Here's who I am & what I do


Hey, I am Nidhi Soley thanks for stopping by. I am a Ph.D. student in the Biomedical Engineering (BME) Department at the Johns Hopkins University. I completed my Masters in Science in BME from the University of Utah, Salt Lake City.

I am passionate about developing and using data science and ML algorithms to solve real-world problems at the intersection of precision medicine, digital health and medical big-data. My goal as a researcher is to bridge the gap between predictive modeling and clinical decision-making by using and combining ML methods with mathematical modeling.

Publications and Posters

  • N. Soley, S. Song, N.F. Manov, and C.O. Taylor, Risk for Poor Post-Operative Quality of Life Among Wearable Use Subgroups in an All of Us Research Cohort, Pacific Symposium on Biocomputing (PSB) 2023.
  • D. Tong, N. Soley, M.A. Schwart, and T.C. Bidone, Characterization of full length alpha2bBeta3 integrin intermediates: from their atomistic dynamics to the assembly of adhesions, Biophysical Journal.
  • N. Soley, A. Klein, C.O. Taylor, G. Ewachiw, H. Shah, and J. Bodurtha, Feasibility of the Genetic Information Assistant Chatbot to Provide Genetic Education and Study Genetic Test Adoption Among Pancreatic Cancer Patients at Johns Hopkins Hospital, AMIA 2023 Informatics Summit. Seattle, WA. March 13-16, 2023.
  • N. Soley, C.O. Taylor, Predicting Post Operative Pain and Chronic Opioid Use through Machine Learning , Johns Hopkins University Department of Medicine & Whiting School of Engineering Research Retreat 2023 (poster presentation).
  • Education

    Doctor of Philosophy - Biomedical Engineering

    May 2023 - Present

    Johns Hopkins University, Baltimore, Maryland, USA

    Master of Science - Biomedical Engineering

    Jan, 2021 - May 2022

    University of Utah, Salt lake City, Utah, USA
    CGPA : 3.89/4

    • Master of Science in Biomedical Engineering with specialization in Computational systsems and data science [Project Track].
    • Coursework : Data Science for Biomedical Engineers, Applied Machine Learning, Genomic Signal Processing, Deep Learning for BME, Visualization of Scientific Computing

    Bachelor of Engineering, major: Biomedical Engineering

    2016 - 2020

    Shri G.S. Institute of Technology & Science, Indore, India
    CGPA : 8.65/10

    • Bachelor of Engineering with Biomedical Major form S.G.S.I.T.S. affiliated to R.P.G.V., Bhopal.
    • Coursework : Programming Tools and Techniques, Biomedical Statistical Signal Processing, Artificial Neural Networks, Signal Processing, Network Systems

    Senior School Certificate Examination


    S.V.M. Bhopal
    Central Board of Secondary Education

    • Scored 92.6 percent in the 12th Grade Central Board of Secondary Education Examination.

    Work Experience

    Research Assistant

    May 2022-Present

    Institute of Computational Medicine, The Johns Hopkins University

    • Guided by Dr. Casey Overby Taylor, Associate Professor of Biomedical Engineering.
    • Working on two projects:
    • Developing models to find association between preoperative physical activity measures taken from Fitbit device and postoperative pain and chronic opioid use.
    • Designing genomic medicine practice registry to study what are (in)effective clinical practices, with and without genomics in specialty genetics care setting.

    Graduate Research Assistant

    May, 2021-May 2022

    Scientific Computing and Imaging Institute, University of Utah

    • Guided by Dr. Tamara Bidone, Assistant Professor of Biomedical Engineering.
    • Download Project Report[pdf]
    • Worked towards MS project on: The role of αIIbβ3 integrin conformation on the stability and composition of cell adhesions- Application and development of new computational approaches from molecular simulations
    • Performed the molecular dynamics(MD) simulations on alpha2bBeta3 integrin imtermediate from atomistic model to mesoscale modeling to understand the mechanism of platelete aggregation. Used PCA to understand the dynmaics of the protein. Embeded the results into brownian dynamics mesoscale model mimic the functioning of cell. The results could help in drug discovery for thrombotic/hemostatics disorders.

    Teaching Assistant : Computation Methods for Bioengineers

    Jan, 2021 - May, 2021

    University of Utah, Salt lake City, Utah, USA

    • Teaching Assistant for Computational methods for Bioengineers- MATLAB. Graded and took lab sessions for 120 students.


    I have worked on various projects, some of the major ones are listed below.

    Detecting Early Alzheimer using MRI data and Machine Learning

    June 2021

    • Performed exploratory data analysis, extracted crucial features, and developed a sound ML model that can help clinicians predict patient being demented or non-demented at an early stage of Alzheimer.

    Analysing Patterns of Gene Expression in Melanoma Skin Cancer

    April 2021

    • Analyzed Melanoma Skin Cancer gene expression data obtained from under the TCGA project.
    • Computed and visualized the SVD of the data. Analyzed it statistically and through GOrilla for the labels like gender and ethnicity

    Breast cancer detection using machine learning algorithms

    March 2020

    • Detection of tumour in breast as benign or malignant using various machine learning algorithms.
    • Do a comparative study of various machine learning algorithms used till date for breast cancer detection and target at getting more accuracy and specificity than in the existing models.

    Intracerebral Haemorrhage Lesion Detection using Image Processing in MATLAB

    June 2019

    • Detecting and highlighting haemorrhage lesion area in MRI images using image processing tools in MATLAB.
    • This project is concerned with brain strokes and investigates proposed image processing techniques to improve the detection of such strokes.

    Face recognition using PCA in MATLAB

    May 2018

    • The program recognizes a face from a database of human faces using PCA. The principal components are projected onto the eigenspace to find the eigenfaces and an unknown face is recognized from the minimum Euclidean distance of projection onto all the face classes.

    Low-Cost hearing aid

    May 2018

    • Designed and manufactured a low-cost audio amplifier. The entire circuit of hearing aid consumed a very small amount of power within the range of 10 milliwatts that could be used as economical hearing aid.


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


    I would like to express my deepest appreciation to the person who put this website together. I am grateful to you.