Hi, my name is Ruth Johnson, and I’m currently a postdoctoral researcher at Harvard Medical School working with Dr. Marinka Zitnik. I completed my PhD in Computer Science at UCLA under Dr. Bogdan Pasaniuc and Dr. Sriram Sankararaman.

My research focuses on developing machine learning methods that integrate electronic health records and genomic biobanks with the goal of translating large-scale health data into tools for disease discovery and improved patient care. My work spans clinical foundation models, graph machine learning, and methods in statistical genetics.

I am currently on the 2026-2027 job market seeking faculty positions at the intersection of AI & Medicine! Feel free to reach out at: ruth_johnson at hms dot harvard dot edu. View my CV (here).

Recent News

• [June 2026] Our work on clinical knowledge embeddings with applications in LLMs is accepted to npj Digital Medicine, Embeddings of clinical codes enable knowledge-grounded AI in medicine.

• [May 2025] Broke my leg, and had surgery to put it back together with plates and screws.

• [October 2024] Our abstract, Unified Clinical Vocabulary Embeddings for Advancing Precision Medicine, is awarded a Stellar Abstract Award and platform presentation at the Annual Program in Quantitative Genomics Conference in Boston, MA.

• [July 2024] Our review on Graph AI in biomedicine is published in Annual Review of Biomedical Data Science, Graph Artificial Intelligence in Medicine.

• [May 2024] Our work on CVID is published in Science Translational Medicine, Electronic health record signatures identify undiagnosed patients with Common Variable Immunodeficiency Disease. See news coverage here, here and here.

Publications

1. Embeddings of clinical codes enable knowledge-grounded AI in medicine
   Ruth Johnson, Uri Gottlieb, Galit Shaham, Lihi Eisen, Jacob Waxman, Stav Devons-Sberro, Curtis R. Ginder, Peter Hong, Raheel Sayeed, Xiaorui Su, Ben Y. Reis, Ran D. Balicer, Noa Dagan, Marinka Zitnik; npj Digital Medicine 2026

2. Multimodal Medical Code Tokenizer
   Xiaorui Su, Shvat Messica, Yepeng Huang, Ruth Johnson, Lukas Fesser, Shanghua Gao, Faryad Sahneh, Marinka Zitnik ; ICML 2025.

3. Multimodal AI predicts clinical outcomes of drug combinations from preclinical data
   Yepeng Huang, Xiaorui Su, Varun Ullanat, Intae Moon, Ivy Liang, Lindsay Clegg, Damilola Olabode, Ruth Johnson, Nicholas Ho, Megan Gibbs, Alexander Gusev, Bino John, Marinka Zitnik; arXiv 2025 (under revision at Nature Communications).

4. Graph AI in Medicine
   Ruth Johnson, Michelle M. Li, Ayush Noori, Owen Queen, and Marinka Zitnik; Annual Review of Biomedical Data Science 2024.

5. 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; Science Translational Medicine 2024.

6. Polygenic scores for tobacco use provide insights into systemic health risks in a diverse EHR-linked biobank in Los Angeles
   Vidhya Venkateswaran, Kristin Boulier, Yi Ding, Ruth Johnson, Arjun Bhattacharya, Bogdan Pasaniuc; Translational Psychiatry 2024.

7. 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; Cell Genomics 2023.
   

8. 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 2022.

9. Global Biobank Meta-analysis Initiative: powering genetic discovery across human diseases
   Global Biobank Meta-analysis Initiative; Cell Genomics 2022.

10. Exome-wide association study to identify rare variants influencing COVID-19 outcomes: Results from the Host Genetics Initiative
    Guillaume Butler-Laporte et al.; PLOS Genetics 2022.

11. 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.

12. 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.

13. 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.

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

15. 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.

16. 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.

17. 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.

18. 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.

19. An automated machine learning-based model predicts postoperative mortality using readily extractable 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.

20. 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.

21. 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).

22. 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.

Talks

1. Unified Clinical Vocabulary Embeddings for Advancing Precision Medicine
   Annual Program in Quantitative Genomics Conference, October 2024. Boston, MA.

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

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

4. 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)

5. 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.

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

7. 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.

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

9. 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)