Hi! I am an incoming graduate student at Yale University, pursuing a M.S. in Computer Science.

My interest lies in leveraging natural language processing (NLP) to improve question answering systems and the analysis of textual data. I am particularly interested in exploring how large language models (LLMs) can enhance educational experiences and facilitate knowledge acquisition, as well as provide valuable insights from financial documents and legal reports.

I am also passionate about web development and have experience with various full-stack technologies. My applications have amassed 30k+ users.

Outside of CS, I love to play sports, watch movies, and listen to music.

🔥 News

• 04/24: Interning at DUMAC (Duke Management Company) this summer
• 03/24: Attending Yale in the fall
• 12/24: Check out INTERACT on arXiv
• 09/24: Nominated Phi Beta Kappa (ΦΒΚ)

💼 Experience

• 05/25 - 08/25: DUMAC, Engineering Intern
• 6/24 - 05/25: COMP 210/211/311, Teaching Assistant
• 07/23 - 05/25: Learning from Language Lab, Research Assistant
• 06/24 - 9/24: MURGe Lab, Research Intern
• 06/23 - 07/23: Launch Chapel Hill, Summer Cohort

📝 Publications

• ACL 2025 Submission INTERACT: Enabling Interactive, Question-Driven Learning in Large Language Models
  • Aum Kendapadi, Kerem Zaman, Rakesh Menon, Shashank Srivastava
  • This paper explores how LLMs can transition to interactive, question-driven learning through student-teacher dialogues. (arXiv)

👨‍💻 Projects

Classmate

• Schedule classes with friends
• Helping over 30k students at over 10 schools
• Built with React, Firebase, Mixpanel

Waffle

• Chat with YouTube videos
• PennApps 2023 w/ Arvindh Manian, Billy Pan
• Built with LangChain, Whisper (OpenAI), FastAPI

Verdit

• Use AI to evaluate your AITA stories.
• Built with React, Together.ai

uncGuessr

• Guess where photos were taken at UNC
• Built with Angular, MongoDB, Express.js

Tunetones

• Create album cover color palettes
• Built with Vue

• Spotifind: Generate ML music recommendations - Vectorize feature sets of playlists created using TF-IDF and OHE then find similar songs using the KNN algorithm - Built with Scikit-Learn
• Twitiment: Analyze the sentiment of tweets using NLP - Analyze the sentiment of tweets using VADER and RoBERTa NLP models, as well a DistilBERT Hugging Face Pipeline - Built with NLTK, Hugging Face
• Wikipath: Find (the shortest) paths between Wikipedia articles using bidirectional search - Built with Flask, PyVis
• Digitect: Teach a computer to read handwriting - Use the MNIST dataset to train a homemade neural network to recognize digits - Built with NumPy
• Fractastic: Create Markovian Lindenmayer systems - Combine L-systems and Markov chains to produce stochastic fractals - Built with p5.js
• Flowscape: Simulate fluid movement with Perlin noise on vector fields - Built with p5.js
• Enigma: A basic model of an Enigma machine with plugboard, starting position, and ring functionality
• Vigenere: A Vigenere cipher with two decryption tools: a brute-force dictionary attack, and a kasiski examination which uses n-gram character repetitions in large text samples to conduct frequency analysis

📚 Education

• Spring ‘26: Yale University
  • M.S. Computer Science
• Spring ‘25: University of North Carolina at Chapel Hill
  • B.S. Computer Science
  • Highest Distinction, Phi Beta Kappa
  • GPA: 3.9
• Summer ‘24: DIS Copenhagen
  • Study Abroad
  • Coursework: Computer Organization (and Architecture)
• Spring ‘22: Providence High School
  • High School Diploma
  • Dual Enrolled at Central Piedmont Community College
  • GPA: 4.7