I'm a dedicated Computer Science graduate student at Northeastern University, on track to complete my Master's degree in December 2025. My journey began in Electrical and Electronics Engineering, but my passion for software development and data engineering led me to transition into the world of Computer Science. This unique background allows me to approach problems with a multidisciplinary perspective, combining hardware knowledge with software expertise.

• Degree: Master of Science in Computer Science
• Expected Graduation: December 2025
• GPA: 3.8/4.0
• Key Coursework:
  • Algorithms and Programming Design Paradigm

• Degree: Bachelor of Engineering in Electrical and Electronics Engineering
• Graduation: April 2021
• CGPA: 7.7/10
• Key Coursework:
  • Data Structures and Algorithms
  • Object Oriented Programming
  • Design Patterns and Principles

• Programming Languages:
  • Python (Advanced)
  • Java (Intermediate)
  • JavaScript (Intermediate)
• Web Development:
  • Frontend: React, HTML5, CSS3
  • Backend: Flask
• Data Engineering & Big Data:
  • Apache Kafka
• Cloud Platforms:
  • Amazon Web Services (AWS)
  • Microsoft Azure
• Databases:
  • Relational: MySQL, PostgreSQL, SQLite
  • NoSQL: MongoDB
• DevOps & Tools:
  • Version Control: Git and GitHub
  • CI/CD: Jenkins
  • Project Management: Jira
  • API Testing: Postman
  • Automation: Selenium
• Data Analysis & Visualization:
  • NumPy, Pandas
  • Matplotlib, Seaborn
• Machine Learning:
  • Scikit-learn
  • TensorFlow
  • Convolutional Neural Networks (CNN)

• Technologies: Python, Flask, React, Google's Gemini AI, SQLite, MongoDB
• Description: Developed a web application that leverages AI to transcribe, summarize, and enable Q&A for YouTube videos.
• Key Features:
  • Integrated Google's Gemini AI for advanced natural language processing
  • Implemented a Flask backend with RESTful API endpoints
  • Designed a responsive React frontend for seamless user interaction
  • Utilized SQLite for user data storage and MongoDB for efficient chat data management
• Outcome: Enhanced content accessibility and user engagement for video content

• Technologies: Apache Kafka, AWS (S3, Athena, Glue), Python, SQL
• Description: Engineered an end-to-end data pipeline for processing real-time stock market data.
• Key Components:
  • Utilized Apache Kafka for high-throughput, fault-tolerant data streaming
  • Implemented data flow from Kafka to AWS S3 for durable storage
  • Configured AWS Glue Crawler for automated schema detection and cataloging
  • Leveraged AWS Athena for SQL-based data analysis on S3 data
• Outcome: Enabled real-time processing and analysis of stock market data, facilitating informed decision-making

• Technologies: Python, TensorFlow, Convolutional Neural Networks
• Description: Developed a machine learning model to distinguish between malaria-infected and uninfected cells.
• Key Achievements:
  • Achieved 88.06% accuracy on the test set
  • Trained the model on a small dataset of 550 images, demonstrating effective use of limited data
  • Implemented data augmentation techniques to enhance model generalization
• Impact: Contributed to the development of automated diagnostic tools for malaria detection

• Technologies: Python, Scikit-learn, Pandas, Matplotlib
• Description: Built a machine learning model to identify fraudulent credit card transactions.
• Key Features:
  • Implemented logistic regression algorithm for binary classification
  • Conducted extensive Exploratory Data Analysis (EDA) on a dataset of 284,807 transactions
  • Achieved 92.89% accuracy in classifying fraudulent transactions
  • Identified key traits of fraudulent transactions, including timing and amount patterns
• Outcome: Developed a robust model for early detection of credit card fraud, enhancing financial security

Position: Associate Software Engineer Duration: October 2021 – December 2022

Key Responsibilities and Achievements:

• Developed and maintained comprehensive testing documents, enhancing project transparency and stakeholder collaboration
• Executed over 500 test cases using Python, Selenium, and Pytest, achieving 87% test coverage for critical functionalities
• Identified and reported more than 100 defects in JIRA, significantly improving software quality and user experience
• Leveraged Python programming and Jenkins for automation and CI/CD pipelines, resulting in an 18% reduction in testing time
• Generated detailed Pytest reports to facilitate efficient identification, troubleshooting, and resolution of technical issues
• Collaborated with cross-functional teams to identify and prioritize focus areas for upcoming sprint cycles, ensuring alignment with project goals and outcomes

• Roux Hackathon: Secured runner-up position and $500 prize for developing Maine Quest, an AI-driven tourism platform
• Start Summit - Decarbonizing the Built Environment: Achieved runner-up position and $1000 prize for presenting a sustainable construction model.
• Start Summit: New Mainer Inclusivity: Secured runner-up position for proposing InclusiLang, a company utilizing AI to provide language interpreters for New Mainers. The mobile app connects New Mainers, particularly from the Democratic Republic of the Congo, with AI and immediate interpreters to assist with everyday needs such as banking, documentation, and healthcare challenges.
• Google Data Analytics Professional Certificate
• IBM Data Science Professional Certificate

• Email: tharanimtharan@gmail.com
• LinkedIn: www.linkedin.com/in/tharanitharanm
• Portfolio: www.tharanitharan.com/
• Phone: +1 (207)-332-4078

I'm always open to interesting projects and collaboration opportunities. Feel free to explore my repositories and reach out if you'd like to connect or discuss potential collaborations!