Transforming raw data into meaningful insights by applying machine learning and deep learning methods to uncover patterns and drive informed decisions.
Data Science Sophomore from DJ Sanghvi Mumbai with a strong interest in machine learning and software development.
Skilled in Python with hands-on experience in applying machine learning and deep learning models to real-world problems. Focused on using AI to uncover insights, support data-driven decision-making, and improve business outcomes through smart, efficient solutions.
Sept 2024 - Present
Bachelor of Technology degree - CSEDS 9.235/10.00
Subjects: Algebra, Statistics, Algorithm Programming, Database, Machine Learning, Deep Learning, NLP, Data Mining, Big Data
Harvard University
DeepLearning.AI
Amazon Web Services (AWS)
Harvard University
Harvard University
Academic Projects & Technical Implementations
2025
Implementation of a Breadth-First Search Algorithm to find the degrees of separation between two selected actors, by films they have starred in.
Achievement: Finds shortest actor connection paths through film collaborations using BFS graph traversal.
2025
Implementation of a Tic Tac Toe AI using a Minimax Algorithm with Alpha-Beta pruning. Randomisation varies the AI's moves where several have equal utility.
Outcome: Built an unbeatable AI opponent using minimax algorithm with alpha-beta pruning optimization.
2025
An AI that plays the classic Windows 'Minesweeper' game, using a knowledge base and inference to generate new knowledge about the game state.
Result: Built an AI that solves Minesweeper using logical inference and knowledge base reasoning to identify mines and safe cells.
2025
An AI that ranks web pages by importance - similar to the Google PageRank AI - using both a Random Surfer Model and an Iterative Algorithm.
Impact: Implemented Google's PageRank algorithm using both Markov Chain sampling and iterative methods to rank web pages by importance.
2023
An AI that generates crossword puzzles, by treating the crossword generation as a constraint satisfaction problem and using a backtracking search algorithm.
Achievement: Built an AI crossword generator using constraint satisfaction with node consistency, arc consistency, and backtracking search algorithms.
2025
An AI that predicts whether online shopping customers will complete a purchase, using the Scikit-Learn k-Nearest Neighbour classifier on a customer dataset.
Result: Developed a machine learning classifier to predict customer purchase intent with sensitivity and specificity metrics using k-nearest neighbors.
2025
An AI that teaches itself to play the game 'Nim' using Reinforcement Learning. A Q-Learning algorithm with ε-Greedy Decision Making is used to estimate the value of actions for game states.
Achievement: Created a self-learning AI that masters Nim through reinforcement learning using ε-greedy Q-learning algorithm.
2025
An AI that identifies which traffic sign appears in a photograph, using a TensorFlow convolutional neural network.
Impact: Built a convolutional neural network to classify 43 different German traffic signs with high accuracy using TensorFlow and OpenCV.
2025
An AI that can parse sentences and extract noun phrases, using the context-free grammar formalism and the Python nltk library.
Outcome: Developed a natural language parser that extracts noun phrases from English sentences using context-free grammar and NLTK.
2025
An AI that answers questions, by determining the most relevant document(s) using tf-idf ranking and then extracting the most relevant sentence(s) using idf and a query term density measure.
Achievement: Built a question-answering system that retrieves relevant documents and extracts answers using TF-IDF ranking and query term density analysis.
I am open to any collaboration opportunities.
Mumbai, India