Pranay Narula
I Build ML Algorithms
Undergraduate Student | Machine Learning Enthusiast
Started Coding
Age 13 (2018)
Discovered the world of programming and wrote my first lines of code
ML Journey Begins
Age 15 (2020)
Started learning machine learning and built my first neural network
Startup Journey
Age 17 (2023)
6 months of algorithm development, 2 months of prototype building
- Algorithm Development (6 months)
- Prototype Building (2 months)
Work Experience
Team Lead Intern
Redvest
January 2025 - Present
- Supporting data-driven decision-making through statistical analysis and data visualization.
- Collaborating with cross-functional teams to identify trends and actionable insights in the UI.
- Working with large datasets to provide actionable solutions for growing revenue
AI Safety Fellow
Uconn Beacon AI
September 2024 - November 2024
- Engaged in in-depth paper reviews, including implementations and activities centered around AI safety and ethical considerations.
- Collaborated with peers and mentors on understanding the overarching risks of AI and mitigating them
- Developed an understanding of safety protocols and frameworks applicable to machine learning and AI models.
InterviewAI Intern
InterviewAI
May 2024- August 2024
- Developed v0 of InterviewAI Async, a B2B SaaS for InterviewAI using NextJS, OpenAI, and Supabase
- Developed the entire payment integration and subscription system using hooks and Stripe
- Gained hands-on experience in transforming user specifications into code, and writing good copy
Education
Bachelor of Science in Computer Science
Concentration: Algorithms
University of Connecticut, Storrs, Connecticut
2024 - 2028
Relevant Coursework
Featured Projects
FelicityAI - Startup for Efficient LLM Fine-Tuning using Explainability
FelicityAI helps fine-tune large language models (LLMs) by leveraging an explainability algorithm designed implemented and tested by me. It determines the contribution percentages of different categories in datasets, enabling better insights and improved model performance.
ASL Teacher Using Image Recognition and Spaced Repition built for HackMHS
Learn ASL using spaced repition through a convolutional Neural Network
Adversarial Attacks on Face Recognition (Hackathon Winner)
Implemented a Projected Gradient Descent (PGD) adversarial attack on facial recognition systems using the FaceNet model to demonstrate vulnerabilities in high-security environments like airports.
Skills
Machine Learning
- Neural Networks
- Deep Learning
- Computer Vision
- NLP
Programming
- Python
- PyTorch
- TensorFlow
- scikit-learn
Tools
- Git
- Docker
- Linux
- Jupyter
Math & Stats
- Linear Algebra
- Calculus
- Probability
- Statistics