Surag Nair

I am a PhD student in Computer Science at Stanford. My primary interests are in Machine Learning, Genomics and Natural Language Processing. At Stanford, I work with Anshul Kundaje on single-cell epigenomics and deep learning models for chromatin accessibility.

I spent Summer 2018 at Apple where I worked in the Siri International team. I also TAed the Winter 2018 edition of CS230 Deep Learning. I have developed open-source implementations of interesting machine learning systems such as Alpha Zero and sequence GANs.

I did my undergrad from IIT Delhi in Electrical Engineering. I worked with Mausam on temporal information extraction. Previously, I've spent a summer on the beautiful campus of University of Lausanne working with Christophe Dessimoz on speeding up the detection of homologous biological sequences.

Recent Updates

14 October 2022: dynseq is published in Nature Genetics! [paper]

8 June 2022: dynseq track preprint out, available at UCSC, WashU and HiGlass/Resgen browsers! [preprint]

8 March 2022: fastISM is published in Bioinformatics! [paper] [code] [docs] [slides] [talk]

19 September 2020: Developed fastISM, 10x faster in-silico saturation mutagenesis for convolutional neural networks. Accepted to MLCB 2020 for oral presentation (15% acceptance rate) [code] [docs] [preprint] [slides] [talk]

29 April 2019: Our paper on predicting chromatin accessibility across cellular contexts was accepted for an oral presentation in ISMB 2019 [slides] [talk] [code]

29 December 2017: A Simple Alpha(Go) Zero Tutorial


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