Sara Kohtz

Sara Kohtz is an Assistant Professor in the School of Systems Science and Industrial Engineering at Binghamton University. She holds a BS (2016) and MS (2017) in Industrial Engineering from Binghamton University and a PhD in Industrial Engineering from the University of Illinois at Urbana-Champaign (2024). Her research focuses on machine learning theory and applications in high-impact engineered systems, particularly physics-informed machine learning for energy systems, reliability engineering, and fault diagnosis in electrified systems.

• Education Background:
• PhD: Industrial Engineering – University of Illinois at Urbana-Champaign
• MS: Industrial Engineering – Binghamton University
• BS: Industrial Engineering – Binghamton University

Her work bridges data science and engineering, addressing challenges in battery management, sensor placement, and optimal system design. Recent publications emphasize machine learning methodologies for prognostics, energy systems optimization, and physics-driven models.

Professional memberships include ASME, IISE, and the Society of Women Engineers (SWE). No awards or grants are explicitly listed in the provided information.