Taha Yasin BhattiEmail

I take ML and AI systems from prototype to production, and I fix them when they break in production.

I’m Taha Yasin Bhatti, a machine-learning engineer and researcher in Lahore. I work on agent systems, geospatial planning and ML infrastructure where a plausible demo is only the beginning.

system trace2025 incident
01ESP8266
02IoT Core
03DynamoDB
04Trigger
05Lambda
06AQI
silent boundarydisabled stream trigger · months without an alarm
Production trace from the urban air-quality network

A public-safe production trace from an urban air-quality network. The disabled stream trigger caused months of silent data loss; the repair made freshness visible at every boundary.

Production systems

Commercial work is described by sector, geography and system shape. Private names and architectures remain private.

2023–26

Lead architecture and principal engineering

Agents and privacy controls across three operating systems

A multi-agent order-and-fulfilment assistant for a US retailer, taken from prototype to production against live order systems. I designed structured tool calls, permission boundaries and regression coverage, then turned the implementation into a reusable template for a second brand in the same group.

  • 3 system shapes
  • 2 retail brands
  • 2-layer PII control

Full record

system trace2023–26
01Request
02Orchestrator
03Policy
04Tools
05Trace
Disclosure-safe agent orchestration diagram

Public systems

Energy, mobility and environmental infrastructure with the scale figures attached to the programmes that own them.

2025–26

Lead architect

Multi-agent grid and EV planning

The planning surface combines five layers that usually live in different tools: distribution-grid data, traffic patterns, geospatial analysis, demand forecasts and hosting-capacity estimates. A FastAPI service coordinates the analysis. The Next.js and deck.gl front end handles city-scale polygon and vector-tile rendering; Docker Compose keeps the working system reproducible across environments.

  • 5 planning layers
  • 2 utility briefings
  • ACEF 2025

Full record

system trace2025–26
01Grid
02Traffic
03Forecast
04Capacity
05Map
Public-safe planning system map

2024–25

Lead architect

Urban air-quality sensing network

ESP8266 sensor nodes publish through AWS IoT Core into DynamoDB. Lambda processing converts readings into EPA AQI bands, and a hosted dashboard renders IDW-interpolated heatmaps across the monitored area.

  • 8 university partners
  • 4-stage cloud path
  • Months-long failure diagnosed

Full record

system trace2024–25
01ESP8266
02IoT Core
03DynamoDB
04Trigger
05Lambda
06AQI
silent boundarydisabled stream trigger · months without an alarm
Air-quality ingestion production trace