Priya Veeraraghavan
About Priya Veeraraghavan
Priya Veeraraghavan is a scientist specializing in computational biology, currently working at Dyno Therapeutics in Watertown, Massachusetts. She holds a PhD from Harvard University and has extensive experience in computational biology and software development through various roles in academia and industry.
Title at Dyno Therapeutics
Priya Veeraraghavan currently holds the position of Scientist, Computational Biology at Dyno Therapeutics. Based in Watertown, Massachusetts, her work focuses on leveraging computational methods to advance the field of gene therapy.
Education and Academic Background
Priya earned her PhD in Biological and Biomedical Sciences from Harvard University, holding the prestigious NSF Graduate Research Fellowship during her studies. Prior to her PhD, she completed a Bachelor's degree in Computational and Molecular Biology (Course 6-7) from the Massachusetts Institute of Technology (MIT). Her educational career began at the Liberal Arts and Science Academy High School (LASA).
Professional Experience and Research Contributions
Priya has accumulated a wealth of experience in various research roles. She interned as a Computational Chemistry Intern at USV PRIVATE LIMITED, contributed to rare cancer research at the Broad Institute with the Chordoma Project, and developed software tools for biological data analysis during her internship at Google. She also participated in cancer genomics studies at the Dana-Farber Cancer Institute and contributed to undergraduate research at MIT's Computer Science and Artificial Intelligence Laboratory (CSAIL).
Roles in Corporate and Biotech Development
Apart from her academic and research endeavors, Priya has gained corporate experience as a Corporate Development Intern at VC-Backed Biotech NewCo. This role, which she held from 2022 to 2023, provided her with a valuable perspective on the business side of biotech industries.
Research Focus Areas
Throughout her career, Priya's research has spanned several key areas in computational biology. She has worked on computational methods for drug discovery, molecular and computational approaches to study the kinetics of axonal RNA transport, and machine learning techniques for optimizing antibody affinity to antigens.