Mukundh Murthy
PhD student, computational biologist, passionate about drug discovery and machine learning
Summary
Mukundh Murthy is an aspiring leader in computational biology and drug discovery, evidenced by his upcoming PhD at Stanford Genetics and his current role as a Visiting Researcher at the Broad Institute of MIT and Harvard. His work spans statistical genetics, single-cell technologies, and protein engineering, applying advanced computational methods to biological challenges. nitter+2
He demonstrates a strong foundation in machine learning and its application to biotechnology, particularly in drug discovery. His internship at Octant involved developing predictive models and a 'Library Enumerator' to optimize chemical library design and forecast drug potency, significantly improving the efficiency of identifying promising drug candidates. His Medium posts also highlight his expertise in machine learning and chemiinformatics. octant+1
Mukundh is engaged in academic research with publications in prestigious journals like Nature Genetics, co-authoring work on transcriptome-wide analysis. His Google Scholar profile shows a focus on genomics and computational biology. google+1
He is committed to fostering innovation and entrepreneurship in biotech. As a co-founder and Managing Director of the Nucleate Ann Arbor Chapter and founder of Michigan BioCatalyst, he actively supports students in translating their research into new biotechnology ventures. michiganbiocatalyst
His educational background from the University of Michigan in Computer Science, combined with his research interests, underscores his multidisciplinary approach. He applied physics-informed neural networks to cell signal transduction modeling in his 'AI for Science' course, reflecting a deep understanding of combining AI with fundamental scientific principles. umich
Work
Education
Projects
Writing
Transcriptome-wide analysis of differential expression in perturbation atlases
January 1, 2025Co-authored a paper published in Nature Genetics applying new statistical methods to understand cellular response to genetic perturbations.
Machine Learning for More Informed Drug Screening: My Data Science Internship
September 14, 2023Authored a blog post detailing his machine learning internship at Octant Bio, where he developed tools and models to accelerate drug discovery, including a 'Library Enumerator' and predictive models for drug potency.
Generating Molecular Conformations via Normalizing Flows and Neural ODEs
March 25, 2022How are Protein Structures Refined?
Blog post explaining force field functions, Rosetta, and deep learning in protein structure refinement.