Aaron Feller
PhD Candidate in Computational Biochemistry
The University of Texas at Austin
PhD Candidate in Computational Biochemistry
The University of Texas at Austin
I work at the intersection of machine learning and molecular science, focusing on building models that help make sense of complex biological data. My current projects involve developing predictive tools for peptides and designing interpretable systems that bridge the gap between raw sequences and real-world applications.
I’m interested in creating tools that are both scientifically rigorous and practically useful—models that can be deployed, not just published. My approach combines computational techniques with a deep understanding of biological systems to uncover patterns and insights that drive innovation in biotech and pharma.