AS
110/150NEETCODEROADMAP IN PROGRESS73% complete · 40 to go
SYSTEM DESIGN (HLD)CORE TOPICS · IN-DEPTH UNDERSTANDING
NETWORKINGCAP + HASHINGSCALABILITYSQL / NOSQLCACHINGMICROSERVICESFAULT TOLERANCEKAFKA + RABBITMQSECURITYCASE STUDIES
My goal · in work and in life

Jack of all trades Master of all trades.

PORTFOLIO_OS / 1.0HELLO, I'M ADVIT.

My goal, in life and at work, is to keep learning across every domain I enter—and keep going until versatility becomes mastery.

ADVIT
SINGH
SOFTWARE ENGINEER
OPEN TO SOFTWARE ENGINEERING ROLES

CLICK THE KEYS
OR USE YOUR KEYBOARD

UCR / 2027

Systems · Applied AI · Full Stack

Scroll to explore ↓
EXPERIENCERIVERSIDE, CALIFORNIA
MAY 2026 — PRESENT

Embedded Systems Intern

UC RIVERSIDE · COMPUTER SCIENCE

I build Rust and C firmware for a real-time brain-computer interface. Want the low-level receipts? My résumé has them ↗

OKAY, THAT'S THE TECHNICAL VERSION. BUT YOU KNOW WHAT MY RÉSUMÉ LEFT OUT—AND WHAT I FOUND SO COOL THAT I DEDICATED A WHOLE SECTION OF THIS WEBSITE TO IT? Computers don't actually know addition; they estimate. Our job is figuring out how close they get and how wrong we can safely let them be. I've dedicated the next section to it—click here.

NOV 2025 — MAR 2026

Software Engineering Intern

ALIEN ATTORNEY

I built AI search that could navigate more than 10,000 legal documents. Need the polished corporate version? It's on my résumé ↗

THAT'S THE RÉSUMÉ-FRIENDLY PART. THE THING I ACTUALLY COULDN'T STOP TALKING ABOUT? Cosine similarity can make AI understand the idea you meant, even when your question and the answer use almost none of the same words. Slightly creepy. Extremely useful.

NOV 2024 — MAR 2025

Computer Science Researcher

HOODLE LABS · UC RIVERSIDE

I made million-run entomology simulations move three times faster. Want the data-heavy director's cut? Check the résumé ↗

NUMBERS ASIDE, HERE'S THE SIX-LEGGED PLOT TWIST THAT NEVER MADE MY RÉSUMÉ: Ant colonies have no central boss. They're basically distributed systems with six legs, excellent uptime, and a truly unreasonable amount of data.

B.S. Computer Science

University of California, Riverside
Expected graduation · 2027
Competitive Coding Club · Board Member

Technical toolkit

C++ · C · C# · Java · Python · Rust · TypeScript · Go · JavaScript · Assembly · SQL · React · React Native · Node.js · Next.js · FastAPI · Spring Boot · GraphQL · PyTorch · TensorFlow · LangChain · Hugging Face · OpenAI API · .NET · Kafka · RabbitMQ · Git · Linux

Embedded systems · precision

Close
enough?

Computers are brilliant at whole numbers. Decimals are where things get weird. Most values cannot be represented perfectly in binary, so the machine stores the closest version it can.

That means a calculation can be mathematically correct and still land a microscopic distance away from the answer. Usually, nobody notices. In real-time embedded systems, that tiny difference can accumulate, change a threshold, or arrive one interrupt too late.

Working on brain-computer-interface firmware taught me that engineering is not just asking, “Is this right?” It is asking, “How wrong can this safely be—and how quickly do we need to know?”

That balance between precision, latency, memory, and hardware is what makes low-level software so fascinating: every approximation has a cost, and every saved cycle has a reason.

LOADING SEQUENCE — 0%

Life,
compiled.

Interested in my projects? The serious technical stuff lives right over here ↘

Clash of Clans [TownHall 11 Maxed · Clan Co-Leader]

Yes, I take fictional infrastructure seriously. Visit my village · #R208JCU2C ↗

I think designing a good base helps with system design. I might be forcing it, but both involve managing limited resources, layering defenses, and building something that can survive hostile traffic.

Chess.com: 500 Elo → 1200

That's the year-end target. Public accountability seemed like a good idea five seconds ago. Challenge me on Chess.com ↗

I think chess helps with LeetCode. I might be forcing it, but both reward seeing the trap before committing to the move.

Rubik's Cube [3×3—for now]

I can solve the classic 3×3. The mirror cube is next, because apparently one shape-shifting headache wasn't enough.

Tap the binary strings below—or move your cursor through them. Make sure your audio is turned on :)

Can you beat my fastest mile?

Yes, I run—usually when sitting at a debugger starts feeling medically irresponsible. Find me on Strava ↗

Crows & ravens

I like them because they're tough, clever, and just dramatic enough.

Small fact: crows remember human faces for years—and can teach other crows who caused trouble. So be polite.
SELECTED ENGINEERING2024—2026
01 / C++ · MULTITHREADING · DISTRIBUTED SYSTEMS

Concurrent KV Engine

LIVE PROJECTClick here to use it ↗GITHUBGo deeper into the code ↗
WHAT IT ACTUALLY DOES

Imagine 200 people asking one librarian to store and fetch notes at once. Instead of one enormous cabinet—and one enormous line—the engine sends each key to one of 64 smaller locked cabinets. Different people can safely use different cabinets at the same time.

THE TECHNICAL VERSION

A C++ key-value engine that hashes requests across 64 independent shards, uses fine-grained locking and an LRU cache, and serves TCP/UDP clients at 159,000+ operations per second across 200 concurrent connections.

THIS IS BASICALLY WHAT I CODED

WHY?

Unlike one regular data table with one waiting line, independently locked shards let many reads and writes move safely in parallel—especially as the dataset and traffic grow.

VECTOR<SHARD> [64]hash(key) % 64 → ONE INDEPENDENT SHARDSHARD 05shared_mutexadvit → SWEcube → solvedSHARD 22shared_mutexraven → cleverchess → 1200SHARD 51shared_mutexcoffee → hotbug → fixedSEPARATE O(1) LRU CACHEUNORDERED_MAPkey → list iterator"advit" → •"raven" → •advit:SWEMOST RECENTraven:cleverOLDERCACHE MISS? READ THE SHARD.CACHE HIT? MOVE NODE TO THE FRONT.
02 / DISTRIBUTED SYSTEMS · COMMERCE · GRAPHQL · MICROSERVICES

Distributed Commerce

LIVE PROJECTClick here to use it ↗GITHUBGo deeper into the code ↗
WHAT IT ACTUALLY DOES

A full e-commerce platform split into 5 independent services—catalog, pricing, inventory, orders, and payments—all talking through a single GraphQL gateway. Add to cart, check out, and watch the order propagate through each service in real time.

THE TECHNICAL VERSION

Next.js storefront → Apollo GraphQL gateway → 5 FastAPI microservices → PostgreSQL (Neon) + Redis (Upstash). JWT auth, event-driven order flow, deployed on Render (backend) and Netlify (frontend). 159k+ ops/sec throughput at the cache layer.

ONE GATEWAY, FIVE SERVICES, ZERO SHARED STATE

WHY?

Each service owns its own database. Pricing can go down without taking inventory with it. The gateway is the only piece any client ever talks to.

NEXT.JSGRAPHQL GATEWAYCATALOGPRICINGINVENTORYORDERSPAYMENTSPOSTGRES · REDIS
03 / IOS · ANDROID · COMPUTER VISION · GAMEPLAY WORK IN PROGRESS

WildCard

PROJECT PREVIEWDemo coming soon ↗GITHUBCode hatchery coming soon ↗
WHAT IT ACTUALLY DOES

Spot an animal, take its photo, and recruit it as a fighter. A crow might unlock clever aerial attacks; a lion gets a very different, considerably less polite move set. Then your newly discovered creatures battle other players' teams.

THE TECHNICAL VERSION

A cross-platform iOS and Android app combining camera capture, animal classification, generated creature stats, and a turn-based combat engine. The big unsolved checkpoint is reliable capture verification: proving the camera saw a real animal instead of another screen or printed photo.

THE WORLD BECOMES THE CHARACTER SELECT SCREEN

WHY?

Because seeing a crow on a walk should be the beginning of a side quest, not just something you forget five minutes later.

FROM SIGHTING → FIGHTER01 · CAMERASNAP THE ANIMAL02 · REAL-CAPTURE CHECKNOT A SCREEN / PRINT?OPEN PROBLEM03 · CLASSIFYCROW · LION · RAVEN...04 · BUILDSTATS + MOVE SETCROWDIVE BOMB · MIMICSPEED 88 · WIT 97LIONPOUNCE · ROARPOWER 98 · WIT 6105 · BUILD A TEAM. PICK A MOVE. BATTLE.
THE FULL STORY · ONE PAGE

Résumé.

DOWNLOAD PDF ↓