Education
- Ph.D. in Computer Science, University of Virginia, 2014-2018
- Advisor: Dr. Yanjun Qi
- Thesis: Fast and Interpretable Classification of Sequential Data in Biology, University of Virginia’s nominee for CGS/ProQuest Distinguished Dissertation Award for Mathematics, Physical Sciences, and Engineering
- M.S in Computer Science, University of Virginia, 2012-2014
- B.E in Computer Engineering, University of Pune (India), 2008-2012
Research Experience
- Senior Research Fellow, University of Washington, 2018-2019
- Advisor: Dr. William Noble
- Research Intern, Microsoft Research New England, May-Aug 2017
- Advisor: Dr. Jennifer Listgarten
Publications
For most recent publications (post-2019) please refer to the Singh Lab @ Brown website
Submitted
- Jacob Schreiber, R. Singh, Jeff Bilmes, and William Stafford Noble, “A pitfall for machine learning methods aiming to predict across cell types.” [bioRxiv] (2019)
2019
- Jie Liu, Yuanhao Huang, R. Singh, Jean-Philippe Vert, and William Stafford Noble, “Jointly embedding multiple single-cell omics measurements”. WABI. [bioRXiv][code]
2018
- Arshdeep Sekhon, R. Singh, and Yanjun Qi, “DeepDiff: Deep-learning for predicting Differential gene expression from histone modifications”. Bioinformatics (ECCB). [paper][code]
2017
- R. Singh, Jack Lanchantin, Arshdeep Sekhon, and Yanjun Qi, “Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin”. NIPS. [arXiv][code]
- R. Singh, Arshdeep Sekhon, Kamran Kowsari, Jack Lanchantin, Beilun Wang, and Yanjun Qi, “GaKCo: a Fast GApped k-mer string Kernel using COunting”. ECML-PKDD. [arXiv][code]
- Beilun Wang, R. Singh, and Yanjun Qi, “A constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models”. Machine Learning. [paper]
- Jack Lanchantin, R. Singh, and Yanjun Qi. “Memory Matching Networks for Genomic Sequence Classification”. ICLR Workshop. [arXiv]
- Jack Lanchantin, R. Singh, Beilun Wang, and Yanjun Qi. “Deep Motif Dashboard: Visualizing and Understanding Genomic Sequences Using Deep Neural Networks”. Pacific Symposium on Biocomputing. (PSB). [arXiv][code]
- Peiwu Qin, Mahmut Parlak, Cem Kuscu, Jigar Bandaria, Mustafa Mir, Karol Szlachta, R. Singh, Xavier Darzcaq, Ahmet Yildiz, and Mazhar Adli. “Live cell imaging of low- and non-repetitive chromosome loci using CRISPR/Cas9”. Nature Communications. [paper]
2016
- R. Singh, Jack Lanchantin, Gabriel Robins, and Yanjun Qi. “Transfer String Kernel for Cross-Context DNA-Protein Binding Prediction”. IEEE/ACM Transactions on Computational Biology and Bioinformatics. [arXiv][code]
- R. Singh, Jack Lanchantin, Gabriel Robins, and Yanjun Qi. “DeepChrome: Deep-learning for predicting gene expression from histone modifications”. Bioinformatics. (ECCB). [paper][arXiv][code][website]
- R. Singh and Yanjun Qi. “Character based String Kernels for Bio-Entity Relation Detection”. ACL BioNLP Workshop. [paper][slides]
- Beilun Wang, R. Singh, and Yanjun Qi. “A constrained l1 minimization approach for estimating multiple Sparse Gaussian or Nonparanormal Graphical Models”. ICML Workshop on Computational Biology. [arXiv]
- Jack Lanchantin, R. Singh, Zeming Lin, and Yanjun Qi.”Deep Motif: Visualizing Genomic Sequence Classifications”. ICLR and ICML Workshops on Computational Biology. [arXiv][code]
2015
- R. Singh, Jack Lanchantin, Gabriel Robins, and Yanjun Qi. “Transfer String Kernel for Cross-Context Transcription Factor Binding Prediction”. International Workshop on Data Mining in Bioinformatics at KDD (BIOKDD).
- R. Singh, Cem Kuscu, Aaron Quinlan, Yanjun Qi, and Mazhar Adli.”Cas9-chromatin binding information enables more accurate CRISPR off-target prediction”. Nucleic Acid Research. [paper][website]
- Aravinda Kuntimaddi, Nicholas J Achille, Jeremy Thorpe, Alyson A Lokken, R. Singh, Charles S Hemenway, Mazhar Adli, Nancy J Zeleznik-Le, John H Bushweller. “Degree of recruitment of DOT1L to MLL-AF9 defines level of H3K79 Di- and tri-methylation on target genes and transformation potential”. Cell Reports. [paper]
- Fujun Qin, Zhenguo Song, Mihaela Babiceanu, Yansu Song, Loryn Facemire, R. Singh, Mazhar Adli, Hui Li. “Discovery of CTCF-sensitive cis-spliced fusion RNAs between adjacent genes in human prostate cells”. PLOS Genetics. [paper]
2014
- Cem Kuscu, Sevki Arslan, R. Singh, Jeremy Thorpe, and Mazhar Adli. “Genome-wide analysis reveals characteristics of off-target sites bound by the Cas9 endonuclease”. Nature Biotechnology. [paper]
Selected Talks
- June 2019: “Unsupervised manifold alignment for single-cell genomics” at Algorithms and Models for Single Cell Genomics Workshop (UC Irvine) and BBI Single Cell Symposium (Fred Hutch Cancer Research Center)
- November 2017: (Invited) “Attend and Predict: Understanding Gene Regulation by Selective Attention on Chromatin” at Casa Matemática Oaxaca (CMO) – Banff International Research Stations (BIRS) Workshop (Oaxaca, Mexico)
- March 2017: “DeepChrome+” at Thirteenth UVa Engineering Research Symposium (University of Virginia) [First Prize]
- September 2016: “DeepChrome: Deep-learning for predicting gene expression from histone modifications” at ECCB 2016 (The Hague, Netherlands)
- June 2016: (Invited) “Transfer String Kernel for Cross-Context Sequence Specific DNA-Protein Binding Prediction” at Indraprastha Institute of Information Technology – Delhi (India)
Teaching Experience:
- Fall 2019: Deep Learning in Genomics (Graduate Level)
- Spring 2019: Deep Learning in Genomics (Undergraduate Level)
Service:
- Program Committee Member: ACM-BCB 2019, ACM-BCB 2020
- Reviewer: RECOMB 2019, ISMB/ECCB 2019, BIOKDD 2019, NeurIPS 2019, ICML 2020, NeurIPS 2020, Nature Communications, PLOS Computional Biology
- Chair: Brown Unconference 2020
Awards and Honors
- COBRE CBHD Pilot Award (Brown University) – 2020
- Algorithms and Models for Single Cell Genomics Workshop Travel Award – 2019
- NIPS Travel Award – 2017
- Grace Hopper Celebration of Women in Computing Student Scholarship – 2017 (Anita Borg Institute)
- Graduate Student Award for Outstanding Research 2016-2017 (Department of Computer Science, UVA)
- First Prize in Podium Presentation – 2017 (13th Annual UVA Engineering Research Symposium)
- Travel Fellowship ECCB – 2016 (International Society of Computational Biology)
- L. William Ballard Fellowship – 2015 (School of Engineering and Applied Sciences, University of Virginia)
- Chief of Army Staff Best Outgoing Student Award – 2012 (Army Institute of Technology, University of Pune)
- TATA Merit Scholarship Award – 2010 (Army Institute of Technology, University of Pune)
Organizations
Graduate Society of Women Engineers (GradSWE) @ University of Virginia
Participated in:
- Undergraduate Mentorship Program (An undergraduate SWE member is paired with a graduate student mentor)
- Professional panel discussion for High School Visitation with SWE (Offered perspective about STEM research to high school girls)