About Me
Skills
Based in the U.S. | Open to Relocating
I am a Computer Science and Data Science graduate with a strong focus on generative AI, machine learning, and data-driven systems.
My experience spans generative AI, machine learning, data analytics, and full-stack development, with hands-on work designing and deploying end-to-end systems. At Mayo Clinic, I built an AI-powered clinical question-answering system by integrating OCR, entity extraction, embedding-based retrieval, and LLM-based generation. Additionally I have worked on recommendation and personalization pipelines, applying ML and data-driven methods to improve content relevance and user experience.
I also enjoy volunteering and giving back to the community. I am a Campus Representative for the National Center for Women & Information Technology (NCWIT), where I connect with and support young women in STEM, helping them grow and stay confident in pursuing careers in the Tech Field. I also volunteer with North STEM Bridge, working with underrepresented K–5 students to teach foundational STEM concepts in fun and engaging ways.
I’m someone who loves learning, stays optimistic, and is very curious and determined. I value using my skills to make a positive impact beyond just code. I am currently seeking full-time roles in MLE, AI, or Software Engineering (AI-focused) and I am open to Relocate.
Experience In
Grounded GenAI (RAG)
Retrieval, context selection, and grounded generation to reduce hallucinations.
Applied ML + Evaluation
Metrics, baselines, error analysis, and iteration loops that improve real outcomes.
Document AI Pipelines
OCR → entity extraction → structured outputs for downstream search and QA.
Full-Stack Prototyping
React + Node for demos, dashboards, and productized ML workflows.
Experience & Education
Work Experience
Jun 2025 – Dec 2025
AI Engineering Intern (BioStatistian Department)
Mayo Clinic
Built a genomics-focused question-answering system integrating OCR, entity extraction, embedding-based retrieval, and LLM generation for grounded responses.
2024 – 2025
HCI Researcher (GenAI)
Group Lens Lab
Developed and evaluated a personalized news recommendation pipeline, experimenting with topic and locality calibration and designing GPT-Prompts to improve relevance while reducing over-personalization and filter-bubble effects.
Education
2022 – 2025
B.S. Computer Science + Data Science, Minor: Statistics
University of Minnesota – Twin Cities
Focused on ML systems, data analytics, and applied statistics. Built projects spanning GenAI, RAG, and data pipelines.
My Projects
Finance Tracker
Built a full-stack personal finance tracker using React, Node.js, and Express with MongoDB for data storage. Implemented CRUD functionality with real-time balance summaries and category-based expense breakdowns.
tDCS Treatment Response Prediction
Evaluated multiple brain connectivity representations and causal machine learning models (T-Learner, X-Learner, Causal Forests) to predict individualized treatment response from neuroimaging data.
RegEx Based Parsing
OCR-driven regex parsing system that transforms unstructured medical PDFs into structured JSON by extracting visa authorization, USMLE exam outcomes, and ECFMG certification data.
VPN-Based Remote Robotics Interface
Designed and deployed a site-to-site VPN enabling secure, reliable communication between autonomous robots and remote driver stations, supporting real-time operation and cross-team collaboration during testing and competitions.