CV

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

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)

Service:

  • Program Committee Member: 10th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics (2019)
  • Reviewer:  RECOMB 2019, ISMB/ECCB 2019, BIOKDD 2019, NeurIPS 2019

Awards and Honors

  • 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)