Summary
Overview
Work History
Education
Skills
Volunteer Experience
Awards
Timeline
Generic

PRIYANKA MAKHIJANI

Summary

Machine Learning Engineer/Scientist with hands-on experience developing and deploying clinical AI solutions across imaging, quality assessment, and treatment recommendation pipelines. Skilled in building clinical workflows, delivering high accuracy, and strong model interpretability.

Overview

7
7
years of professional experience

Work History

Machine Learning Engineer II (SaMD))

VIDEAHEALTH INC.
New York, USA
07.2024 - Current
  • Developed a proof-of-concept 'bad image classifier' to identify non-diagnostic X-rays as part of RCM, with over 80% accuracy.
  • Contributed to clinical data science and treatment recommendation initiatives, improving restorative and orthodontic assessments; achieved 94% alignment with dentist recommendations.
  • Built a unified model to classify and correctly orient X-rays with 93% rotation accuracy and 86% view accuracy.
  • Delivered client-driven image quality filters, enhancing in app usability, and clinical relevance.
  • Key strengths : Statistical analysis, explainable AI, clinical data science, Computer Vision

Senior Lead Machine Learning Engineer (SaMD)

IDEA EVOLVER LLC
New York City, USA
05.2023 - Current
  • Ideating Solutions for ACNU platform - First kind approach for Rx to OTC switch in The USA market for FDA approved drugs.
  • Assisted with designing Drug NoSQL database - matching prescribing information on drug products with a 85% match.
  • Utilizing supervised machine learning approach for ACNU feasibility with a precision of 93%.
  • Utilizing Generative AI approach with LLMs to fine-tune foundation models on self-assessment data to predict outcome for cholesterol and hypertension medications in conjunction with ACNU feasible drugs with an accuracy of 98%.
  • Adherence modeling to analyze cholesterol medication qualified users with 88% accuracy.
  • Key strengths : Statistical analysis, Generative AI, LLMs, explainable AI, Prompt Engineering, Model Optimizations.

Machine Learning Scientist (MedTech - Robotics Surgery)

CHEMIMAGE CORPORATION
Pittsburgh, USA
12.2021 - 05.2023
  • Designing Deep Learning Models for Hyperspectral Imaging (HSI) for minimally invasive surgeries done laparoscopically to detect real-time critical structures.
  • Worked on ex vivo Tissue Vis-NIR Signatures + Key Wavelengths to understand different critical structures reflectance and absorbance standards using univariate analysis.
  • Using Supervised and semi-supervised approach to analyze images and driving in-house GT methodology in medical imaging and post-hoc approaches to meet improvement in overall system performance.
  • Designing end-to-end algorithms with custom training parameters and evaluation on blind datasets for robust and generalizable models.
  • Researched novel approaches for CNN models in TensorFlow for semantic segmentation with fuzzy GT.
  • Precision on segmentation model >80% and recall > 90%.
  • Key strengths : Image Processing, Deep Learning, Statistical analysis, Image Segmentation Fuzzy Ground Truth, Hyperspectral Images, Image Processing, ONNX Models, Applied Research Medical Image Segmentation.

SOFTWARE ENGINEER - Data Science and NLP (Retail Tech)

DEEPNORTH INC.
Foster City, USA
05.2019 - 12.2021
  • Python development for data analysis, statistical inference and visualization on large datasets.
  • Worked on prescriptive and predictive analytics to offer more insights about metrics directly impacting customers to take decisions.
  • Key strengths : Structured Large Datasets, Machine Learning, Statistical analysis, Retail Analytics, Hypothesis Design, GCP, Microsoft Azure.

DEEP LEARNING ENGINEER INTERN (MedTech)

SIEMENS HEALTHINEERS
Hoffman Estates, USA
05.2018 - 12.2018
  • Researched & developed imaging solutions for clinical applications by applying deep learning and computer vision techniques on 3-D neuro DynaCT images.
  • Implementation of fully automatic stenosis(lesion) segmentation by developing prototypes of Deep neural networks : Extraction of features and stenosis detection using CNN for DICOM reconstructed image formats.
  • Conducting experiments on different model choices to achieve competitive performance by devising custom loss and metric functions and analyzing images for information rich exemplars.
  • Key Strengths : Tensorflow, Keras, ITK-SNAP, DICOM Images, Dyna-CT Images, Semantic Segmentation, U-NETS, 3-D Images.

Education

Masters - Computer Science

ILLINOIS INSTITUTE OF TECHNOLOGY
12.2018

Bachelors of Technology - Computer Science

MANIPAL UNIVERSITY JAIPUR
07.2016

Skills

  • Python
  • Prompt Engineering
  • Fine Tuning LLMs
  • Tensorflow
  • PyTorch

Volunteer Experience

  • Labeller, AI Podcast - Building career path in Healthcare AI
  • Illinois Institute of Technology, Alumni Mentor, 11/01/22, 04/30/23
  • ValleyML.AI Deep Learning Bootcamp, AI Course Instructor, 01/01/22, San Francisco, CA
  • WomenOfAI.org, Bay Area Ambassador, 01/01/20, 01/31/21, San Francisco
  • ValleyML.AI, Invited Speaker, 12/01/19, Milpitas, CA
  • Women Who Code, Invited Speaker, 01/01/18, Chicago, IL

Awards

  • Best Hack Using Amazon Web Services, HackPrinceton '18, 04/01/18, Princeton University
  • Qualifier for Microsoft Imagine Cup World Finals, HackIllinois '18, 02/01/18, University of Illinois, Urbana-Champaign
  • Second Place Prize, ScarletHacks '17, 11/01/17, Illinois Institute of Technology

Timeline

Machine Learning Engineer II (SaMD))

VIDEAHEALTH INC.
07.2024 - Current

Senior Lead Machine Learning Engineer (SaMD)

IDEA EVOLVER LLC
05.2023 - Current

Machine Learning Scientist (MedTech - Robotics Surgery)

CHEMIMAGE CORPORATION
12.2021 - 05.2023

SOFTWARE ENGINEER - Data Science and NLP (Retail Tech)

DEEPNORTH INC.
05.2019 - 12.2021

DEEP LEARNING ENGINEER INTERN (MedTech)

SIEMENS HEALTHINEERS
05.2018 - 12.2018

Masters - Computer Science

ILLINOIS INSTITUTE OF TECHNOLOGY

Bachelors of Technology - Computer Science

MANIPAL UNIVERSITY JAIPUR

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