Melissa Rajamanuvel

Education

University of Wisconsin - Madison

Sept 2024 - Dec 2025

Transitioned to UW Madison for a Bachelor’s in Data Science after St. Thomas.

University of St Thomas - St Paul, MN

University of St. Thomas

Sept 2021 - May 2024

Bachelor’s in Data Analytics with Economics, achieving Dean’s List honors.

My Projects

Showcasing innovative projects and entrepreneurial endeavors in technology.

Tecaran Startup

Founder of Tecaran, a startup project since September 2024.

Smart Headphones with Vlogging Camera - Preorder Now! | Tecaran

AI Prediction

Developed air quality index prediction using machine learning techniques.

March 2024 - May 2024

Hotel Cancellations

Predicting cancellations for hotel bookings from October to December 2023.

Optimizing Safe Routes for Pedestrians at Night

Initiating Safe Walk project from March 2025 to present.

• Developed an AI-powered safety device using computer vision (OpenCV) on Raspberry Pi for real-time threat detection

• Built a companion iOS mobile app using Xcode, integrated with Firebase and Google Maps API for GPS tracking and SMS alerts

• Engineered hardware integration by configuring sensors, SMS modules, and camera modules.

• Deployed cloud-based machine learning models for real-time image processing and alert generation

Skills used: Python, OpenCV, Swift, Firebase, Raspberry Pi, API integration

• Built a neural network model to predict a city’s Air Quality Index (AQI) using AQI data from nearby cities

• Collected, cleaned, and structured environmental data for model training

• Applied machine learning techniques to evaluate performance and improve prediction accuracy

• Used libraries such as scikit-learn, pandas, and matplotlib for modeling, data preprocessing, and visualization

Skills used: Python, neural networks, scikit-learn, pandas, matplotlib, data preprocessing, regression modeling

• Developed a Random Forest model in R to predict hotel booking cancellations

• Cleaned the dataset and split it into training and testing sets for model evaluation

• Assessed model performance using a confusion matrix and accuracy metrics

• Analyzed and visualized feature importance to identify key drivers of cancellations

Skills used: R, Random Forest, caret, dplyr, ggplot2, data preprocessing, EDA, classification modeling, model evaluation

• Developed a linear optimization model to identify the safest nighttime walking routes using street lighting and sidewalk network data

• Modeled the problem as a min-max shortest path, minimizing the darkest segment while ensuring the path remains reasonably short

• Integrated real-world geospatial datasets from the City of Madison, including streetlight intensity and pedestrian path maps

• Planned a sensitivity analysis using duality to evaluate the impact of lighting constraints on optimal path selection

Skills used: Linear programming, optimization modeling, Julia, JuMP, sensitivity analysis, duality, data preprocessing

Skills

Data Analysis & Modeling Skills

• Data Analyst Tools: Excel, Minitab

• Data Visualization: ggplot2, pivot table, Power BI

• Modeling Techniques:

  • Neural Networks, Logistic Regression, Linear & Multiple Regression

  • Forecasting, Predictive Modeling, Principal Component Analysis (PCA)

  • K-Nearest Neighbors (KNN), Structural Equation Modeling

  • Computer Vision

Optimization & Mathematical Modeling

Optimization Models:

• Linear Programming

• Shortest Path Algorithms

• Transportation Problem

• Assignment Problem

• Network Flow Optimization

• Trade off Optimization

Programming & Technical Skills

• Languages & Tools: Python, Julia, Java, R

• Version Control & DevOps: GitHub, GitLab

• Platforms: Development in Ubuntu environments (VM & Raspberry Pi)

• API Development: REST API integration, hardware-software interfacing using Flask

• Python libraries: scikit-learn, TensorFlow, matplotlib, pandas, Pytorch