Lukas Buecherl
Biological Engineering
Assistant Professor
Educational Background
Biography
Lukas Buecherl earned his B.S. in Electrical Engineering and Information Technology from Ulm University in Germany in 2019. He then joined the University of Colorado Boulder, where he completed both his M.S. and Ph.D. in Biomedical Engineering through the Interdisciplinary Quantitative Biology Program. His interdisciplinary training across engineering, computation, and biology now shapes his work as Assistant Professor of Biological Engineering at Utah State University.
Dr. Buecherl’s research focuses on making engineered biological systems more reliable, predictable, and transferable from the lab to real-world applications. His group works at the intersection of synthetic biology, systems biology, and biocomputation, combining computational modeling, machine learning, formal analysis, and experimental characterization to improve the design and performance of genetic circuits and other engineered biological systems. His interests include model-guided design of genetic systems, machine-readable and automation-ready biological workflows, reproducible computational biology, and the development of standards and tools that support more robust engineering of living systems. More broadly, he is interested in advancing engineering biology through approaches that integrate design, measurement, computation, and automation.
Dr. Buecherl is also active in the broader synthetic biology community through leadership in open science, standards development, and scientific community building. He has served as an elected Editor for the Synthetic Biology Open Language, a member of the iGEM Registry Steering Committee, General Chair of Bio Innovation Week, and Communications Chair for the Institute of Biological Engineering. His contributions to the field have been recognized through several awards, including the Excellent Mentorship Award and the Outstanding Graduate Researcher Award from the University of Colorado Boulder.
Teaching Interests
Synthetic Biology Engineering, Systems Biology Modeling, Python Programming, Technical Presentation Skills for Engineers
Research Interests
1.) Genetic Circuit Design, Analysis, and Model-Guided Engineering
2.) Robustness, Reliability, and Predictability in Engineered Biological Systems
3.) Formal Modeling, Verification, and Machine Learning for Synthetic Biology
4.) Biological Design Automation and Automation-Ready Experimental Workflows
5.) Open Science, Standards, and Reproducible Computational Biology