I am interested in software engineering, machine learning, and artificial intelligence. My goal is to leverage technology to make impactful contributions to the CS industry and society. Looking forward to connect with fellow peers and industry professionals!

University of California, Los Angeles (UCLA)
Master of Science in Data Science Engineering March 2026 – Present

San Diego State University (SDSU)
Bachelor of Science in Computer Science
Minor in Business Administration
August 2022 – December 2025

• Languages: Python, Java, C++, C#, .NET, MATLAB, Haskell, Prolog, MIPS, R, SAS, Swift
• Web Development: Javascript, React, Node.js, HTML, CSS, Web API, Spring Boot, Flask, Jinja, Streamlit, Bootstrap
• Data Science & Machine Learning: Pandas, NumPy, Scikit-Learn, TensorFlow, Pytorch, Keras, Matplotlib, Seaborn, HuggingFace
• Databases: SQL, SQLite, PostgreSQL, MongoDB
• Cybersecurity: Unix, Linux, Splunk
• Cloud: AWS (Bedrock, S3, SageMaker AI, Lambda, API Gateway, IAM, Textract, EC2), GCP (BigQuery), Azure (Virtual Machines)
• Tools: VSCode, IntelliJ, CLion, Jupyter Notebooks, Google Colab, Git, Github, Apache Kafka, Unity, Tableau, Dynatrace, Jira, Confluence, Microsoft Office (Word, Excel, Powerpoint, Access)
• AI-assisted Development Tools: Cursor, Claude, Copilot, Codex

1. Wireless Mobile Subscriber Churn Prediction Model and Generative AI Chatbot

• Built a supervised ML/DNN model that predicts the wireless mobile subscriber churn with 97.17% accuracy using network location, network usage (voice/data), billing and customer service data.
• Created a generative AI/BI (RAG to SQL) chatbot to help answer natural language analytic queries on the predicted dataset.
• Tools: Python, Scikit-learn, TensorFlow, Matplotlib, Streamlit, Google Colab
• Learnings: exploratory data analysis, machine learning, RAG, Text-to-SQL

2. WiDS ADHD Pattern Regression

• Developed a multi-output regression model to predict ADHD diagnosis and participant sex using functional MRI and socio-demographic data, achieving an F1-score of 0.75 for ADHD prediction.
• Achieved 3rd place among UCLA Break Through Tech AI teams in the Women in Data Science Datathon 2025.
• Tools: Python, Scikit-learn, Pandas, NumPy, Matplotlib, Google Colab
• Learnings: exploratory data analysis, machine learning

3. AWS Document Compliance

• Designed and implemented a solution to automate document compliance checks by identifying missing key information.
• Won 'Most Impact Potential' at the LPL Financial Hackarama 2025, competing against 43 teams and 137 participants from 6 universities to deliver a high-impact solution.
• Tools: AWS Textract, AWS Lambda, AWS S3, Python
• Learnings: cloud, text extraction, serverless execution, scalable storage

4. Data Dashboard

• Designed an interactive data dashboard, allowing users to visualize and explore data about characters from The Amazing Spider-Man series using dynamic charts, graphs and real-time filtering and sorting features across 2736 comics.
• Tools: Javascript, React, HTML, CSS, Web API
• Learnings: frontend development, data visualization, API integration

5. On The Fly

• Engineered a full-stack web application that provides users with a seamless interface for planning trips and organizing destinations using robust data management and server-side logic in order to streamline travel planning.
• Allows users to plan trips and add destinations related to the trip.
• Tools: PostgreSQL, Express, React, Node.js, Javascript, HTML, CSS, Railway
• Learnings: full-stack web development, relational database, CRUD operations, dynamic data visualization

6. Cognizant Gen AI Externship

• Applied Python and generative AI techniques across projects involving GPT‑2, BERT fine‑tuning, and BigGAN image synthesis; built text completion apps, explored prompt tuning, and evaluated model outputs for coherence, bias, and factuality.
• Tools: Python, Scikit-learn, Hugging Face, OpenAI GPT-2, BigGAN-deep-256, BERT
• Learnings: generative AI, LLM applications, prompt engineering

7. Fish On! 2D Game

• Designed and developed an arcade-style fishing game where players cast a line, reel in fish, and earn points within a timed session featuring varied fish behaviors, speeds, and point values.
• Tools: Unity, C#, TextMeshPro, Animator, Audio Source
• Learnings: 2D-game development, animation, event-driven scripting

• Email: meghanajkillada@gmail.com
• LinkedIn: linkedin.com/in/meghanakillada