Data Science and Machine Learning, Making Data Driven Decisions, Massachusetts Institute of Technology Schwarzman College of Computing, 10/01/24, 02/01/25, https://www.mygreatlearning.com/eportfolio/advik-lall
Timeline
Software Engineering Intern
TipTop Technologies
03.2025 - Current
Software Engineering Co-Lead
RU BOTS
01.2025 - Current
AI Systems Trainer
OpenTrain AI
09.2024 - Current
Computer Science and Data Science -
Rutgers University
High School -
East Brunswick High School
Projects
Predictive Modeling for an eLearning Startup: Built predictive models to identify leads most likely to convert, using Random Forest, Logistic Regression, and XGBoost. Applied SMOTE for class balancing, GridSearchCV for hyperparameter tuning, and SHAP for model explainability. Leveraged Pandas, NumPy, Scikit-learn, and visualized insights with Matplotlib and Seaborn to inform business strategy.
Amazon Recommendation System: Developed a recommendation system using collaborative filtering (KNNBasic, SVD, CoClustering) on real Amazon datasets to recommend the best products to users.
MoodMart (In progress): Full stack e-commerce app that categorizes products by moods or feelings (e.g., "Cheer Me Up," "Relaxation," "Energy Boosters"). Leverages Sentiment Analysis (NLP) to analyze reviews and creates dynamic recommendations based on user surveys.