Joshua Rollins is a computational biology and machine learning PhD candidate and graduate researcher at CUNY with nine years of experience blending academic research and production-grade software engineering. He has applied ML to bioscience problems at institutions including Harvard Medical School, D. E. Shaw Research, and in Dr. Lei Xie's lab, bringing a rare mix of deep technical rigor and practical implementation. Earlier roles—ranging from web and curriculum development to project management and freelance science journalism—reflect strong communication skills and an ability to translate complex ideas for diverse audiences. His training spans PhD work in computer science, graduate studies at Harvard in machine learning and writing, and dual bachelor’s degrees in electrical engineering and applied math from the University of Washington, grounding him in algorithms, embedded systems, and computational methods. Formerly part of the Debora Marks Lab, he bridges protein- and genomics-focused research with scalable ML tooling, often shipping reproducible code alongside publications. Based in New York, he combines interdisciplinary curiosity with hands-on engineering to move models from theory into impactful biological insight.
9 years of coding experience
7 years of employment as a software developer
Bachelor’s Degree Applied and Computational Mathematical Sciences (Discrete Mathematics and Algorithm Design), Bachelor’s Degree Applied and Computational Mathematical Sciences (Discrete Mathematics and Algorithm Design) at University of Washington
Doctor of Philosophy - PhD Computer Science, Doctor of Philosophy - PhD Computer Science at The Graduate Center, City University of New York
Bachelor’s Degree Electrical Engineering (Embedded Computing Sys), Bachelor’s Degree Electrical Engineering (Embedded Computing Sys) at University of Washington College of Engineering
Associate of Science Degree in Computer and Electrical Engineering, Associate of Science Degree in Computer and Electrical Engineering at Bellevue College
Graduate Studies Machine Learning and Writing, Graduate Studies Machine Learning and Writing at Harvard University
toolkit for finding likely cas9 off-target binding and effect on gene expression, designing sgRNAs and pairs of sgRNAs with minimal off-target effect on gene-expression
Contributions:32 commits, 8 PRs, 36 pushes in 2 years 3 months
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