Kritthika Shanmugam

Graduate student at City University of Seattle

About

I'm Kritthika Shanmugam, a Computer Science graduate student at City University of Seattle with a focus on full-stack development, AI, and data science. I have hands-on experience with technologies such as Python, Flask, TensorFlow, and React. My notable projects include Multi Factor authentication system, a CNN-based drowsy driver detection system, a high-precision fraud detection model, and a feature-rich React Native weather app. I've been honored on the Dean’s List for Fall and Winter 2023-2024 and secured 3rd rank in the Tamil Nadu state board exams. I am also studying data structures and solving problems on LeetCode to enhance my problem-solving and algorithmic skills.

    City: Kirkland, USA

Skills

  • Programming Languages:

    • Python, C++, C, SQL, R, HTML, CSS, JavaScript

  • Development Tools:

    • Jupyter, Git, GitHub, MySQL, NoSQL, Anaconda, VSCode, RStudio, Power BI, Docker

    Resume

    About Me

    Summary

    Education

    Master of Science in Computer Science - 2025

    GPA: 4.0

    City University of Seattle, Washington

    Full Stack and Web development(Mobile app), Artifical Intelligence for Data Science, Cloud Computing Overview, Programming for Computing, Machine Learning/Deep Learning,Software Engineering, Discrete Mth/Algorithms computing

    Bachelor of Engineering - Electronics and Communications Engineering - 2020

    GPA : 8.5

    Kongu Engineering College, Anna University

    Problem solving and programming(C Language), Object Oriented Programming(C++)

    Achievements

    Dean's List Honors

    Selected for the Dean's List at City University of Seattle for Fall 2023-24 and Winter 2023-24, recognizing academic excellence.

    Top 3 Rank in State Board Exams

    Achieved 3rd rank among one million students in the Class 10 Tamil Nadu state board exams.

    Project Experience

    A Secure Multi-Factor Authentication System Github link
    December 24

    Python, Flask, Flask-Bcrypt, SQLAlchemy, PyOTP, Docker

      Designed a Flask-based MFA system with secure password hashing, 30-second refreshing OTPs using PyOTP, containerized with Docker, and integrated Google Authenticator for reliable authentication, utilizing Flask blueprints and SQLAlchemy for modular architecture and secure database management.

    Drowsy Driver Detection Github link
    April 24

    Python, TensorFlow, VSCode

      Incorporated a CNN for drowsiness detection, boosting accuracy by 35% with data augmentation and implemented a 4-layer CNN for enhanced real-time eye closure detection.

    Credit Card Fraud Detection Github link
    January 24

    R, Kaggle Dataset, VSCode

      Implemented a Decision Tree model with 99.44% accuracy and an AUC of 0.886 for fraud detection, addressing class imbalance through undersampling to enhance precision and reliability.

    React Native Weather Application Github link
    January 24

    React native, API, Axios

      Built a React Native weather app with real-time updates, a 3-day forecast, and a dynamic GIF background to boost user engagement.

    Publications

    A Study on Detection of Tuberculosis From Chest X Ray Images and Microscopic Images Based on Deep Learning Techniques Link


  • Developed CNN models with MATLAB, achieving accuracies of 91.89% for tuberculosis detection and 94.48% for COVID-19, surpassing traditional SVM methods.
  • Implemented advanced techniques such as morphological opening and GLCM for improved noise reduction and texture feature extraction in X-ray images.