Kellen Petersen

Kellen Petersen is a Postdoctoral Research Fellow in the Department of Neurology at the Albert Einstein College of Medicine. His research focuses on applying machine learning techniques to understand Alzheimer’s Disease progression, including biomarker analysis and predictive modeling. He also investigates superhydrophobic surface dynamics using numerical methods derived from phase field and energy approaches.

Education: PhD in Mathematics (New York University, 2020), MS in Mathematics (NYU), and dual BS degrees in Mathematics and Physics (University of Utah). His doctoral work under Dr. Robert V. Kohn explored metastable droplet states and surface optimization to minimize energy barriers.

Research interests include machine learning applications in neurology, mathematical modeling of biological systems, Alzheimer’s biomarker analysis, and interdisciplinary approaches to disease progression. Key contributions include developing risk scores for cognitive impairment and analyzing CSF inflammatory cytokines as prognostic indicators.

Recent talks include a 2021 presentation on APOE4’s role in Alzheimer’s biomarker associations at the APOE4 and Immunity Conference. His work bridges mathematical rigor with clinical neuroscience, targeting heterogeneous patient subgroups through machine learning frameworks.