Co-Founder
Dec 2024 - Current
HTML, CSS, Javascript/Typescript, Git, Vercel, Supabase, many APIs
UnitNode is the first real estate operations software that replaces outsourced property management with automation and simplicity for owners, helping them increase rental income margins, boost efficiency, and regain control of their portfolio effortlessly.
As a co-founder, I’ve helped ship nearly every core feature from building the end-to-end workflows for properties, leases, bills, and payments to refining the UI/UX across the product and marketing site. I’ve implemented payments and billing with the Stripe API and built automation features like translated tenant alerts and email/document parsing that turns incoming utility emails into structured tenant bills with due dates. I’ve also contributed across the stack on database UI/UX design, normal/Google authentication, integrations, testing/bug fixes, and deployment—doing whatever the product needed to move faster and stay simple.
Research Scholar
Jun 2025 - Jul 2025
Python, Pytest, Git, LaTex, Figma
Accepted as a Scholar among the top 64 of New Jersey high school students with a less than 1% acceptance rate. Completed coursework in Modern Physics, Robotics, Sustainable Energy, and AI/ML Engineering.
As an NJGSET Scholar, I built a Python-based emotional support assistant using the Gemini API, designed to simulate conversations with specific individuals by grounding responses in publicly available information (e.g., LinkedIn profiles, biographies, and portfolios). I also helped develop the initial 15-page paper, “TaintMonkey: Dynamic Taint Analysis of Python Web Applications Using Monkey Patching,” published in the NJGSET Research Paper Archive and presented at the NJGSET 2025 Symposium (Later presented at MIT URTC 2025, Published in IEEE Xplore).
NJ Governor's School of Engineering and Technology 2025 Publication →
Data Analyst Intern
Jun 2024 - Sep 2024
Python, Appfolio, Rent Manager, Google Sheets
Built a database of 1,160+ properties across New Jersey and Pennsylvania, then developed an OpenAI API–powered analyzer to process Philadelphia Water Department billing reports and cross-reference month-by-month data for accuracy (filtering outliers) to uncover water-bill cost anomalies at scale. Using these insights, I partnered with local contractors to upgrade outdated utility systems and implement low-waste solutions in 12 Philadelphia homes with the highest water costs.
GitHub Pages
