The engineer behind your AI systems.

Muhammad Roman Khan (M R KHAN) combines formal Artificial Intelligence (BS AI) education with real-world system architecture. Designing production AI agents, custom machine learning workflows, and data pipelines built for business growth.

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CORE STACK & SPECIALTIES

BS Artificial Intelligence PyTorch & Deep Learning Machine Learning (scikit-learn) Python & Data Engineering n8n Workflows OpenAI API & LLM Orchestration Supabase & PostgreSQL HubSpot & CRM Sync

Engineering depth meets practical automation.

Muhammad Roman Khan is a software builder and BS Artificial Intelligence scholar with a singular focus: engineering practical, resilient AI systems that replace manual chaos with reliable autonomous workflows.

Unlike surface-level tool integrators, his work is backed by a disciplined foundation in Machine Learning and Deep Learning. From training predictive models and decision tree ensembles to writing custom PyTorch neural network architectures, he understands how algorithms operate under the hood—ensuring models are chosen for accuracy, speed, and real operational fit.

His engineering extends deeply into Data Analytics & Data Engineering: building clean ingestion pipelines, structuring SQL databases, and automating statistical triage so that AI agents receive reliable, validated data rather than noisy assumptions.

On the production side, his commercial automations—including custom AI generation pipelines for ArtPoliceJoe—have produced over $30K in revenue. Through MRKHANSERVICES, he builds complete lead intake engines, autonomous chatbots, and CRM sync systems that give growing businesses 20+ hours back every week.

Muhammad Roman Khan - M R KHAN Profile

Engineering, machine learning, & performance.

BS Artificial Intelligence Foundation

Pursuing a degree in Artificial Intelligence (BS AI)—grounding every workflow in mathematical rigor, statistical modeling, and machine learning principles from the ground up.

Deep Learning & PyTorch Architectures

Hands-on experience building, training, and fine-tuning neural networks, supervised learning ensembles (XGBoost, Random Forests), and PyTorch models for targeted intelligence tasks.

Data Engineering & Analytics Pipelines

Designing robust data extraction pipelines, custom Python ETL flows, and normalized SQL/Supabase databases that supply clean, structured inputs to production AI agents.

Production B2B Systems We Stand Behind

Translating advanced AI models and APIs into self-running business infrastructure that triages leads, connects CRMs, and returns 20+ hours each week to operating teams.

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