Omkar Prabhune

Position title: M.S. Student



I am a master’s student in Electrical and Computer Engineering at UW-Madison. I am broadly interested in Machine Learning, Computer Vision, Data Science, and Software Development. I completed my Bachelor’s in Electronics and Telecommunication with a minor in Computer Engineering from College of Engineering, Pune. I worked with Citi for 2 years as a Machine Learning and Software Engineer.


  • University of Wisconsin-Madison | August 2021 – Present
    M.S. in Electrical and Computer Engineering
  • College of Engineering, Pune | May 2019
    B.Tech in Electronics and Telecommunication
    Minor in Computer Engineering

Research Interests

  • Machine Learning
  • Data Science
  • Computer Vision
  • Embedded Systems


  • Adobe Intern Project Expo 2022 Winner – Digital Media Organization
  • Graduate Student Grant 2022, North Central Sustainable Agriculture Research and Education
  • Design Automation Conference (DAC) Young Fellowship, 2021
  • Best Outgoing Student Award by College of Engineering, Pune from the undergraduate batch of 2019
  • Best Student Project Award 2019 for undergraduate theses by Tata Consultancy Services
  • Smart India Hackathon 2019 National Winner, conferred by the Government of India


Work Experience

University of Wisconsin-Madison

Research Assistant | January 2022 – Present

  • Developing Deep Learning and Computer Vision models for behavior analysis and activity monitoring of dairy cattle for early prediction of health conditions such as heat stress for sustainable livestock.
  • Modeling Computer Vision system for cattle detection, identification, tracking, and posture recognition, and deploying them in resource-constrained environments such as edge devices.

Adobe Inc.

SWE (Machine Learning) Intern | June 2022 – September 2022

  • Developed Machine Learning models to automate the task of bug triaging (classification) for Quality Engineering team.
  • Improved the accuracy of the ML model from 49% to 80% with better data analysis, cleaning, handling of data imbalance, and improved text processing, feature engineering, text vectorization, and gradient boosting model optimization.
  • Built ML prediction pipeline and integrated it with the in-house tool for bug triaging to automate 5 hours of manual work per engineer per week. Secured 1st position in the Intern Project Expo 2022.

University of Wisconsin-Madison

Teaching Assistant – ECE 315 | Fall 2021, Spring 2022

  • Conducted lab sessions on EDA tools for PCB design, discussion sessions and grading.

Citigroup Inc. (Citibank)

Technology Analyst – Data Science and Software Development | August 2020 – July 2021

  • Built Data Analytics and Visualization dashboard providing insights into large data on trade settlements. Constructed a streamlined data pipeline. Improved user experience by making it intuitive to navigate and comprehend.
  • Developed Natural Language Processing (NLP) engine for entity and intent recognition. Achieved 22.7% increase in accuracy and 350% increase in user engagement in Smart Search Application.
  • RESTful APIs and website development for Data Lineage Tool using Agile methodology to improve the productivity and collaboration of software development teams in the organization.
  • Developed commentary redaction tool using Natural Language Processing (NLP) to automate the process of proofreading, reducing the commentary’s time-to-market and human errors (Citi’s D10X Hackathon – 2nd position).
  • Pilot Projects: Modeled machine learning-based prediction of fraudulent credit card transactions using clustering, developed deep learning-based signature verification to reduce the processing time for document verification.

Nanyang Technological University, Singapore

Research Intern at Rapid Rich Object Search (ROSE) Lab – Deep Learning | May 2018 – July 2018

  • Modeled Deep Convolutional Neural Network-based text-paragraph image classification.

Siemens Technology and Services Pvt Ltd.

Research Intern – Intelligence Traffic Systems | July 2017 – February 2018

  • Developed Computer vision-based real-time vehicle detection for Adaptive Traffic Signal Controller resulting in travel-time and emission reduction.