Mokhtar Z. Alaya

Mokhtar Z. Alaya is an Assistant Professor of Statistics and Machine Learning at the Computer Science Department of Université de Technologie de Compiègne (UTC), where he is affiliated with the LMAC Laboratory. He holds a PhD in Statistical Machine Learning from Université Pierre et Marie Curie (2016) and has conducted postdoctoral research at institutions including Université de Rouen and Université Paris Nanterre.

Education:

• PhD in Statistical Machine Learning, Université Pierre et Marie Curie (2016)
• Master’s in Statistics and Probabilities, Université Pierre et Marie Curie (2011–2012)
• Magisterium of Mathematics, University of Gabes, Tunisia (2010)

Research Interests: His work focuses on statistical machine learning, including optimal transport for ML applications, high-dimensional statistics, matrix completion, and deep learning. Key projects include interdisciplinary collaborations in mechanics (AI4Meca) and chemistry (AI4Chem), leveraging deep learning for anomaly detection and materials science.

Teaching: Courses include Machine Learning, Linear Algebra, and Probability at UTC and international partners like UTSEUS (China). He emphasizes bridging theory and practical coding in Python.

Advising & Labs: Supervises PhD students in topics like robust anomaly detection and Frechét regression. Collaborates extensively with the LMAC Lab and cross-disciplinary teams on projects such as generative deep learning for materials engineering.