I'm a PhD Candidate in Computer Science at Stanford University, advised by Dr. Anshul Kundaje. My research focuses on leveraging machine learning to better understand how the human genome encodes information -- in particular, how genomic sequence regulates the moment when RNA transcription is initiated. My thesis work is on developing and interpreting ProCapNet, which can accurately predict transcription initiation at base-resolution in human cells.
I love science, and I love teaching -- mostly CS109, Stanford's Intro to Probability course. I've also had the wonderful experience of mentoring a few junior scientists (high school and undergrad), including two of my co-authors on the ProCapNet project.
Before Stanford, I conducted research with Dr. Shaun Mahony at the Center For Eukaryotic Gene Regulation at Penn State University. Previously, I graduated from Duke University with a Bachelor's in CS and Minors in Statistics and Computational Biology, beginning my research career in the lab of Dr. Jeremy Kay. I also proudly served as drum major of the Duke University Marching Band.
In my free time, I play trumpet, foster cats, rock climb, bake, and make music with the Stanford Laptop Orchestra.
Cochran, K., Yin, M., Mantripragada, A., Schreiber, J., Marinov, G., Yu, H., Lis, J.T.,
& Kundaje, A.
2024. Dissecting the cis-regulatory syntax of transcription initiation with deep learning. bioRxiv.
Cochran, K., Srivastava, D., Shrikumar, A., Balsubramani, A.,
Hardison, R.C., Kundaje, A., & Mahony, S.
2022. Domain-adaptive neural networks improve cross-species transcription
factor binding prediction. Genome Research. 32(3): pp. 512-523.
Ray, T., Cochran, K., Kozlowski, C., Wang. J., Alexander, G., Cady,
M.A., Spencer. W.J., Ruzycki, P.A., Clark, B.S., Laeremans, A., He, M-X.,
Wang, X., Park, E., Hao, Y., Iannaccone, A., Hu, G., Fedrigo, O., Skiba, N.P.,
Arshavsky, V.Y., & Kay, J.N.
2020. Comprehensive identification of mRNA isoforms reveals the diversity of
neural cell-surface molecules with roles in retinal development and disease.
Nature Communications. 11(1): pp. 1-20.
Ray, T., Cochran, K., & Kay, J. 2019. The enigma of CRB1 and CRB1 retinopathies. In: Bowes Rickman C., Grimm C., Anderson R., Ash J., LaVail M., Hollyfield J. (eds) Retinal Degenerative Diseases. Advances in Experimental Medicine and Biology, vol 1185. Springer, Cham.