About Me

I am a graduate student pursuing Masters of Science in Computer Science at The University of Illinois, Chicago. My area of interest/ I am interested in exploring the fields of are Software Engineering, Full-Stack Development, Machine Learning and I am open to opportunities for the same.

Languages

Languages for systems programming, web automation, and data analysis.

Front-End

My preferred technologies for front-end web development and component design.

Back-End

My preferred technologies for back-end web programming and database architecture.

Frameworks

Frameworks I use for web and mobile app development.

Tools

My favorite tools for version control, code editing, and container orchestration.

DEEP SEE CRIME

An AI Based Crime Monitoring System

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Symptoms based disease prediction

Using decision tree and electronic health record analysis

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Real-time spontaneous abortion prediction and detection

IoT and Machine Learning

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Silent-horn

A smart web app for hearing impaired people

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Atrocity Case Management and Monitoring

Enhance the documentation, management, and monitoring of atrocity cases

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The University of Illinois at Chicago - Masters of Science in Computer Science

Jan 2021 – Dec 2022(expected)

Coursework: Computer Algorithms, Introduction to Machine Learning, Introduction to Mobile Application.

Anna University, India - Bachelors of Engineering in Computer Science and Engineering

June 2016 – May 2020 CGPA: 8.70/10

Coursework: Design & Analysis of Algorithm, Operating System, Internet Programming, Software Engineering, Computer Architecture, Cloud Computing, Database Management Systems, Artificial Intelligence.

Software Engineering Intern at Ethna Attributes Pvt Ltd | May - July 2019

Developed a predictive health monitoring android application that analyses parameters from a user's smart band by leveraging IoT and Machine Learning. Established a firebase connection with the application that periodically displays alert pop-ups.

Research Assistant at Anna University | Nov 2018 – May 2019

Pre- processed the Graft data and analysed across different machine learning models. Trained Bayesian Belief Network & Fuzzy Logic model for prediction of graft survival.