Akshay Balsubramani

Akshay is a machine learning scientist and geneticist with a background in learning and probability theory.

He did postdoctoral work at Stanford Genetics with the Kundaje lab, developing models to derive biological insight from large-scale functional genomic data. He received his Ph.D. in Computer Science from UC San Diego with Yoav Freund after spending time in several machine learning industry research labs, and has experience developing semi-supervised, nonparametric, and sequential learning methods. He grew up in India and Southeast Asia in addition to the US, and enjoys traveling, improv comedy, running, history, and being a mad (sports) fan.


Wainberg, M.*, Kamber, R.A.*, Balsubramani, A*., Meyers, R.M., Sinnott-Armstrong, N., Hornburg, D., Jiang, L., Chan, J., Jian, R., Gu, M., Shcherbina, A., Dubreuil, M. M., Spees, K., Meuleman, W., Snyder, M. P., Bassik, M. C., and Kundaje, A., 2021. A genome-wide atlas of co-essential modules assigns function to uncharacterized genes. Nature Genetics, 53(5).

Koh, P.W., Sagawa, S., Marklund, H., Xie, S.M., Zhang, M., Balsubramani, A., Hu, W., Yasunaga, M., Phillips, R.L., Gao, I., Lee, T., David, E., Stavness, I., Guo, W., Earnshaw, B., Haque, I., Beery, S. M., Leskovec, J., Kundaje, A., Pierson, E., Levine, S., Finn, C., and Liang, P., 2021, July. Wilds: A benchmark of in-the-wild distribution shifts. In International Conference on Machine Learning (ICML 2021). PMLR.

Balsubramani, A., Dasgupta, S., Freund, Y., and Moran, S., 2019. An adaptive nearest neighbor rule for classification. Advances in Neural Information Processing Systems (NeurIPS 2019), 32.

Donahue, C., Lipton, Z.C., Balsubramani, A., and McAuley, J., 2018. Semantically decomposing the latent spaces of generative adversarial networks. International Conference on Learning Representations (ICLR 2018).

Balsubramani, A., 2017. Optimal Binary Autoencoding with Pairwise Correlations. International Conference on Learning Representations (ICLR 2017).

Balsubramani, A. and Ramdas, A., 2016. Sequential nonparametric testing with the law of the iterated logarithm. Uncertainty in Artificial Intelligence (UAI 2016).

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