Md Irfan Khan profile picture

Hello, I'm

Md Irfan Khan

AI for Manufacturing · Robotics & Automation
Mechanical Design · Digital Twins

Mechanical Engineer & Researcher

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Who I Am

About Me

Robotics, automation, and intelligent-manufacturing work areas
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Research

"Graduate Research Assistant, University of South Carolina” with focus on collaborative Physical AI, digital twins, and smart manufacturing

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Education

Ph.D. in Mechanical Engineering (ongoing) University of South Carolina M.S. in Mechanical Engineering The University of Texas at Tyler

I am Md Irfan Khan, a mechanical engineer and researcher with a focus on collaborative Physical AI, digital twins, and smart manufacturing. I design and integrate intelligent systems that connect mechanical hardware, industrial controls, simulation, and data.

I have professional experience designing, prototyping, simulating, testing, and validating mechanical and automated systems. As a Graduate Research Assistant at the University of South Carolina, I work on smart manufacturing, digital twins, federated learning, and predictive maintenance. My research explores trustworthy, decentralized learning for robotic inspection and automation while protecting proprietary manufacturing data.

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What I Focus On

Expertise

Automation

Industrial Automation

PLCs (Rockwell,Siemens), Ladder Logic, Digital twins, Smart Manufacturing & Industrial Control.

AI in Manufacturing

AI in Manufacturing

Federated learning, predictive maintenance, machine learning & data-driven optimization.

Mechanical Design

Mechanical Design

CAD, prototyping, simulation & testing for consumer electronics and industrial systems.

Robotic systems integration

Robotic Systems Integration

Robot simulation, ROS 2, NVIDIA Isaac Sim, PLC-based control, sensors, and vision-language-action model exploration.

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What I Am Exploring

My Research

Decentralized Collaborative Physical AI

Developing an incentive-driven, blockchain-enabled decentralized federated-learning framework for collaborative Physical AI in distributed manufacturing. The work combines a robotic testbed, physical-virtual environment, edge-based learning services, and a permissioned blockchain so manufacturers can collaboratively improve inspection and robotic-manipulation models without sharing proprietary operational data. Key research areas include decentralized coordination, contribution valuation and trust, rare-event data acquisition, and sim-to-real validation.

Framework for decentralized collaborative Physical AI, connecting decentralized learning, trust and incentives, and physical-world modeling.
Conceptual framework for decentralized collaborative Physical AI in distributed manufacturing.

Digital Twins & Smart Factories

Developing data-connected virtual representations of manufacturing systems to support monitoring, simulation, and operational decision-making.

Robot Simulation & Integration

Exploring ROS 2 and NVIDIA Isaac Sim workflows for testing robot behavior, sensors, controls, and automation logic before deployment.

AI-Enabled Manufacturing

Applying machine learning, federated learning, and predictive-maintenance methods to improve manufacturing reliability and performance.

Vision-Language-Action Models

Investigating how VLA models can support more capable, adaptable human-robot interaction and industrial automation.

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Explore My

Strength

Technical Skills

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Federated Learning

Intermediate

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Ladder Logic

Intermediate

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Rockwell Automation: CCW

Intermediate

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ROS 2

Learning & Development

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NVIDIA Isaac Sim

Learning & Simulation

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VLA Models

Research Exploration

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Sensors & Industrial Control

Intermediate

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Solid Works

Experienced

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Autocad

Experienced

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Fusion 360

Basic

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PTC Creo

Intermediate

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KeyShot

Intermediate

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SolidCAM

Basic

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HSMWorks

Basic

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ANSYS

Intermediate

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CMG

Intermediate

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Tecnomatix

Intermediate

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Pnflow

Intermediate

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MATLAB

Intermediate

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Python

Intermediate

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Machine Learning

Intermediate

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Ms Office

Experienced

Certifications

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Hyperledger Fabric: Design, Develop, and Deploy (LFS270)

Issuing Organization: Linux Foundation

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Blockchain: Understanding Its Uses and Implications (LFS170)

Issuing Organization: Linux Foundation

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Mechanical Design at the Level of Professional

Issuing Organization: Dassault Systems

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Additive Manufacturing at the Level of Associate

Issuing Organization: Dassault Systems

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Six Sigma Foundations

Issuing Organization: Coursera

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The Elements of AI

Issuing Organization: University of Helsinki

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Browse My

Projects

Mechanical Design

Mechanical Design & Prototyping

Project 2

Published Works

Project 3

Other Projects

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Get in Touch

Contact Me