Here's who I am & what I do

About

I am a Ph.D. candidate in Biomedical Engineering at Johns Hopkins University. My research focuses on integrating multimodal longitudinal healthcare data, including wearables, Electronic Health Records (EHR), and genomics and develop predictive and interpretable ML models for personalized medicine and leveraging Large Language Models to enhance health insights, and patient communication. user-friendly explanations.

Recenet Publications and Posters

  • Soley N, Bentil M, Shah J, Rouhizadeh M and Taylor CO, Unveiling Social Determinants of Health Impact on Adverse Pregnancy Outcomes through Natural Language Processing, Nature Scientific Reports, SDOH Collection, 2025 (under review).
  • Soley N, Rattsev I, Speed TJ, Xie A, Ferryman KS and Taylor CO, Predicting postoperative chronic opioid use with fair machine learning models integrating multi-modal data sources: a demonstration of ethical machine learning in healthcare, Journal of the American Medical Informatics Association, 2025.
  • Soley N , Zhang S, Zong J, Greenstein J, Taylor CO, Ruchti T, and Mendez-Tellez PA, Early dynamic prediction of organ system deterioration in intensive care unit (ICU) patients using machine learning, Journal of Critical Care, 2025.
  • Soley N, Speed TJ, Xie A, and Taylor CO, Predicting Postoperative Pain and Opioid Use with Machine Learning Applied to Longitudinal Electronic Health Record and Wearable Data, Applied Clinical Informatics, 2024.
  • Nguyen M, Soley N, Rattsev I, Jelin A, and Taylor CO, Strolr: An LLM-enabled Chatbot to Support Pregnant Womens Quick and Easy Information Seeking from Trustworthy Sources, System Demonstration, American Medical Informatics Association, Annual Symposium, 2024.

    • Education

    Doctor of Philosophy, Biomedical Engineering

    JHU
    May 2023 – Present

    Johns Hopkins University, Baltimore, MD, USA

    • Specialization: Biomedical Data Science. Advisor: Dr. Casey Overby Taylor
    • Thesis: Understanding and Enhancing Patient-Centered Outcomes in Pregnancy through Multimodal ML and LLM-based Interpretability Tool

    Master of Science, Biomedical Engineering

    University of Utah
    Jan 2021 – May 2022

    University of Utah, Salt Lake City, UT, USA

    • Specialization: Computational Systems and Biomedical Data Science. Advisor: Dr. Tamara Bidone
    • MS Thesis: Investigated αIIbβ3 integrin conformational states and their impact on platelet adhesion dynamics through multiscale molecular modeling and simulations.

    Bachelor of Engineering, Biomedical Engineering

    SGSITS
    Aug 2016 – May 2020

    Shri G.S. Institute of Technology & Science (SGSITS), Indore, India

    Research Experience

    Research Associate

    JHU
    May 2022 – May 2023

    Institute for Computational Medicine, Johns Hopkins University

    • Developed ML models for multimodal, longitudinal datasets (clinical, genomic, EHR, and wearable/Fitbit data) to support patient-centered outcomes in surgical recovery and chronic pain management.
    • Designed fair ML frameworks to predict chronic opioid use in post-operative patients, addressing bias and improving generalizability across diverse populations.

    Graduate Research Assistant

    SCI Institute
    May 2021 – May 2022

    Scientific Computing and Imaging Institute, University of Utah

    • Performed atomistic and coarse-grained molecular dynamics simulations to study integrin dynamics, followed by dimensionality reduction (PCA) to capture dominant conformational changes.
    • Integrated simulation findings into a Brownian dynamics framework to model cell-scale behavior, providing insights relevant to drug discovery in thrombotic and hemostatic disorders.

    Awards & Leadership Roles

    A selection of honors, teaching roles, and leadership experiences that reflect my commitment to research, education, and innovation.

    • 2024–2025: Lead Teaching Assistant, Precision Care Medicine (EN.580.480/680), Johns Hopkins University. Designed assignments, led grading, delivered an unsupervised ML lectures, and mentored 9 graduate student teams.
    • 2023: Honorable Mention Paper Award, 14th ACM Conference on Bioinformatics, Computational Biology, and Health Informatics.
    • 2023: NSF Travel Grant Recipient, International Workshop on Computational Network Biology.
    • 2021: Graduate Teaching Assistant, Bioengineering Computational Methods (BME-3301), University of Utah. Held office hours, graded coursework, and mentored 6 student teams.
    • 2021: Gold Medalist, Department of Biomedical Engineering, SGSITS (Academic Year 2019–2020).
    • 2016–2020: Recipient of Central Sector Scholarship for College and University Students, awarded by the Government of India.

    Contact

    Hope you had fun reading and enjoyed small peek into my world !! Feel free to reach out.