We use MixedWM38, the mixed-type wafer defect pattern dataset for wafer defect pattern regcognition with visual transformers.

• UpdatedOct 1, 2023
• Jupyter Notebook

Lithography defect prediction for microchip manufacturing optimization with machine learning model

• UpdatedDec 2, 2023
• Jupyter Notebook

Practical example from the SPIE short course "Data Analytics and Machine Learning in Semiconductor Manufacturing: Applications for Physical Design, Process and Yield Optimization"

• UpdatedFeb 25, 2018
• Jupyter Notebook

MEMS patent

• UpdatedMay 25, 2025
• TeX

SemiPRO: Advanced Semiconductor Process Simulator

• UpdatedJul 10, 2025
• C++

Data-Driven Optimization of Semiconductor Processes and Forecasting

• UpdatedAug 28, 2024
• Jupyter Notebook

Czochralski Apparatus for Modeling Efficient Lattice growth

• UpdatedJul 19, 2024
• SWIG

Semiconductor Process Control (ECE6455-A) @ Georgia Institute of Technology, Atlanta, GA, USA

• UpdatedFeb 20, 2024
• Jupyter Notebook

Revolutionary ultra-smooth nanofabrication platform with quantum-enhanced precision manufacturing. Achieved 90.4% manufacturing readiness with full commercial deployment approval. Features quantum coherence positioning (0.062 nm accuracy), real-time quality control, and comprehensive UQ resolution for semiconductor and quantum device manufacturing.

• UpdatedJul 11, 2025
• Python

Micron AI Challenge 2025

• UpdatedJun 20, 2025
• Jupyter Notebook

klayout square array of auto-labeled alignment marks

• UpdatedApr 28, 2025
• Python

A Minecraft mod adding realistic semiconductor manufacturing.

• UpdatedSep 28, 2023
• Java

Calculating semiconductor chip yield against defect density using a Monte Carlo simulation is a common approach to assess the impact of defects on chip manufacturing. In this simulation, we'll randomly generate defect locations and evaluate chip yield based on specified criteria.

• UpdatedDec 1, 2023
• Jupyter Notebook