Dai-Rong Wu

CAD Automation & EDA Infrastructure Engineer

Architecting production-scale automation platforms and SPICE compact modeling frameworks. Demonstrated capability in driving global model deployment and significantly shrinking measurement timelines from days to hours at Tier-1 semiconductor companies.

CAD automation engineer with deep expertise in production-scale SKILL/Python automation platforms, process design kit (PDK) architecture, and SPICE compact modeling enablement. I thrive at the intersection of software engineering and semiconductor physics, designing robust systems that scale globally.

At Infineon, I architected a unified model lifecycle platform that slashed QA cycle time from 24 hours to 3 hours, effectively eliminating manual error pathways. I also developed automated testing flows that compressed measurement cycles from 1 day down to just 30 minutes. Previously, at Siemens EDA, I drove automated migration tooling that significantly accelerated global PDK delivery cycles.

I hold a U.S. Green Card and am available for immediate relocation. Fluent in English and native in Mandarin, I have extensive experience collaborating with U.S.-based engineering leadership to execute complex initiatives in distributed, cross-functional environments.

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Scale & Automation Deployed Python/SKILL frameworks that automated critical paths, reducing tuning time by 93% and QA time by 88%.
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Production Deployment Engineered production-grade solutions encompassing BSIM4, HiSIM-HV, PCell architecture, and CDF/Callbacks for global utilization.
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Distributed Execution Successfully coordinated cross-functional initiatives bridging EMEA, APAC, and North American engineering leadership.
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No Sponsorship Required U.S. Green Card holder โ€” unrestricted authorization to work and relocate within the United States.

Core Competencies

01

Automation & Infrastructure

Python (OOP, GUI) Cadence SKILL Tcl Perl Shell Scripting C / C++
02

EDA Platform & PDK Architecture

Cadence Virtuoso Siemens Tanner EDA Mentor Calibre (DRC/LVS/PEX) PCell Development CDF / Callbacks Netlisting iPDK Frameworks
03

SPICE & Simulation

BSIM4 / BSIM-Bulk HiSIM-HV Verilog-A / AMS HSPICE / Spectre / Eldo Ngspice Model QA Pipelines
04

DevOps & Domain Knowledge

Git / SVN Jira / Confluence CMOS / FinFET High-Voltage Devices Analog / Mixed-Signal RF Device Modeling

Professional History

SEP 2023 โ€” PRESENT
Staff Engineer โ€” CAD Automation & Compact Modeling
Infineon Technologies  ยท  Munich, Germany
  • Architected and deployed a production model lifecycle platform consolidating model translation, QA validation, and release pipelines into a unified framework โ€” cutting QA cycle time by 88%(24 h โ†’ 3 h).
  • Developed a scalable gradient-descent parameter centering engine, reducing manual SPICE tuning time by 93% and accelerating compact model delivery for high-voltage (HV) device families.
  • Built and maintained a Virtuoso-integrated validation infrastructure for automated device characterization, handling testbench generation, multi-parameter sweeps, and cross-simulator verification.
  • Executed automated QA flows that accelerated testing cycle times drastically, reducing standard measurement durations from 1 day to 30 minutes.
  • Directed end-to-end model enablement across production technology nodes, coordinating foundry partners, PDK, and design teams across EMEA for global compact-model releases.
MAR 2020 โ€” AUG 2023
Software Engineer โ€” EDA & PDK Platform Development
Siemens EDA  ยท  Hsinchu, Taiwan
  • Designed and shipped production PDKs enabling Tanner EDA design flows for global customer teams across diverse process technology nodes.
  • Built a compatibility layer for TSMC iPDKs by migrating legacy SKILL code to Tcl/Python, automating symbol and PCell conversion processes.
  • Maintained automated PDK regression testing infrastructure to ensure consistent release quality; managed transition from manual verification to automated standards.
  • Collaborated closely with U.S.-based engineering leadership and cross-functional teams across North America and APAC; fluent in distributed engineering execution.
JAN 2018 โ€” MAR 2020
Senior Engineer โ€” Device Modeling & EDA Enablement
United Microelectronics Corporation (UMC)  ยท  Hsinchu, Taiwan
  • Delivered production-grade SPICE models (MOSFETs, RF devices, varactors, diodes, resistors) deployed across UMC customer design flows for multiple technology nodes.
  • Established BSIM4 extraction methodology documentation and built a team mentorship program, standardizing knowledge transfer practices and accelerating modeling team ramp-up.

Automation Projects

๐Ÿค–
Analog-AI-Sizer

Automated analog circuit sizing framework integrating Bayesian Optimization with the SkyWater 130nm PDK. GUI-driven simultaneous Gain/Bandwidth optimization for single MOSFET and differential pair topologies.

Python Ngspice Bayesian Opt.
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BSIM4 Auto-Centering Engine

Gradient-based optimization engine for SkyWater 130nm BSIM4 models. Simultaneously tunes Vth0, u0, and vsat to target measurements, eliminating the iterative manual fitting loop entirely.

Python NumPy BSIM4
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KLayout PCell Generator

Comprehensive parameterized cell library for KLayout supporting Sky130 and GF180nm PDKs. Scriptable generation for MOSFETs, Resistors, and MIM capacitors with full GDS output.

Python KLayout GDS
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Aging Model Predictor

A machine learning-based tool for predicting device aging and degradation (HCI/BTI). Features Predictive Analysis using trained ML models on stress data, Reliability Modeling for HCI/BTI evaluation, and automated Visualization of degradation trends.

Python Machine Learning Device Reliability
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Analog Layout Constraint Extractor

Automated framework for extracting symmetry, matching, and routing constraints directly from analog circuit schematics to accelerate layout generation and verification.

Python EDA Layout
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OpenSpice Playground

An interactive simulation environment built around open-source SPICE engines, enabling rapid prototyping, testing, and visualization of analog circuit behaviors.

Python SPICE Simulation

Publications

[1]
SPAD Characterization in 0.18 ยตm High-Voltage CMOS
IEEE Journal of Lightwave Technology โ€” First Author
Single-Photon Avalanche Diode (SPAD) device characterization; compact modeling in production HV CMOS technology.
[2]
SPAD Measurement & Analysis in HV CMOS for Photon-Counting Applications
Proc. IEEE Optical MEMS & Nanophotonics (OMN) 2018 โ€” First Author
Conference paper expanding on SPAD noise characterization and dark count rate modeling at varying bias conditions.
[3]
Single-photon avalanche diodes in 0.18-ฮผm high-voltage CMOS technology
Optics Express 25 (12), 13333-13339, 2017
Co-author: L.D. Huang, J.Y. Wu, J.P. Wang, C.M. Tsai, Y.H. Huang, D.R. Wu, S.D. Lin.
[4]
CMOS single-photon avalanche diodes for light detection and ranging in strong background illumination
Proc. Solid-State Devices and Materials (SSDM), 319-320, 2018
Co-author: W.S. Huang, T.H. Liu, D.R. Wu, C.M. Tsai, S.D. Lin.

Academic Background

M.S. in Electronics Engineering
National Chiao Tung University (NCTU)
SEP 2015 โ€” AUG 2017 ยท Hsinchu, Taiwan

Research focus on SPAD device characterization in HV CMOS. Produced two first-author publications in peer-reviewed IEEE venues during graduate study.

B.S. in Physics
National Taiwan Normal University (NTNU)
SEP 2011 โ€” JUN 2015 ยท Taipei, Taiwan

Strong foundation in semiconductor physics, solid-state theory, and analytical mathematical modeling โ€” core underpinning for compact device modeling work.

Professional Certifications

Cadence
Advanced SKILL Language Programming

Advanced mastery of SKILL for EDA tool integration, complex data structures, and GUI development within the Cadence environment.

Verify Badge โ†’
Cadence
SKILL Development of Parameterized Cells

Expertise in coding advanced Pcells with stretching, repetition, and conditional layout logic for PDK architecture.

Verify Badge โ†’
Testdome
Programming in Python

Verified proficiency in Python algorithm design, data manipulation, and software engineering best practices.

Verify Certificate โ†’
Cadence
Analog Modeling with Verilog-A

Development of high-fidelity behavioral models for SPICE simulation and analog circuit verification.

Cadence
Behavioral Modeling with Verilog-AMS

Implementing mixed-signal behavioral models to accelerate system-level simulation and verification flows.

Verify Badge โ†’
Testdome
Programming in C++

Advanced knowledge of C++ memory management, OOP principles, and performance optimization.

Verify Certificate โ†’
EF SET
English Certificate (C2 Proficient)

Highest level of English proficiency, demonstrating ability to communicate complex ideas with native-level precision.

Verify Result โ†’

Language Proficiency

English
Full Professional Proficiency
C2
Mandarin
Native Speaker
Native
Taiwanese
Native Speaker
Native
German
Elementary Proficiency
A2