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About Me.

I'm an aspiring Machine Learning engineer who loves to experiment with data augmentation, image processing and pattern recognition. I'm currently an Electrical Engineering graduate student at Columbia University in the City of New York.

Education

2022-2023

Columbia University

Master of Science

Electrical Engineering with a focus in Data Driven Analysis and Control.

2016-2020

PES University

Bachelor of Technology

Major - Electronics and Communication Engineering 

Minor - Computer Science Engineering

Work Experience

May 2023 - August 2023

CCC Intelligent Solutions

Data Science R&D Intern

  • Successfully launched a ML prototype to production that solves the categorization of thousands of documents.

  • Successfully deployed a transformer based system for predicting collision descriptors from car crash images.

  • Successfully leveraged traditional and existing ML models to achieve a 98% accuracy in Customer Care Call categorization.

August 2020 - June 2022

Schneider Electric

Analyst

  • Achieved a 10 percent reduction in vulnerabilities by implementing cross-site scripting to prevent security issues and DOS attacks,  leveraging secure coding practices for successful implementation.

  • Successfully integrated User Interface upgrade with the backend of the entire application to ensure seamless functionality and enhanced performance.

  • Successfully implemented a last minute project required during the Ukraine-Russia global crisis to ensure company operations continue globally without compromising quality, delivered end-to-end product in two sprints.

January 2020 - May 2020

Schneider Electric

Intern

  • Successfully delivered a facial recognition and authentication system which was built on AWS leveraging AWS recognition APIs and integrated with the company database hosted on Salesforce.

  • Performed exploratory customer data analysis using Salesforce Lightning Reports and Dashboards to understand trends in customer data.

June 2019 - August 2019

KPIT Technologies

Intern

• Designed and implemented a deep learning system for real-time recognition of facial expressions and head

poses of drivers employing transfer learning training methods.

• Achieved an average system accuracy of 96%, executed system using Keras and OpenCV Python3 libraries

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