Nouri Sakr


Assistant Professor of Data Science and Operations Research
Department of Computer Science and Engineering


Brief Biography

Nouri Sakr is an assistant professor of data science and operations research at the computer science and engineering department. She is also a member of the advisory board for the newly launched data science undergraduate program at The American University in Cairo (AUC).

Sakr received her PhD from Columbia University where she worked on data-driven combinatorial optimization and efficient machine learning frameworks under the supervision of Cliff Stein. As an undergraduate at AUC, she double majored in computer science and actuarial science with a minor in economics, then spent eight months at the University of Waterloo to complete a Master's of Mathematics in actuarial science where her main research focus was on FinTech.

Her research focuses on leveraging connections between data science and combinatorial optimization to design data-driven algorithms that efficiently tackle real-world optimization challenges with social impact. At Amazon and Microsoft, she worked on supply chain analytics, dynamic inventory allocation and cloud storage traffic problems. During her PhD, she was an affiliate of the Data Science Institute, where she accumulated further experience on building fast machine learning frameworks and adaptive machine learning in cybersecurity through her collaborations with Google Brain and Sandia National Labs. She also built healthcare solutions for Columbia Medical Center and collaborated with Graham Windham in NYC to look into improving foster care matchings. In Egypt, she advises multiple startups and multinational organizations on their data science work and aims to involve as many students as possible in research and industrial collaborations that can help them expand their exposure and knowledge horizon.

As a huge supporter to interdisciplinarity, Sakr founded the Data Science Hub (DSH) as a collaboration platform for academics and industry professionals as well as research scholars from Egypt and abroad. The projects at the DSH apply data science techniques in interdisciplinary areas, such as in education, healthcare, fintech, system scheduling, psychology and economics. Recently, interns at the DSH have been involved in research related to education under the pandemic, reinforcement learning and more recently an exciting new project related to GDP with the Central Bank of Egypt as well as research work using GANs for oil and gas problems with RAISA Energy.

    • PhD in Industrial Engineering and Operations Research, Columbia University, USA
    • Farid, K. and Sakr, N. (2021) “Few-Shot System Identification for Reinforcement Learning” IEEE Asia-Pacific Conference on Intelligent Robot Systems (ACIRS 2021)
    • Sundin, L., Sakr, N., Leinonen, J., Aly, S. and Cutts, Q. (2021) “Visual recipes for slicing and dicing data: Teaching data wrangling using subgoal graphics.” Proceedings of the 21st Koli Calling International Conference on Computing Education Research (Koli Calling '21). ACM
    • Bojarski,M., Choromanska, A., Choromanski, K., Fagan,F., Gouy-Pailler, C., Morvan, A., Sarlos, T., Sakr, N. and Atif, J. (2017) “Structured Adaptive and Random Spinners for Fast Machine Learning Computations” International Conference on Artificial Intelligence and Statistics (AISTATS 2017), PMLR 54:1020-1029. 1029
    • Nourhan Sakr and Cliff Stein. (2016) “An empirical study of online packet scheduling algorithms” Proceedings of the 15th International Symposium on Experimental Algorithms (SEA 2016) - Volume 968, pp 278-293
    • Salma Roshdy, CSCE graduate
    • Omar Elsheikha, CSCE graduate, Co-advisor: T. Sakr
    • Omar Elseadawy, CSCE graduate
    • Karim Farid, CSCE graduate
    • Michael Azer, FINC graduate, Co-advisor: A. Bassiouny
    • Rania Elshenety, MACT undergraduate, Co-advisor: A. Hadi
    • Menna Hassan, MACT undergraduate, Co-advisor: A. Charpentier
    • CSCE 1001: Fundamentals of Computing I
    • CSCE 2202: Analysis and Design of Algorithms
    • CSCE 4930: Foundations of Data Science
    • CSCE 4930: Data Science and Optimization
    • CSCE 4910: Guided Studies on Reinforcement Learning Applications
    • CSCE 4950: Industrial Training
    • CSCE 4980/1: Senior Projects
    • CSCE 5221: Algorithms and Complexity Theory
    • CSCE 5930: Data-driven Optimization
    • DSCI 1412: Fundamentals of Data Science II
    • FINC 5320: Financial Computing
    • FINC 5402: Seminar on FinTech Research
    • MACT 4332: Short-term Actuarial Mathematics II
Research Interest
  • Data Science
  • Combinatorial Optimization
  • Reinforcement Learning
  • Operations Research
  • Algorithm Design
  • Social Impact
  • Education and Policy Design