Currently an Extern @Pfizer
I'm a junior at Northeastern University, eager to enhance my skills and competitiveness in tech.
Dive into my work showcasing my growing skills in computer science and AI, developed through hands-on experiences.
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Pfizer · ✅ Verified by Extern · ⏱️ In progress
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
Building a serverless full-stack application to analyze journal entries and detect emotional patterns over time using AWS. Designed DynamoDB schema optimized for time-based querying of user entries and trend analysis. Implemented initial API endpoints using AWS Lambda and API Gateway for journal submission and retrieval. Integrating AWS Comprehend for sentiment analysis and developing a custom pattern detection engine to identify mood trends and recurring themes. Developing weekly aggregation workflows to generate personalized reflection summaries and insights. Creating an interactive dashboard using React to visualize mood trends and surface user-specific insights.
I'm a junior at Northeastern University, eager to enhance my skills and competitiveness in tech.
I'm a junior at Northeastern University pursuing a Bachelor's Degree in Computer Science. Currently, I'm deepening my skills through an externship at Pfizer, focused on AI-powered document insights and data extraction.
Externships
Pfizer Advanced: AI-Powered Document Insights & Data Extraction Externship
Pfizer
Experience
Software Development Co-op
Stealth Internship · January 2026 - Present
Software Development Intern
Stealth Internship · July 2025 - November 2025
Education
Northeastern University, Khoury College of Computer Science
Bachelor of Science in Computer Science, Concentration in AI · Class of 2027
Skills
✅ Verified by Extern · ⏱️ In progress
Prototype AI-powered document intelligence with Pfizer—using OCR, LLMs, and RAG to automate real enterprise PDF workflows and build a standout portfolio project.
The externship prototyped AI document-insight pipelines combining OCR, vector retrieval, and large language models to extract and synthesize information from pharmaceutical PDFs. The work surveyed model architectures and system components and produced implementation artifacts for automated data extraction and generative Q&A. The deliverables included a written description of LLM concepts and an
I produced a detailed description of LLM concepts and a step-by-step workflow mapping covering tokenization, embeddings, transformer processing, attention weighting, probability scoring, and iterative token prediction.
I described LLM concepts and workflow. I defined tokens, tokenizers, embeddings, transformers, and attention, then outlined the LLM process from input tokenization through embedding, transformer processing, attention weighting, probability scoring, and iterative token prediction.
Building a serverless full-stack application to analyze journal entries and detect emotional patterns over time using AWS. Designed DynamoDB schema optimized for time-based querying of user entries and trend analysis. Implemented initial API endpoints using AWS Lambda and API Gateway for journal submission and retrieval. Integrating AWS Comprehend for sentiment analysis and developing a custom pattern detection engine to identify mood trends and recurring themes. Developing weekly aggregation workflows to generate personalized reflection summaries and insights. Creating an interactive dashboard using React to visualize mood trends and surface user-specific insights.
Built a full-stack platform to streamline co-op application workflows for students and administrators. Integrated role-based dashboards and DEI analytics using Streamlit, Flask, and MySQL. Developed and deployed the system using Docker & Docker Compose, integrating sample data and ensuring scalable, containerized deployment. Designed a relational schema with 10+ tables modeling students, employers, applications, and advisors. Built admin dashboards to track placement trends and DEI statistics for data-driven decisions.