hi, i'm Dvip.
i train language models and i train my sleep schedule. one of them is vastly outperforming the other. this is a portfolio, but like, the funny version. the real one is up the hall → /academic.
“refactors in prod, apologizes in pull requests.”
— anonymous commit message, probably
the lore (abridged)
everything true, nothing serious
- • 179-page thesis. defended. 1 paper, 2 badges.
- • ships on fridays. coping is a strategy.
- • allegedly owns a cat named segfault.
jobs i've conned my way into (real)
linkedin's words, my vibes
aka Founding Engineer at Mediabridge — a multi-tenant SaaS i helped build from an empty repo.
- 🔸Co-built and launched a multi-tenant SaaS platform from scratch, owning architecture decisions across frontend, backend, and AWS deployment.
- 🔸Personally built the core systems — a custom role-based access control (RBAC) layer, a dynamic form builder, and an event-driven notification system.
- 🔸Owned the full lifecycle from requirements through production launch and served as primary technical contact for the client.
aka AI Engineer at Palomino Systems — a place that asked for a migration, got a whole pipeline.
- 🔸Designed and shipped Laravel Upgrader, a fully autonomous CLI-driven AI agent that migrates legacy Laravel codebases end-to-end — a 10-step pipeline (analysis → planning → transformation → validation → self-healing) processing ~10k LOC/run at under $80/run, with 85–90% automated issue resolution via detect → fix → retry loops.
- 🔸Measured two full migrations by hand first, then automated those exact steps — cutting manual migration effort by ~80% (a baseline-grounded number, not an estimate).
- 🔸Owned the codebase end-to-end and was the primary technical contact with Palomino stakeholders, presenting the agent architecture and translating tradeoffs into prioritized recommendations.
aka Graduate Research Assistant (Responsible AI & Evals) at Ontario Tech University — a university that tolerates my 1am commits.
- 🔸Designed TRAC-RE — a Traceable, Reliable, Auditable, and Contextual framework for automated Requirements Engineering, built from four interconnected phases that take raw stakeholder prose to implicit domain-knowledge discovery, grounded in an industrial FinTech/SaaS corpus of 110 requirements and 1,997 High-Level JSON (HLJ) artifacts.
- 🔸Phase 1 — Context-aware requirement identification: empirical study of sentence-level classification (all-mpnet-base-v2, DeBERTa-v3-base) across frozen / LoRA / full fine-tuning and context windows k=0–3, showing structured local context adds +16 F1 points (0.664 → 0.894) and that 4K domain-aligned samples (F1=0.894) beat 15K mixed (F1=0.883).
- 🔸Phase 3 — Governed LLM parsing: built and benchmarked a multi-model parsing pipeline (GPT-4.1, Claude Opus 4, Meta-70B) producing confidence-scored HLJ artifacts with a versioned tag-governance stack (Harvest → Filter → Cluster → Validate → Whitelist → Audit → Drift); tag precision improved 0.657 → 0.897 at the strictest v2 stage. Published at CASCON 2025 (IEEE), first author.
aka Full-Stack Developer at Finserve Infotech — a place where i speak fluent laravel.
- 🔸Delivered 4 production systems for clients across three industries (manufacturing, retail distribution, travel), building each full stack in Laravel and MySQL, from UI and application logic to the transactional schemas underneath.
- 🔸Built a manufacturing execution system tracking garment production end to end, from raw cotton to finished product, including routing work out to external processors and back, with bidirectional invoicing covering both standard and reverse invoice flows for subcontracted stages.
- 🔸Built a supply chain and distribution platform moving finished goods from factory through warehouse to retail stores, with multi-location inventory tracking and an integrated point-of-sale module.
papers i wrote when i should've been sleeping
the thesis is real, the sleep isn't
“Toward Automated Requirements Engineering: Empirical and Architectural Foundations for Structured Parsing and Knowledge Discovery”
aka: teaching LLMs manners, with receipts. supervised by Prof. Sanaa Alwidian.
the one that actually got published 🏆
A modular multi-model LLM pipeline that converts raw stakeholder requirements into High-Level JSON (HLJ) artifacts with confidence-scored fields, paired with a versioned…
want the write-up with actual numbers and no emoji? → academic mode
things i built (on purpose)
shipped > perfect, always
want the grown-up version with the full stack + story? → corporate mode
the arcade (please touch the exhibits)
six ways to waste time productively
powered by a cheap, rate-limited LLM. be nice, it's on a budget.
type a roast. the AI will roast you back, harder each round. it does not have feelings, but it will pretend to be hurt and then end you.
type your name. a real (cheap, sleepy) AI decides if you and dvip build a unicorn or a merge conflict.
launch an AI startup
no product. no plan. infinite confidence. click to raise money you will absolutely set on fire.
hit generate to receive a perfectly reasonable, totally achievable requirement from a product manager who definitely understands engineering. 🫠
it's 4:55pm on a friday. the button is right there.
psst: there's an achievement system. yes, on a portfolio. no, i will not explain myself. try the konami code. ↑↑↓↓←→←→ b a
the meme museum (peer-reviewed)
generated live · academically accurate · citation: trust me bro
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memes, but every caption is a real résumé fact.
source: thesis · phase 1 · template: drake
curator's note: if any exhibit shows a cat instead of a meme, the meme API died and the cat is covering the shift. tip him.
skills, tier-list style
scientifically wrong, vibes accurate
ok but actually, here's the real stack →
5 cards per pack, one guaranteed rare+. commons→epics are real skills; legendaries (3%) are real receipts.
wall of random flexes
receipts, flex, fine print
framed somewhere. probably.
“Toward Automated Requirements Engineering: Empirical and Architectural Foundations for St…”
supervisor: Prof. Sanaa Alwidian
resolved: ∞
remaining: ∞ + 1
status: it's fine. this is fine.
- coffee/day: 2.4
- tea/day: 1.1 (emergency)
- commits/coffee: 7
- commits/tea: 0.3
- uptime: mine? or the servers?
- sleep SLA: breached every night
- on-call vibe: contemplative
every serious number on this page is traceable to an mdx file in /content. the coffee stats are not. that's a flex, right? right?
boss-fight: high-five the cat
clear this level → unlock hire-me card
high-five the cat to unlock. cat policy. (exceptions: see below.)
coded at 3am · deployed at 4am · debugged at 4:07am · cat slapped 0×