I am a Visiting Assistant Professor of Computer Science and Engineering at New York University’s Tandon School of Engineering. Before, I was a postdoctoral researcher at HDSIUCSD, where I work with Barna Saha and Yusu Wang. I obtained my PhD in Computer Science under the supervision of Andrei Bulatov at SFU. I also completed my master’s degree in the Mathematics Department at SFU, working with Cedric Chauve and Ladislav Stacho. I obtained my BSc in Computer Science from the University of Tehran. In 2022, I interned as an AI Research Scientist at Meta, where I was supervised by Mani Malek and Ilya Mironov. I also completed an internship at NII - Tokyo, Japan, where I was supervised by Yuichi Yoshida.

Research Interest: I have a broad interest in theoretical computer science and algorithm design. In particular:

• Algorithms and Combinatorial Optimization
  • Constraint satisfaction problems (CSPs), submodular optimization, sparsification
• Responsible AI and Optimization
  • Differential privacy, federated learning, fairness
• Machine Learning and Learning Theory
  • Learning-enabled (combinatorial) optimizations

Teaching

• This semester I am teaching CS-GY 6923 Machine Learning at NYU Tandon.

• DSC 40B – Theoretical Foundations of Data Science II at HDSI.

  • Spring 2024, Fall 2023

Publications

(Unless stated otherwise, author names are in alphabetical order.)

Decomposable Submodular Maximization in Federated Setting.
Akbar Rafiey
International Conference on Machine Learning (ICML 2024)
arXiv

Inapproximability of H-Coloring Problems.
Kamyar Khodamoradi, Akbar Rafiey, Arash Rafiey
Comming Soon

Bi-arc Digraphs: Recognition Algorithm and Applications.
Pavol Hell, Akbar Rafiey, Arash Rafiey
Latin American Symposium on Theoretical Informatics (LATIN 2024)
Link

Private Boosted Decision Trees via Smooth Re-Weighting.
Vahid R. Asadi, Marco L. Carmosino, Mohammadmahdi Jahanara, Akbar Rafiey, Bahar Sala- matian.
Theory and Practice of Differential Privacy Workshop, International Conference on Machine Learning (ICML 2021)
Journal of Privacy and Confidentiality Vol. 13 No. 1 (2023)
(Link)

On the Complexity of CSP-based Ideal Membership Problems.
Andrei A. Bulatov, Akbar Rafiey.
ACM Symposium on Theory of Computing (STOC 2022)
Link

Sparsification of Decomposable Submodular Functions.
Akbar Rafiey, Yuichi Yoshida.
Association for the Advancement of Artificial Intelligence (AAAI 2022)
Link

The Ideal Membership Problem and Abelian Groups.
Andrei A. Bulatov, Akbar Rafiey.
Symposium on Theoretical Aspects of Computer Science (STACS 2022)
Link

Fast and Private Submodular and k-Submodular Functions Maximization with Matroid Constraints.
Akbar Rafiey, Yuichi Yoshida.
International Conference on Machine Learning (ICML 2020)
Link

Toward a Dichotomy for Approximation of H-coloring.
Akbar Rafiey, Arash Rafiey, Thiago Santos.
International Colloquium on Automata, Languages and Programming, (ICALP 2019)
Link

Approximation Algorithms for Generalized MST and TSP in Grid Clusters.
Binay K. Bhattacharya, Ante Custic, Akbar Rafiey, Arash Rafiey, Vladyslav Sokol.
Combinatorial Optimization and Applications (COCOA 2015)
Link

Miscellaneous

Bi-arc digraphs and conservative polymorphism.
Pavol Hell, Akbar Rafiey, Arash Rafiey.
Preprint, (ArXiv, 2020)

Counting Maximal Near Perfect Matchings in Quasirandom and Dense Graphs.
Yifan Jing, Akbar Rafiey.
Preprint, (ArXiv 2019)

MaxTiC: Fast Ranking Of A Phylogenetic Tree By Maximum Time Consistency With Lateral Gene Transfers.
Cedric Chauve, Akbar Rafiey, Adrian A. Davin, Celine Scornavacca, Philippe Veber, Bastien Boussau, Gergely Szollosi, Vincent Daubin, Eric Tannier Eric Tannier.
Preprint (bioRxiv, 2017)

Ordering with Precedence Constraints and Budget Minimization.
Akbar Rafiey, Jeff Kinne, Jan Manuch, Arash Rafiey.
Preprint, (ArXiv 2015)