Physical AI · Robotics · Digital Twin

Hi, I'm Matthew Hsieh

NVIDIA Omniverse / Isaac Sim · Industrial Robotics · Customer Deployment

I build and deploy industrial Physical AI and Digital Twin systems from 0-to-1 development through real-world customer validation, robotics integration, and factory adoption.

2+
Years in Physical AI
12
Weeks U.S. Customer Onsite
4
Customer Production Stations

From Simulation to Production Deployment

Hands-on engineering with customer-facing ownership across Physical AI, robotics and manufacturing.

0-to-1 Platform Ownership

Primary owner and developer of the first-generation industrial Digital Twin / Physical AI platform at Pegatron, covering NVIDIA Omniverse and Isaac Sim, local applications, third-party integration, robot integration, deployment and cross-system debugging.

Customer-Facing DRI

Served as the Digital Twin DRI for a major U.S. consumer electronics manufacturing program, translating factory requirements into technical solutions and owning integration, feature delivery, debugging, validation and technical enablement.

AI Academic Foundation

M.S. from the Graduate Degree Program of Artificial Intelligence at National Yang Ming Chiao Tung University (NYCU), with graduate research in synthetic data generation using Conditional Normalizing Flows.

Core Competencies

A deployment-oriented stack spanning simulation, robots, software and factory integration.

Physical AI & Simulation

NVIDIA Omniverse, Isaac Sim, OpenUSD, PhysX, Digital Twins, Real-to-Sim, Sim-to-Real, Synthetic Data

Robotics & Motion

ROS 2, MoveIt, Universal Robots / UR5e, Epson, Flexiv, Manipulation, Motion Planning, Pick-and-Place

Industrial Integration

RTDE, MQTT, AWS IoT Greengrass, REST APIs, industrial equipment and camera integration

Software & Systems

Python, C/C++, JavaScript, Linux, Docker, APIs, application UI and deployment tooling

Solution Delivery

Requirements discovery, solution design, onsite debugging, customer validation, enablement and knowledge transfer

AI / ML Foundation

PyTorch, TensorFlow, OpenCV, NumPy, Pandas, Normalizing Flows and synthetic-data research

Physical AI & Digital Twin at Pegatron

0-to-1 engineering, customer delivery, productization and factory adoption.

2024 - Present

Senior Engineer — Physical AI / Digital Twin

Pegatron Corporation

Taiwan & United States

Build and deploy industrial Digital Twin and robotics solutions using NVIDIA Omniverse / Isaac Sim, serving across hands-on development, solution integration, customer delivery and production deployment.

🚀
0-to-1 Primary Owner & Developer

Owned the first-generation Physical AI / Digital Twin platform across simulation, UI, third-party software, robot integration and deployment, before later development was expanded to additional team members.

🇺🇸
Digital Twin DRI for U.S. Customer Program

Owned Digital Twin delivery across four production stations—Pick-and-Place, Screw, Press and robotic dispensing—working directly with customer engineers on requirements, technical decisions, debugging and validation.

🛠️
Two Six-Week Onsite Deployments

Acted as the primary Digital Twin technical owner during 12 total weeks of U.S. onsite support, resolving cross-team integration issues and delivering new features required for acceptance.

✅
Validation Tied to Commercial Milestones

Successful customer validation after onsite engagements enabled major commercial milestones, connecting engineering delivery directly with project execution and business outcomes.

🎓
Customer Enablement & Scale-Out

Established deployment workflows and transferred technical knowledge so customer engineers could independently extend Digital Twin deployment beyond the initial four stations.

🏭
Productization & Internal Factory Adoption

Supported evolution of the original solution toward a reusable product platform and currently contributes to Digital Twin optimization PoCs across two internal Pegatron production lines.

NVIDIA GTC & COMPUTEX 2025

Representing the project from technical demonstration to commercial productization.

Technical Demonstration

NVIDIA GTC 2025

March 2025 • San Jose, CA

Primary Platform Owner on the Exhibition Floor

Demonstrated the first-generation system in person, explaining the engineering architecture and industrial use cases to external technical audiences. The project later appeared in NVIDIA public customer and keynote content.

NVIDIA Omniverse
Isaac Sim
Physical AI
Product Evolution

COMPUTEX 2025

May 2025 • Taipei, Taiwan

From Demonstration to Reusable Product

Represented the platform as it evolved from an exhibition prototype into a reusable customer solution, with follow-on engagement from the U.S. program and growing interest from manufacturing organizations in Taiwan.

Productization
Customer Adoption
Manufacturing AI

Projects & Research

Professional Physical AI systems plus academic and open-source work.

Customer Deployment

Multi-Station U.S. Manufacturing Program

Digital Twin DRI across four production stations. Two six-week onsite engagements covered requirements, solution integration, new feature delivery, debugging, validation and customer enablement. Customer identity and implementation details are intentionally omitted for confidentiality.

Customer DRI4 Stations12 Weeks OnsiteProduction Deployment
Internal Factory PoC

Digital Twin Optimization Across Two Production Lines

Supporting group-level factory teams in evaluating where Digital Twin and simulation can improve line efficiency, process visibility and engineering decision-making. The current phase is PoC and use-case discovery across two production lines.

Factory OptimizationPoCDigital TwinManufacturing
Master's Research

Synthetic Data Generation using Conditional Normalizing Flows

Graduate research on Conditional Normalizing Flows for high-quality synthetic data generation, including data upsampling, outlier-focused generation and objective evaluation of generated data quality.

Machine LearningNormalizing FlowsPythonDeep Learning
GitHub Project

Stock Analysis & Backtesting

Python-based stock analysis and strategy backtesting projects covering data processing, technical indicators, strategy evaluation and performance analysis.

PythonPandasBacktesting
University Project

Autonomous Campus Patrol Vehicle

Autonomous patrol vehicle integrating ROS, computer vision, remote monitoring and a web control interface—an early robotics project preceding my current industrial robotics work.

ROSPythonComputer Vision

Let's Connect

Open to conversations around Physical AI, robotics, simulation and industrial deployment.

Professional Links

For recruiting, technical collaboration or engineering discussions, email or connect with me through LinkedIn.