
Dr. Mohamed Nafea
Assistant Professor, Electrical and Computer Engineering Department
Email: mnafea@mst.edu
Office: 131 Emerson Electric Co Hall;
Phone: (573) 341-4558
About Me
I am an Assistant Professor in Computer Engineering in the Electrical & Computer Engineering (ECE) department at Missouri University of Science & Technology. Before joining Missouri S&T, I was an assistant professor in the ECE department at University of Detroit. Prior to that, I spent a year as a postdoctoral research fellow at Georgia Tech, ECE.
I received my Ph.D. degree in electrical engineering from Penn State, University Park, in December 2018, under supervision of Dr. Aylin Yener. I also received a masters degree in mathematics from Penn State in 2017. Before that, I received a masters degree in wireless & information technologies from Nile University, Egypt, in 2012, and my bachelor degree in Electrical Engineering (communication & electronics specialization) from Alexandria University, Egypt, in 2010.
My research lies at the intersection of statistical learning, information and data sciences, and causal reasoning, and aims to solve problems in responsible development of machine learning models encompassing issues of reliability & trustworthiness, explainability/interpretability, privacy, robustness and security, and algorithmic fairness. Specific areas of research interest include:
- Developing explainable & fair ML models, with emphasis on “representation learning” approaches.
- Federated learning & distributed optimization, with emphasis on privacy, fairness, and robustness.
- Causal reasoning & inference with applications to ML interpretability & fairness; social & biological sciences, and econometrics.
- ML diagnostic models for Healthcare applications, with emphasis on explainability, privacy, robustness, trustworthiness, and fairness.
- Information theory; with emphasis on its applications to ML systems such as Explainable-ML & representation learning, as well as security & privacy of information processing systems.
On the application side, I am interested in a wide range of disciplines including information processing systems, image processing, data science, health informatics, as well as social, biological, and legal sciences.
Join US! I am always looking for excelled and self-motivated PhD students to join our research group. If you are interested, please check out this flyer and apply accordingly. Application not following instructions listed will likely not be reviewed.
If you are already a student at Missouri S&T, then taking a course that I am offering and doing very well is a great plus.
News!
- March 2025: Our paper “Information-theoretic quantification of inherent discrimination bias in training data for supervised learning”” is accepted for presentation at the 2nd Workshop on Navigating and Addressing Data Problems for Foundation Models (DATA-FM @ ICLR 2025), in conjunction with the 13th International Conference on Learning Representations ICLR 2025.
- March 2025: Our paper “Centralized and federated heart disease classification using UCI dataset: A benchmark with interpretability analysis” is accepted for publication and oral presentation at the 2025 IEEE Evolution conference, to be held in Boston, MA, June 2025.
- February 2025: I gave a talk at the 2025 Information Theory and Application (ITA2025) Workshop, titled “Information-theoretic quantification of inherent discrimination bias in training data for supervised learning”.
- January 2025: Junior undergrad, computer science, student Yeva Vainerman joined our research group. Welcome Yeva!
- October 2024: Our paper “Causal discovery in linear models with unobserved variables and measurement error” is accepted for presentation at the Causal Representation Learning workshop at the 2024 Neural Information Processing Conference (CRL@NeurIPS24).
- August 2024: I started a new position as an Assistant Professor in Computer Engineering at Missouri University of Science & Technology, ECE department.
- August 2024: I was elevated to an IEEE senior member!
- August 24: My master’s student Mario Rodriguez has successfully defended his master’s thesis!
- July 2024: Our paper “Causal Discovery in Linear Models with Unobserved Variables and Measurement Error” is available on arXiv.
- May 2024: PhD, computer engineering, student Sokrat Aldarmini joined our research group. Welcome Sokrat!
- April 2024: I delivered a virtual talk titled “Towards Responsible AI: Learning with Biased, Imperfect, and Decentralized Data” to the Computer Science Department at Texas Tech University.
- March 2024: I visited the ECE department at University of New Haven and delivered the same talk.
- February 2024: I visited the ECE department at Missouri University of Science and Technology and delivered the same talk.