AI Engineering (BSE) + Wharton @ Penn · Building Varma LLC · Shipped Plateify to the App Store
I build data products end to end: model, backend, interface, ship. Most of my work sits where machine learning meets a real decision someone has to make.
Currently recruiting for Summer 2027 SWE / ML / Data internships.
- Plateify: maintaining the live iOS app; Android port in progress
- Allergen menu scanner: AI that flags likely-safe dishes from restaurant menus; exploring a path to restaurant-verified data
- Coursework: statistical computing in R (STAT 4050), engineering statistics (ESE 4020), dynamical systems (ESE 2100)
- Reading: human–AI decision-making and causal inference, ahead of a Spring 2027 research assistantship
Plateify: iOS · Live on the App Store
Connects what you eat to your mood and energy. No calorie counting.
Photo of a meal → Google Vision extracts ingredients → a pattern engine correlates foods against the user's own check-ins. The interesting part is the signal problem: the engine upweights infrequently-eaten foods that track with how someone feels and downweights foods that show up on good and bad days alike, then lets users run structured elimination tests to confirm what it surfaced.
Swift · Firebase · Google Vision AI · pattern detection
AgentDeck: Desktop LLM agent with approval gates
An Electron app hosting a Claude agent with four local tools: read file, write file, run shell, fetch URL. Built around a security boundary — the renderer has no filesystem or shell access, the main process holds the API key, and every destructive operation goes through an explicit user approval gate.
Electron · JavaScript · Anthropic SDK · IPC · tool use
Analyzed user email engagement in Snowflake to isolate the drivers behind an engagement drop, and turned the result into a recommendation the team could act on.
SQL · Snowflake · analytics
Languages: Python · SQL · Swift · JavaScript · R · Java
Data: Snowflake · pandas · statistical computing in R
Build:Firebase · Electron · Google Vision AI · Git · Claude Code
Interests: human–AI decision-making · causal inference · experimentation
Open to: Summer 2027 internships (SWE, ML, data) · research collaborations in human–AI decision-making
Penn '29, BSE in Artificial Intelligence + Wharton (uncoordinated dual degree)

