Tanya Nair

First-year undergraduate at Johns Hopkins, double-majoring in Electrical and Computer Engineering. Passion for applying cutting-edge AI and emerging technologies to problems spanning medicine, accessibility, and more. Interested in making a sustainable, accessible, AI-enhanced future.

Core Skills

• Languages: C, C++, Python, Java
• Frameworks: PyTorch, TensorFlow, HF Transformers
• Systems: Linux/UNIX, Git, Docker, Cloudflare Workers, Render
• Focus Areas: Sustainable Systems, Accessibility Tech, Healthcare & Surgical AI, Resource Optimization

My Areas of Interest:

• RAG and Knowledge-Grounded LLMs
• Energy- and Resource-Efficient AI Systems
• Multilingual and Cross-Cultural Language Models/Information Flows
• Societal, Ethical, and Accessibility Impacts of AI
• LLM Reliability & Security: Hallucinations, Robustness, and Data Privacy

Current Experience

• Johns Hopkins Center for Language and Speech Processing: Working with Prof. Ziang Xiao and Nikhil Sharma to build a benchmark for multilingual LLM outputs to queries. Continuation of work by Sharma, et. al..
• ARGOS Research Lab: Transparency Gaps in Surgical LLM Research, Geospatial Disparities in Community Opportunity Metrics: A Data-Driven Framework for Equitable Surgical Resource Allocation
• University of WA: Working on an automated pipeline to enhance accessibility of .pptx presentations for vision-impaired students. Presenting at EDUCAUSE 2025.

Past Experience

• Dartmouth Health: Built a RAG model for clinician cross-referencing of pathology reports with fusion vector search (Okapi BM25 and FAISS), implemented Microsoft's phi-2 for efficiency. Link to project portfolio website here.
• Published Research: Natural Language Processing used in sentiment analysis of poetry: a study of six common techniques
• Won Hackathons: HopHacks (1st Place Data Visualization Track), HackPNW (Best Use of Sponsor's API - Twilio)

Additional Projects

• Startup (in progress): Building a research-informed life analytics platform.
• Reading: 30 books this year!
• YouTube channel: Posting about AI & linguistics once a month (in an ideal world).