Theory and Methods, Vol. 43, pp. 2468-2475. [Link]
  • A. R. Asadi. (2013) Problem 96.J with solution. The Mathematical Gazette, Vol. 97, No. 539, pp. 345-346, United Kingdom. [Link]

Ph.D. Dissertation

  • A. R. Asadi (2021) Neural Network Learning: A Multiscale-Entropy and Self-Similarity Approach. (Princeton University)

Talks

  • UK Crypto Day, University of Sheffield, Sheffield, United Kingdom. June 2025
  • Chennai Mathematical Institute, Chennai, India. January 2025
  • Department of Mathematical Sciences, Durham University, UK. May 2023
  • Department of Mathematics and Statistics, Lancaster University, UK. February 2023
  • Statistical Laboratory, University of Cambridge, UK. February 2023
  • Department of Computer Science, ETH Zürich, Switzerland. February 2021
  • NSF-Simons Collaboration on the Theoretical Foundations of Deep Learning. December 2020
  • Department of EECS, Massachusetts Institute of Technology, USA. December 2020
  • Center for Data Science, New York University, USA. June 2020
  • Laboratoire de Physique, École Normale Supérieure, France. May 2020
  • Department of Statistical Sciences, University of Toronto, Canada. April 2020
  • Department of Engineering, University of Cambridge, UK. March 2020
  • Institute for Advanced Study, Princeton, USA. October 2019 [YouTube Link]
  • Microsoft Research AI, Redmond, USA. September 2019

Workshop Organization

Personal

I enjoy staying active through exercise and watching sports, with a particular passion for football, Formula 1, and tennis. I also take pleasure in reading poetry, particularly works by Saadi and Hafez.