Sarah M. Coleman

Sarah M. Coleman is a Postdoctoral Research Fellow in the Department of Statistics and Data Sciences at the University of Texas at Austin. Her research focuses on integrating computational and experimental approaches to advance metabolic engineering, synthetic biology, and bioprocess optimization. She holds a PhD in Chemical Engineering (2024), MS in Statistics (2024), and BS in Chemical-Biological Engineering (2019) from MIT. Her work emphasizes sustainable biomanufacturing using non-traditional feedstocks and improving microbial strain robustness through systems biology methods.

Key research interests include metabolic pathway engineering for omega-3 production, statistical modeling of synthetic gene circuits, and leveraging Yarrowia lipolytica for industrial applications. She explores topics such as extracellular electron transfer for living materials and CFD modeling in bioreactor scale-up. Her interdisciplinary background combines chemical engineering principles with advanced statistical analysis to solve complex bioprocess challenges.

Recent publications highlight innovations in microbial tolerance to industrial waste, plant-based photonic systems, and biosensor-driven metabolic pathway optimization. Her research bridges computational modeling with lab-scale experimentation, addressing scalability and sustainability in biotechnology. While no formal awards are listed, her contributions reflect cutting-edge advancements in bioengineering and data-driven bioprocess development.