Devansh Sanghavi

Junior at Los Altos High School. I build civic tech, research how AI models are evaluated, compete in math, and do robotics.

Projects

CivicPulse

App Store ↗ · Town Crier article ↗

Devansh receiving a Certificate of Appreciation for CivicPulse from the Rotary Club of Mountain View, with CivicPulse shown on the screen behind.
Receiving a Certificate of Appreciation for CivicPulse from the Rotary Club of Mountain View.

CivicPulse is a platform where Los Altos residents can report local infrastructure problems, upvote what matters most to them, and track whether anything gets resolved. Residents drop a pin, attach a photo, and submit a report in under a minute. The app has a live map of all active reports, community upvoting so the most urgent issues surface first, push notifications, and an admin dashboard for city staff. It was covered by the Los Altos Town Crier in April 2026 and is in active use with LAMVCF and the Rotary Club. The iOS app is live on the App Store.

React, TypeScript, Firebase, Leaflet.js, Tailwind CSS, iOS, Android

Multi-Output Gaussian Process Surrogate Model for NTD Drug Discovery

Project write-up ↗

Two line charts comparing MOGP against GP-MOBO, Random Search, Single-Objective BO, and a Greedy Filter across a multi-seed benchmark. The left panel plots hypervolume against the number of molecules evaluated, with MOGP reaching about 0.35 while the next best baseline reaches about 0.19. The right panel plots Pareto-front size against molecules evaluated, with MOGP finishing highest at about 50.
Hypervolume and Pareto-front size against molecules evaluated, MOGP compared with four baselines.

Drug discovery for neglected tropical diseases is underfunded and computationally expensive. Screening a billion compounds on a single processor core would take 475 years. Caleb and I are building a surrogate modeling pipeline that uses a Multi-Output Gaussian Process trained on molecular fingerprints to predict ADMET properties, meaning Absorption, Distribution, Metabolism, Excretion, and Toxicity, from a molecule's SMILES string alone. Rather than collapsing drug-likeness into a single score, the model treats human safety, absorption, and synthesizability as conflicting objectives on a Pareto front, and uses Expected Hypervolume Improvement to choose the next molecule to evaluate. The goal is to let underfunded NTD researchers skip expensive wet lab screening and go straight to a ranked list of promising candidates. We are validating the approach by simulating rediscovery of a known drug at a fraction of the documented cost and time.

Python, RDKit, GPyTorch, PyTDC, ChEMBL, scikit-learn

Carta

GitHub repository ↗

Carta's home screen, listing benefits notices as countdown cards. A red card reads 2 days left for a CalFresh renewal, an amber card reads 11 days left for benefits stopping, and a green card below shows 46.
Every notice becomes a countdown, colored by how little time is left.
Carta's plain words screen, showing an explanation of a CalFresh letter generated on the phone. A notice above it reads that Carta wrote this on this phone from the words in the photo, that it can be wrong, and that the original is below.
The on-device model's rewrite, labeled as machine written with the original letter kept below.

During the 2023-24 Medicaid unwinding, more than 25 million people lost coverage, and among states reporting a reason, KFF's tracker counts 69% of those disenrollments as procedural, meaning paperwork rather than a finding of ineligibility. They were already enrolled, so I am building Carta for retention rather than enrollment. A recipient photographs the renewal letter, a CalFresh SAR 7 or a Medi-Cal redetermination, and the app reads it on the phone, finds the deadline buried inside, and schedules reminders against it. Nothing on that path touches the network, enforced by a test that disables fetch, XMLHttpRequest, WebSocket, and the native bridge, verifies the sabotage really throws, then replays 79 recorded scans and fails on any attempt. A deterministic extraction cascade reaches 96.4% precision on core fields and 100% on every date the app schedules against, measured across 23 photographs shot in nine physical conditions rather than on clean synthetic text. An optional on-device Qwen2.5-1.5B model rewrites a notice in plain language at 1.3 seconds to first token and 37 tokens per second on an iPhone, held to a hand-written GBNF grammar, and it withholds any explanation citing a date the user has not confirmed. It runs in English and Spanish, though that rewrite still answers Spanish letters in English and is unfinished. Getting a model onto the phone at all meant a 4-bit quantization of Qwen2.5-1.5B down to about 1.1 GB, shipped as an optional download rather than bundled into the app, plus the iOS entitlements that let a process hold that much in memory. The grammar is the third design rather than the first. Constraining the shape of a date let through 00/00/0001, and a grammar with no production meaning "not stated" left the sampler no legal way to abstain, so on a notice with no deadline the model confidently emitted the notice date instead.

React Native, Expo, TypeScript, Apple Vision OCR, llama.rn, Qwen2.5-1.5B, Jest, iOS

Research Intern, Paper Lantern

Frontier models have effectively consumed the open internet as training data, and yet they still fall short on the tasks worth the most in our economy, the ones that need deep expertise, long term thinking, or taste. Closing that gap takes human judgement and verifiable outcomes, which is why benchmarks, arenas, and RL environments have grown into a multi billion dollar industry of their own. My work is a survey of that landscape. I am cataloguing which evaluation efforts exist, what model capability each one actually tests, how it collects human or verifiable judgements, and how it found an audience, including the ten or so that were built and never caught on. I map them along dimensions like domain, task complexity, and accessibility, meaning whether only a well funded lab can evaluate on it or whether an ordinary person can contribute. The point of the survey is to find a capability that is measurably weak, prove it with data rather than assert it, and then build the evaluation and training data that would improve it.

Benchmarks, arenas, RL environments, evaluation design, literature review

STEM Research Club

Instagram ↗

I run workshops at LAHS for students who want to do research and have no idea what the first step is. The barrier is not interest, it is that nobody teaches you how to identify what you want to study, how to read an academic paper, or what a cold email to a professor should say. The workshops cover exactly that, plus literature review and resume preparation, and more than 100 people have come through them. We also bring in guest speakers, so far all of them working in AI, including venture capital partners and people at large tech companies, each walking through the path they took. The eventual goal is to connect members with professors and research programs at nearby community colleges and state universities.

Workshops, guest lectures, paper reading, cold outreach, literature review, resume preparation

Kangaroo Atlas

kangarooatlas.com ↗ · GitHub repository ↗

Devansh leaning over a table of younger students working through Math Kangaroo practice problems, with worksheets and pencils spread across the desks.
Working through practice problems with students, the in-person program Kangaroo Atlas is built to serve.

Past papers tell a student the score, not which skill failed. I run a Math Kangaroo prep program for about 60 students a year. Most of that work is in person at the schools, sitting at a table with a group of kids and working a problem through out loud, and that room is where the program actually lives. We fix the problem a student missed, and the misconception underneath it survives to the next paper. Kangaroo Atlas is what I built instead. Every one of the 600 wrong answer choices stores the specific misconception that produces it, a rule the build enforces, so a score becomes a diagnosis rather than a number. Behind it sits a prerequisite graph over 91 named skills in 7 strands joined by 106 edges, so a miss on the adaptive diagnostic walks down to the skill underneath. I wrote all 150 problems myself, so no official Math Kangaroo question is ever reproduced, and each one carries a three step hint ladder and, where it needs one, a hand-drawn figure from a set of 25. Every one is hand written rather than generated or adapted, and each took a long sitting to analyze, because a problem is only worth including once it tests the skill it claims to test instead of rewarding a trick the student happens to have seen. Timed 75 minute mocks, per skill ladders, and printable worksheets whose answer key carries those explanations all run signed out, with no ads or trackers. It builds to 869 static pages behind 2,138 tests and 102 accessibility assertions, every one of them build-blocking. The goal is a free version of my program that another tutor can self host.

Next.js, TypeScript, Tailwind CSS, Zod, ts-fsrs, Vitest, axe-core, GitHub Actions

Voltage Drop

YouTube channel ↗

You cannot fabricate a chip in a garage, so I explain chip design out loud instead. Voltage Drop covers what is happening at the frontier of electrical engineering and computation: new ways to build a chip, new ways to move data between chips, and the hardware underneath the AI systems most people only meet at the software layer. Each episode is a roughly ten minute breakdown of one idea, built from the primary sources, the original paper and the vendor's own published specifications, rather than from other people's summaries, and it names the actual hardware. Episodes so far have covered living neurons grown on silicon and trained to play Doom, and photonic interconnect replacing copper in AI data centers.

Chip design, silicon photonics, biological computing, primary source research, YouTube

About

I'm a junior at Los Altos High School in Los Altos, CA. I tend to notice when something is not working, and I keep going until I understand why. That is roughly how CivicPulse started.

I kept walking past cracked sidewalks and broken streetlights around my neighborhood that nobody seemed to fix. It turned out there was no simple way for residents to flag those problems to the city, so I built one.

Right now I am a research intern at Paper Lantern, working with a team led by current Google DeepMind executives on how frontier AI models get evaluated. I spend my time mapping the landscape of benchmarks, arenas, and RL environments, figuring out what each one actually measures and why a handful of them became standards while most were built and then forgotten.

Outside of software, I mentor about 60 students a year in Math Kangaroo prep, compete on the VEX and FRC robotics teams, debate parliamentary for the speech and debate team, and run the STEM Research Club I started at LAHS. I make a podcast about chip design, and I have 200+ volunteer hours across the library, FCSN, and STEM outreach.

Highlights

A running record of the things I have competed in, built, led, or shown up for. The projects on the front page go into more depth.

Research

Research intern at Paper Lantern, working with a team led by current Google DeepMind executives on how frontier AI models are evaluated.

The work is a survey of that landscape, cataloguing what each benchmark, arena, and RL environment actually measures, how it collects human or verifiable judgement, and why a handful became standards while most were built and then forgotten.

Co-authoring a multi-output Gaussian process surrogate model for neglected tropical disease drug discovery, meant to let an underfunded lab skip a round of wet lab screening.

Math

4th place nationally in Math Kangaroo in 10th grade, and a multi-time national award winner.

Runs a Math Kangaroo prep program in its fifth year, teaching about 60 students a year, mostly in person at the schools. More than 30 have gone on to win national awards.

Built Kangaroo Atlas, the free and open source platform behind the program, around 150 hand written problems and a prerequisite graph over 91 named skills.

AMC 10 competitor.

Devansh helping a group of younger students work through Math Kangaroo practice problems at a classroom table.
Working through Math Kangaroo practice problems with students.
Robotics

VEX Robotics co-captain. Implemented inertial sensor integration so the autonomous routine held its heading instead of drifting off course.

FRC team member covering assembly, machining, and electrical work, and designed a spindexer, the rotating carousel that lines game pieces up one at a time.

Completed MIT Beaver Works "Basics of ASICs", covering digital logic and HDL chip design.

Civic Tech

CivicPulse covered by the Los Altos Town Crier in April 2026.

iOS app live on the App Store. Android submitted for review.

Active collaborations with LAMVCF and the Rotary Club, who gave CivicPulse a Certificate of Appreciation.

Building Carta, an on-device iPhone app that reads a government benefits letter and makes sure the deadline buried inside it is not missed.

Speech and Debate

Parliamentary debater and state qualifier, ranked in the top 100 teams in the country.

PR and social chair. Plans and advertises events across multiple schools, reaching 200+ students a year, and works on funding and the record of past results.

Community

Founded and runs the STEM Research Club at LAHS, which has taught 100+ students how to find a research interest, read an academic paper, and write a cold email to a professor.

200+ volunteer hours across the library, FCSN, and STEM outreach.

100 of those at the Los Altos Library, organizing and pulling books and running the sorting machine.

JV tennis league champions as team captain.

Skills

Each with the project it was used on.

Building and shipping apps

Full-stack mobile app development, shipped to the App Store (CivicPulse)

Cross-platform iOS and Android with React Native and Expo (CivicPulse, Carta)

Web development with Next.js and static site generation, deployed on Cloudflare (Kangaroo Atlas, this site)

Accessibility and internationalization, WCAG 2.1 AA and English with Spanish (Kangaroo Atlas, Carta)

On-device machine learning

Local LLM inference on iOS with quantized GGUF models (Carta)

On-device OCR and structured field extraction (Carta)

Grammar-constrained decoding to block hallucinated fields (Carta)

Hardware benchmarking of latency and throughput (Carta)

Surrogate modeling and Bayesian optimization

Multi-output Gaussian process surrogate models (MOGP)

Multi-objective Bayesian optimization with Pareto fronts and expected hypervolume improvement (MOGP)

Cheminformatics: molecular fingerprints, ADMET prediction, and docking validation (MOGP)

Benchmarking against baselines across seeds with held-out evaluation (MOGP)

Research and measurement

AI evaluation research across benchmarks, arenas, and RL environments (Paper Lantern)

Evaluation corpus design with real-world inputs and held-out sets (Carta)

Precision and recall reporting with minimum sample thresholds (Carta)

Multi-seed experiments with confidence intervals (MOGP)

Agentic coding

Directing AI coding agents across multi-month projects (Carta, Kangaroo Atlas, MOGP)

Project briefs with guardrails, settled results, and ruled-out approaches (all projects)

Reviewing generated code against spec and catching overclaims (all projects)

Research-grounded technical decision making (Paper Lantern)

Testing and quality

Large test suites as build gates, 591 and 2,100+ tests (Carta, Kangaroo Atlas)

Adversarial testing, including network isolation proofs (Carta)

Automated accessibility and contrast testing in CI (Kangaroo Atlas)

Continuous integration with typecheck, lint, test, and content validation gates (Kangaroo Atlas)

Security and privacy

Field-level AES-256-GCM encryption with hardware-backed keys (Carta)

PII redaction before persistence (Carta)

Privacy-by-design for minors and vulnerable users, no trackers or accounts (Kangaroo Atlas, Carta)

Postgres row-level security with pgTAP tests (Kangaroo Atlas)

Teaching and leadership

In-person tutoring of about 60 students a year with original curriculum (Math Kangaroo prep)

Workshop facilitation for 100+ students (STEM Research Club)

Parliamentary debate at state level and event organizing for 200+ across schools (Speech and Debate)

Technical communication for general audiences (Voltage Drop)

Languages and tools

TypeScript, Python, Java, SQL. React, React Native, Expo, Next.js. PyTorch, GPyTorch, BoTorch, RDKit, scikit-learn, pandas. Firebase, Supabase, Postgres, Cloudflare. Jest, Vitest, pytest, GitHub Actions, Claude Code.

Contact

Feel free to reach out about anything, whether it is CivicPulse, AI evaluation, the science fair project, math, or robotics.