Dr. James P. Shiely
at Synopsys Inc
SPIE Involvement:
Author | Instructor
Publications (35)

Proceedings Article | 20 March 2019
Proc. SPIE. 10962, Design-Process-Technology Co-optimization for Manufacturability XIII
KEYWORDS: Lithography, Detection and tracking algorithms, Pattern recognition, Integrated circuits

Proceedings Article | 20 March 2019
Proc. SPIE. 10961, Optical Microlithography XXXII
KEYWORDS: Lithography, Photomasks, Machine learning, Computational lithography, Optical proximity correction

Proceedings Article | 20 March 2019
Proc. SPIE. 10961, Optical Microlithography XXXII
KEYWORDS: Lithography, Image processing, Silicon, Scanning electron microscopy, Semiconducting wafers

Proceedings Article | 3 October 2018
Proc. SPIE. 10810, Photomask Technology 2018
KEYWORDS: Lithography, Data modeling, Visualization, Computer programming, Neural networks, Photomasks, Machine learning, Information theory, Binary data, Neurons

Proceedings Article | 31 March 2014
Proc. SPIE. 9052, Optical Microlithography XXVII
KEYWORDS: Lithography, Data modeling, Calibration, Etching, 3D modeling, Integrated modeling, Photomasks, Optical proximity correction, Photoresist processing, Semiconducting wafers

Showing 5 of 35 publications
Course Instructor
SC1264: Machine Learning for Lithography
This course provides background on supervised learning applied to microlithography. A primary goal of the course is to illustrate supervised learning, inference, and validation workflow to practitioners of microlithography, using datasets and problems with which they are familiar. Example applications will include photoresist models and inverse lithography models. Example model types include linear classifiers, multilayer perceptrons and deep neural networks. Training methodology will utilize prepared datasets with Jupyter notebooks.
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