33.6844° N 73.0479° E ISB --:--
AI / ML ENGINEER ELECTRONICS RESEARCHER FULL-STACK BUILDER

HASNAAT HUSSAIN

Muhammad Hasnaat Hussain, AI and machine-learning engineer from Islamabad
FIG. 01 / HUMAN IN THE LOOP

CURRENT THESIS

Building intelligence that survives contact with the real world.

Selected work Resume / PDF
00 / THESIS NOISE IN → SIGNAL OUT

Physical signals. Learned systems. Shipped products.

I work across the full path: from electronics and signal processing, through model architecture, to the interface a person actually uses.

The advantage is not another tool list. It is seeing the system as one connected instrument.

01 / SENSEPhysical world
02 / LEARNModel behavior
03 / SHIPProduction system
01 / SELECTED TRANSMISSIONS THREE SYSTEMS / IN PRODUCTION

Work that moved from idea to interface.

Selected products where machine intelligence is part of the operating system, not an ornamental feature.

RETENTION SIGNAL / LIVE MODEL CONFIDENCE 92.4%
CUSTOMER HEALTH / COHORT 04 LOW RISK INTERVENTION RECOVERING
ACCOUNT HEALTH / BILLING / SUPPORT ANCHORYN © 2026
01 / 03

AI-POWERED B2B SAAS

Anchoryn

Find the churn signal before the customer leaves.

A retention operating surface combining behavior, account health, support pressure, billing signals, and AI-guided interventions for founders and customer-success teams.

ROLE
Product / ML / Full stack
SYSTEM
PyTorch, FastAPI, PostgreSQL, Next.js
FOCUS
Risk prediction & actionability
Open live product↗
RETROFORGE.EXE_ □ X
WEB TIME MACHINE
ERA SELECTORX
  • WINDOWS 98
  • GEOCITIES
  • CRT TERMINAL
  • MAC CLASSIC
PROCESS COMPLETE 8 ARTIFACTS GENERATED █
AUTHENTICALLY INCORRECT / 1998–2026
02 / 03

GENERATIVE WEB TOOL / MONOREPO

RetroForge

Send any website backwards through the internet.

A nostalgia-heavy generator that converts public sites into era-correct artifacts: XP, Windows 98, GeoCities, CRT, Netscape, ANSI/BBS, and early Blogspot.

ROLE
Concept / System / Frontend
SYSTEM
Next.js, TypeScript, Python, Tailwind
FOCUS
Generative art direction
Open live product↗
01 / INPUT NICHE Objects for slow mornings
02 / THEME
Editorial commerce
03 / COPY SYSTEM
04 / DEPLOY STORE LIVE 00:57
03 / 03

LLM TOOLING / COMMERCE

StoreCraft AI

From a niche to a configured Shopify store in under a minute.

An AI store builder generating themes, product copy, email flows, ad creative, and policies before deploying the finished storefront.

ROLE
Product / AI workflows / Full stack
SYSTEM
Next.js, Node.js, OpenAI, Shopify API
FOCUS
Generative operations
Open live product↗
02 / OPEN-SOURCE PATCH BAY FAULT → INTERVENTION → MERGE

Fixing the layer underneath.

Production-grade AI and data infrastructure improves one precise upstream intervention at a time.

PYDANTIC AIMERGED
6098

Amazon Bedrock tool-result co-location across model families.

Prevented validation failures during agent conversations by handling provider-specific content constraints correctly.

BUG FIX / COMPATIBILITY↗
SQLGLOTMERGED
7807

Correctly parsed parenthesized multi-expression queries.

Resolved a parser edge case where expression tuples were interpreted as subqueries.

PARSER / CORRECTNESS↗
PLOTLY.JSMERGED
7768

Small-number tick labels in exponential notation.

Fixed axis formatting across chart types for values near the exponential threshold.

AXES / FORMATTING↗
ULTRALYTICSMERGED
25153

RT-DETR detection limits across export and validation.

Honored max_det consistently in decoder exports and evaluation paths.

MODEL EXPORT / DETECTION↗
05 OPEN SIGNALS Current pull requests
PANDAS / 66209CustomBusinessDay resampling with closed="right"OPEN ↗ LITELLM / 32452Embedding dimensions with drop_paramsOPEN ↗ LITELLM / 31081Budget checks on model discovery routesOPEN ↗ LLAMA INDEX / 22310Nested object properties in MCP schemasOPEN ↗ CREWAI / 6377Structured tool-output serializationOPEN ↗
03 / CAPABILITY SPECTRUM MODEL WEIGHTS → USER SURFACE

One connected instrument.

Depth in the model layer, range across the production stack, and an electronics foundation underneath both.

BAND / 01

Models & intelligence

PyTorch, Transformers, computer vision, YOLO, RAG, ONNX, quantization

BAND / 02

Data & systems

FastAPI, PostgreSQL, Redis, Kafka, experiment tracking, APIs, deployment

BAND / 03

Product engineering

Next.js, React, TypeScript, Node.js, interaction design, Vercel, Docker

BAND / 04

Hardware-aware foundations

Digital signal processing, RF systems, edge inference, FPGA fundamentals

04 / FIELD NOTES ISLAMABAD / PAKISTAN
Portrait of Muhammad Hasnaat Hussain SUBJECT HH / FRAME 02

BACKGROUND / DIFFERENTIATOR

A builder shaped by signals before software.

I am an electronics student at Quaid-i-Azam University, going deep on machine learning while building products people can actually use. Signal processing, quantization, and edge inference feel natural because the physical layer came first.

I also work upstream: finding precise failures in production-grade AI infrastructure and fixing them at the source.

JUL 2026 — PRESENT
NATIONAL CENTER FOR PHYSICS / COE AITEC

ML / DL Intern

Deep-learning research in Islamabad, applying modern machine-learning architectures to real research problems.

AUG — SEP 2025
RADIO PAKISTAN / ISLAMABAD

Engineering Intern

Worked with real-time audio pipelines, broadcast transmission, and digital signal processing in a live production environment.

2023 — 2027
QUAID-I-AZAM UNIVERSITY

BS Electronics

Transformers, attention mechanisms, clustering, computer vision, digital systems, and edge-AI deployment.

05 / LIVE DEVELOPMENT SIGNAL SNAPSHOT / 2026-08-08

Work in the open.

A live readout of public repositories and contribution cadence. Static evidence remains when the network does not.

30PUBLIC REPOSITORIES
8GITHUB FOLLOWERS
10TRACKED PRS
04MERGED UPSTREAM
CONTRIBUTION DENSITY / 52 WEEKSLIVE SIGNAL
Full profile ↗
QUIETACTIVE
06 / ESTABLISH A LINK AVAILABLE FOR SELECT WORK

HAVE A HARD PROBLEM?

Bring the signal.

Open to remote roles, serious freelance work, and ML problems worth thinking about.

GITHUB ↗ LINKEDIN ↗ X / TWITTER ↗ RESUME ↗