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Akshay Khunte is a seasoned researcher with expertise in machine learning and cardiovascular data science. Currently working as a Machine Learning Researcher at Cardiovascular Data Science (CarDS) Lab, he has also held positions at Yale University School of Medicine, where he worked on various projects including public health research and brain tumor detection. With a strong educational background, Khunte holds an MD/PhD from NYU Grossman School of Medicine and a Bachelor of Science in Computer Science from Yale University. Proficient in multiple languages, including Marathi and Spanish, he has also gained experience in working with MATLAB and Magnetic Resonance Imaging data analysis software.

Credentials

  • Deep Learning Specialization
    Coursera
    Jan, 2021
    - Apr, 2026

Experience

    • Machine Learning Researcher
      • Aug 2021 - Present

      Using machine learning to diagnose cardiovascular diseases from ECG signal and image data.Developing novel noise-augmentation techniques for wearable-adapted training of ECG signal models.Khunte A et al. Detection of Left Ventricular Systolic Dysfunction from Single-Lead Electrocardiography Adapted for Wearable Devices https://www.nature.com/articles/s41746-023-00869-w

    • United States
    • Research Services
    • 700 & Above Employee
    • Wiznia Lab — Public Health Research Assistant
      • Jun 2019 - May 2024

      Working to identify treatment disparities between Medicaid and privately insured patients at Urgent Care Centers in all fifty US states; using JMP statistical analysis software to analyze collected data and discern patterns and statistically significant results; currently publishing new research paper on access to testing for COVID-19.

    • deGraaf Lab — Magnetic Resonance Research Assistant
      • Jun 2017 - Aug 2020

      Using MATLAB and Magnetic Resonance Imaging data analysis software to improve spectroscopic image analysis to increase the accuracy and speed of brain tumor detection; developing software dedicated to mapping of tumor progression and simulating Nuclear Magnetic Resonance (NMR) experiments to reduce the time, manpower, and cost of NMR data acquisition.

  • Liminal Sciences, Inc.
    • Guilford, Connecticut, United States
    • Machine Learning Intern
      • Jun 2021 - Aug 2021
      • Guilford, Connecticut, United States

      Worked on the development of time-series classification and regression models for an ultrasound-based brain imaging device.

Education

  • 2024 - 2031
    NYU Grossman School of Medicine
    MD/PhD
  • 2020 - 2024
    Yale University
    Bachelor of Science - BS, Computer Science
  • 2016 - 2020
    Xavier High School in Middletown, CT
    High School Diploma

Suggested Services

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Industry Focus. “Computer Software”

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