Kamel Lahouel

Kamel Lahouel is an Assistant Professor at the Early Detection and Prevention Division of the Translational Genomics Research Institute (TGen). He joined TGen in February 2022 and focuses on mathematical and statistical models applied to cancer biology.

• Education: Ph.D. in Applied Mathematics and Statistics from Johns Hopkins University (2018).

Dr. Lahouel specializes in machine learning and stochastic processes to analyze cell-free DNA for cancer early detection and minimal residual disease testing (MRD). His methodological work includes branching processes, Markov chains, and non-parametric statistics for tasks like stochastic optimization and multiple hypothesis testing. His research also explores pattern recognition in latent dynamical systems.

Recent publications highlight his development of generative models for tumorigenesis timelines (2020), supervised mutational signatures in cancer (2021), and data-driven blood testing combined with PET-CT (2020). His work bridges applied mathematics with clinical oncology, emphasizing computational approaches for early cancer detection.