Hi, my name is Ruth Johnson, and I’m currently a 5th year computer science PhD student at the University of California, Los Angeles working with Sriram Sankararaman and Bogdan Pasaniuc. I am interested in the intersection of machine learning and medical data, specifically electronic health records and genomics.

This past summer, I worked as a Data Science intern at Microsoft where I worked on explainable AI (XAI) tools for web experiences. Previously, I worked on deep learning applications for genome sequencing technology at Illumina as a summer intern and as an R&D engineering intern at Sandia National Laboratories in Albuquerque, NM.

I am also currently on the 2023 job market! Feel free to reach out at: ruthjohnson at ucla dot edu. View my CV (here).

Recent News


Publications

  1. Leveraging genomic diversity for discovery in an EHR-linked biobank: the UCLA ATLAS Community Health Initiative.
    Ruth Johnson, Yi Ding, Vidhya Venkateswaran, Arjun Bhattacharya, Alec Chiu, Tommer Schwarz, Malika Freund, Lingyu Zhan, Kathryn S. Burch, Christa Caggiano, Brian Hill, Nadav Rakocz, Brunilda Balliu, Jae Hoon Sul, Noah Zaitlen, Valerie A. Arboleda, Eran Halperin, Sriram Sankararaman, Manish J. Butte, UCLA Precision Health Data Discovery Repository Working Group, UCLA Precision Health ATLAS Working Group, Clara Lajonchere, Daniel H. Geschwind, Bogdan Pasaniuc; Genome Medicine in-press.

  2. Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases
    Global Biobank Meta-analysis Initiative; Cell Genomics in-press.

  3. Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Re- sults from the Host Genetics Initiative
    Guillaume Butler-Laporte et al; PLOS Genetics in-press.

  4. Estimation of regional polygenicity from GWAS provides insights into the genetic architecture of complex traits
    Ruth Johnson, Kathryn S. Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc, Sriram Sankararaman; PLOS Computational Biology 2021.

  5. EH3k27ac-HiChIP in prostate cell lines identifies risk genes for prostate cancer susceptibility
    Claudia Giambartolomei, Ji-Heui Seo, Tommer Schwarz, Malika Kumar Freund, Ruth Johnson, Sandor Spisak, Sylvan C. Baca, Alexander Gusev, Nicholas Mancuso, Bogdan Pasaniuc, Matthew L. Freedman; American Journal of Human Genetics 2021.

  6. Virtual meetings promise to eliminate the geographical and administrative barriers and increase accessibility, diversity, and inclusivity
    Juncheng Wu, Anushka Rajesh, Yu-Ning Huang, Karishma Chhugani, Rajesh Acharya, Kerui Peng, Ruth Johnson, Andrada Fiscutean, Carla Daniela Robles-Espinoza, Francisco M. De La Vega, Riyue Bao, Serghei Mangul; Nature Biotechnology 2021.

  7. Mapping the human genetic architecture of COVID-19
    COVID-19 Host Genetics Initiative; Nature 2021.

  8. Integrative analyses identify susceptibility genes underlying COVID-19 hospitalization
    Gita Pathak, Kritika Singh, Tyne Miller-Fleming, Frank Wendt, Nava Ehsan, Kangcheng Hou, Ruth Johnson, Zeyun Lu, Shyamalika Gopalan, Loic Yengo, Pejman Mohammadi, Bogdan Pasaniuc, Renato Polimanti, Lea Davis, Nicholas Mancuso; Nature Communications 2021.

  9. Pre-existing conditions in Hispanics/Latinxs that are COVID-19 risk factors
    Timothy S Chang, Yi Ding, Malika K Freund, Ruth Johnson, Tommer Schwarz, Julie M Yabu, Chad Hazlett, Jeffrey N Chiang, Ami Wulf, Daniel H Geschwind, Manish J Butte, Bogdan Pasaniuc; iScience 2021.

  10. Localizing components of shared transethnic genetic architecture of complex traits from GWAS summary data.
    Huwenbo Shi, Kathryn S Burch, Ruth Johnson, Malika K Freund, Gleb Kichaev, Nicholas Mancuso, Astrid M Manuel, Natalie Dong, Bogdan Pasaniuc; American Journal of Human Genetics 2020.

  11. A scalable method for estimating the regional polygenicity of complex traits
    Ruth Johnson, Kathryn S. Burch, Kangcheng Hou, Mario Paciuc, Bogdan Pasaniuc, Sriram Sankararaman; RECOMB 2020.

  12. An automated machine learning-based model predicts postoperative mortality using readilyextractable preoperative electronic health record data
    Brian Hill, Robert Brown, Eilon Gabel, Christine Lee, Maxime Cannesson, Loes Olde Loohuis, Ruth Johnson, Brandon Jew, Uri Maoz, Aman Mahajan, Sriram Sankararaman, Ira Hofer, Eran Halperin; British Journal of Anaesthesia 2019.

  13. Probabilistic fine-mapping of transcriptome-wide association studies
    Nicholas Mancuso, Malika K. Freund, Ruth Johnson, Huwenbo Shi, Gleb Kichaev, Alexander Gusev, and Bogdan Pasaniuc; Nature Genetics 2019.

  14. A unifying framework for joint trait analysis under a non-infinitesimal model
    Ruth Johnson, Huwenbo Shi, Bogdan Pasaniuc, Sriram Sankararaman; ISMB 2018 (simultaneously published in Bioinformatics 2018).

  15. Improved methods for multi-trait fine mapping of pleiotropic risk loci
    Gleb Kichaev, Megan Roytman, Ruth Johnson, Eleazar Eskin, Sara Lindström, Peter Kraft, Bogdan Pasaniuc; Bioinformatics 2017.

(preprints)

  1. Electronic health record signatures identify undiagnosed patients with Common Variable Immunodeficiency Disease
    Ruth Johnson, Alexis V Stephens, Sergey Knyazev, Lisa A Kohn, Malika K Freund, Leroy Bondhus, Brian L Hill, Tommer Schwarz, Noah Zaitlen, Valerie Arboleda, Manish J Butte, Bogdan Pasaniuc; medRxiv 2022 (under review at Science Translational Medicine).

  2. The UCLA ATLAS Community Health Initiative: promoting precision health research in a diverse biobank
    Ruth Johnson, Yi Ding, Arjun Bhattacharya, Alec Chiu, Clara Lajonchere, Daniel H Geschwind, Bogdan Pasaniuc; medRxiv 2022. (under revision at Cell Genomics).

Talks

  1. Electronic health record signatures identify undiagnosed patients with CVID
    California Center for Rare Diseases Genomic Rounds, November 2021. Virtual meeting.

  2. A scalable method for estimating the regional polygenicity of complex traits
    RECOMB, July 2020, Virtual.

  3. Leveraging electronic health record signatures identify undiagnosed patients with Common Variable Immunodeficiency Disease
    Undiagnosed Diseases Network - Steering Committee Meeting, March 2020. Los Angeles, CA, USA. (cancelled due to COVID-19)

  4. Leveraging electronic health record signatures identify undiagnosed patients with Common Variable Immunodeficiency Disease
    Institute for Quantitative and Computational Biosciences - Research Seminar, February 2020. Los Angeles, CA, USA.

  5. Electronic health record signatures identify undiagnosed patients with of CVID
    Medical and Population Genetics seminar - Computational Genomics and Health, November 2019. Los Angeles, CA, USA.

  6. A scalable Bayesian framework for estimating the proportion of causal variants for a complex trait from GWAS
    Probabilistic Modeling In Genomics, Nov 2018. Long Island, NY, USA.

  7. A unifying framework for joint trait analysis under a non-infinitesimal model
    ISMB 2018, July 2018. Chicago, IL, USA.

  8. CANVIS: Correlation Annotation VISualization
    RECOMB-Genetics Satellite Meeting, July 2017. Los Angeles, CA, USA.


Awards & Recognitions

  • Charles J. Epstein Trainee Award for Excellence in Human Genetics Research semi-finalist (2022)
  • EECS Rising Stars participant (2020)
  • Stellar Abstract Award Honorable Mention at Program in Quantitative Genomics Conference (2020)
  • RECOMB 2020 Travel Fellowship (2020)
  • NSF-NRT MENTOR Training Grant (2018)
  • Ford Foundation Predoctoral Fellowship - Honorable Mention (2018)
  • NSF Graduate Research Fellowships Program - Honorable Mention (2017)
  • Eugene V. Cota-Robles Fellowship (2017)
  • Dean’s Prize for Excellence for Undergraduate Research (2017)
  • Undergraduate Bioinformatics Research Award (2017)
  • Chancellor’s Service Award (2017)