Meghana Kshirsagar

Currently: Senior Research Scientist, Microsoft, AI for Good research

Formerly: Postdoctoral researcher

Memorial Sloan Kettering Cancer Center

Graduate student

School of CS, Carnegie Mellon University

meghana dot ksagar at gmail dot com

(I moved to Redmond, WA!)

I joined Microsoft in 2019 after my post-doc in Christina Leslie's group. Prior to this, I did a brief stint at IBM Research, in the Machine Learning group (headed by Naoki Abe) working with Aurelie Lozano and Eunho Yang. I graduated from the School of Computer Science, Carnegie Mellon where I was advised by Prof. Jaime Carbonell and Prof. Judith Klein-Seetharaman. I am interested in the broad area of machine learning for computational biology, health and social good problems. I am currently working on building deep learning model for understanding epigenetic regulation from NGS assays, cryptic pocket binding from MD simulations data, statistical genetics among other things. My thesis focussed on multitask and transfer learning methods for host-pathogen protein-protein interaction prediction.

Before computational biology I have had not-so-brief stints in the areas of Information Retrieval for structured data (during my Masters at IIT Bombay) and Information Extraction from unstructured data (at Yahoo! Labs). I worked with S. Sudarshan at IIT Bombay and with Rajeev Rastogi, Srinivasan H. Sengamedu and Shailesh Kumar at Yahoo! Labs.

I was a TA for Machine Learning in the Spring of 2012, with Roni Rosenfeld. In the Spring of 2011, I TA-ed Data Mining and Information Retrieval with Jaime Carbonell.

Here is my CV CV

Publications (outdated). Please check my CV above / google scholar instead.

Journals and Proceedings

Under review:

"Becoming good at AI for good", Meghana Kshirsagar*, Caleb Robinson*, Siyu Yang* et al.

"Recurrent Convolutional Neural Networks for large scale Bird species classification", Gaurav Gupta, Meghana Kshirsagar, Ming Zhong, Shahrzad Gholami, Juan Lavista Ferres

"Identifying Human Interactors of SARS-CoV-2 Proteins and Drug Targets for COVID-19 using Network-Based Label Propagation", Jeffrey N. Law, Kyle Akers, Nure Tasnina, Catherine M. Della Santina, Meghana Kshirsagar, Judith Klein-Seetharaman, Mark Crovella, Padmavathy Rajagopalan, Simon Kasif, T. M. Murali


"Protein sequence models for prediction and comparative analysis of the SARS-CoV-2 —human interactome", Meghana Kshirsagar, Nure Tasnina, Michael D. Ward, Jeffrey N. Law, T. M. Murali, Juan M. Lavista Ferres, Gregory R. Bowman and Judith Klein-Seetharaman
Pacific Symposium on Biocomputing 2021 [Paper] [Code]

"A Network-Based Label Propagation Framework to Reposition Drugs for COVID-19", Jeffrey Law, Meghana Kshirsagar, Mark Crovella, Padmavathy Rajagopalan, Judith Klein-Seetharaman, Simon Kasif and T. M. Murali
Intelligent Systems for Molecular Biology 2020, COVID-19 special session

"BindSpace: decoding transcription factor binding signals by large-scale joint embedding", Han Yuan, Meghana Kshirsagar, Lee Zamparo, Yuheng Lu, and Christina Leslie
Nature Methods 2019 [Paper on biorxiv]

"Learning interpretable models of transcription factor binding from atac-seq data", Meghana Kshirsagar, Han Yuan, Lee Zamparo, and Christina Leslie. (In preparation).

"Learning task structure via sparsity grouped multitask learning", Meghana Kshirsagar, Eunho Yang, and Aurelie C. Lozano
European Conference on Machine Learning (ECML 2017) [Paper on Arxiv]

"Multitask matrix completion for learning protein interactions across diseases", Meghana Kshirsagar, Keerthiram Murugesan, Jaime Carbonell and Judith Klein-Seetharaman.
In Research in Computational and Molecular Biology (RECOMB 2016) [Paper] [Code]
Journal of Computational Biology, 2017 (extended version)

"Frame-Semantic Role Labeling with Heterogeneous Annotations", Meghana Kshirsagar, Sam Thomson, Nathan Schneider, Jaime Carbonell, Noah A. Smith and Chris Dyer, Assoc. for Computational Linguistics (ACL) 2015 [Paper] [Code] [Slides] (part of the SEMAFOR system)

"Techniques for transferring host-pathogen protein interactions knowledge to new tasks", Meghana Kshirsagar, Sylvia Schleker, Jaime Carbonell and Judith Klein-Seetharaman, Frontiers in Microbiology, 2015. [Paper] [Code]

"Comparing human–Salmonella with plant–Salmonella protein–protein interaction predictions", Sylvia Schleker, Meghana Kshirsagar and Judith Klein-Seetharaman, Frontiers in Microbiology, 2015. [Paper]

"Multi-task learning for Host-Pathogen protein interactions", Meghana Kshirsagar, Jaime Carbonell and Judith Klein-Seetharaman
In Intelligent Systems for Molecular Biology (ISMB) and
Bioinformatics 2013
[Paper] [Supplementary, Data, Code]

"Techniques to cope with missing data in host-pathogen protein interaction prediction", Meghana Kshirsagar, Jaime Carbonell and Judith Klein-Seetharaman
In European Conference for Computational Biology (ECCB) and
Bioinformatics 2012
[Paper] [Supplementary Info]

"Virus interactions with human signal transduction pathways", Zhongming Zhao, Junfeng Xia, Oznur Tastan, Irtisha Singh, Meghana Kshirsagar, Jaime Carbonell, Judith Klein-Seetharaman, I. J. Computational Biology and Drug Design 4(1): 83-105 (2011). [Paper]

"High Precision Web Extraction using Site Knowledge", Meghana Kshirsagar, Rajeev Rastogi, Sandeepkumar Satpal, Srinivasan Sangamedu and Venu Satuluri, Conference On Management of Data (COMAD) 2010 (Best Paper Award) [Paper]

"Keyword search on external memory data graphs", Bhavana Dalvi, Meghana Kshirsagar and S. Sudarshan, Very Large Databases (VLDB) 2008. [Paper]

Workshop papers, Posters

"Inferring transcription factor binding profiles jointly from SELEX and ATAC-seq", Meghana Kshirsagar, Han Yuan, Christina Leslie Cold Spring Harbor Labs (CSHL) workshop for Quantitative Biology, 2017.

"Iteratively Regrouped Lasso: learning group structure in genome wide association studies in crops", Meghana Kshirsagar, Aurelie Lozano and Eunho Yang, Workshop on Data Science for Food, Energy and Water, Knowledge Discovery and Data Mining (KDD) 2016

"Automated Sorghum Phenotyping and Trait Development Platform", Mitch Tuiinstra, Cliff Weil, Addie Thompson, Chris Boomsma, Melba Crawford, Ayman Habib, Edward Delp, Keith Cherkauer, Larry Biehl, Naoki Abe, Meghana Kshirsagar, Aurelie Lozano, Karthikeyan Natesan, Peder Olsen, Eunho Yang, Workshop on Data Science for Food, Energy and Water, Knowledge Discovery and Data Mining (KDD) 2016

"Leveraging Heterogeneous Data Sources for Relational Semantic Parsing", Meghana Kshirsagar, Nathan Schneider and Chris Dyer, Assoc. for Computational Linguistics (ACL) 2014 workshop on Semantic Parsing

"Multisource transfer learning for host-pathogen protein interaction prediction in unlabeled tasks", Meghana Kshirsagar, Jaime Carbonell and Judith Klein-Seetharaman, NIPS Workshop on Machine Learning for Computational Biology, 2013 [Paper] [Talk Slides]

"Confident prediction of Salmonella-human protein-protein interactions" Schleker S., Nouretdinov I., Garcia-Garcia J., Oliva B., Meghana Kshirsagar, Klein-Seetharaman J. and Gammerman A, ECCB 2012.

"Transfer learning based methods towards the discovery of host-pathogen protein-protein interactions", Meghana Kshirsagar, Jaime Carbonell and Judith Klein-Seetharaman, ISMB 2012. [Poster]

Reviewing/ Program Committee

PLoS Comp Bio, NIPS 2016-18, ICLR 2017-18, ICML 2017-19, WWW 2017-18 Posters, Neural Computation, Biotechnology Journal, IJCAI 2016, BMC Genomics 2014, Workshop for ML in Comp Bio 2016

PC Co-chair/ Organizer: ICML Workshop for Comp Bio 2017, ICML Workshop for Comp Bio 2018


If you have an old but working laptop/PC to donate to a needy child, please contact me! Here's the website of our campaign: CMU Laptop Rehab

Some of my hobbies are reading science-fiction, birding, photography, kayaking, playing board-games. I have trained in Kathak, an Indian classical dance form. I also love to ice-skate in Pittsburgh winters.