Aiden Aceves

A passionate entrepreneur who has founded three companies and is a community builder across the LA and San Diego Life Science Communities. At Caltech, my work focuses on developing machine learning and modeling methods to support the engineering of biomolecules ranging from small peptides to antibody-drug conjugates. A unifying theme of this work is adapting machine learning to domains where existing data is sparse or non-existent, and where experimental observation is slow, expensive, or otherwise prohibitive. I have developed methods incorporating reinforcement learning, active learning, transfer learning and representation learning, and work with sequence, structural, and textual data, in addition to molecular dynamics. Prior to joining Caltech, I studied pure chemistry at UC Riverside, where I earned a 4.0 GPA and conducted research on organic synthesis and toxicology. I have been involved in the founding and operation of life sciences and fintech companies, and am an active member of the lifesciences communities of Los Angeles and San Diego. These roles have given me a hands-on knowledge of the drug discovery and candidate selection processes, as well as experience with sales, academic partnerships, and working with contractors. I have served as a Data Science intern at the Novartis Institutes for BioMedical Research (NIBR), and am an active reviewer for the American Association of Pharmaceutical Scientists annual meeting. I currently serve as the Co-President of the Biotechnology Club at Caltech, an organization providing students, post docs, and faculty members with opportunities to discover and explore opportunities in industry and entrepreneurship.