Mr. Doohwan Kwak Profile

Doohwan Kwak

Keumkang Designer at Siemens EDA

SPIE Involvement:

Author

Publications (4)

Proceedings Article | 28 April 2023 Presentation + Paper

Unsupervised ML classification driven process model coverage check

SeungWon Song, Seokyoon Jeong, Sangwoo Park, Jungkee Choi, WoonHyuk Choi, No-young Chung, Seongtae Jeong, Fan Jiang, Liang Cao, Le Hong, Junhyoung Park, Doohwan Kwak, Jongwon Lee, Harin Kim, Jiyoung Lee

Proceedings Volume 12495, 1249518 (2023) https://doi.org/10.1117/12.2658322

KEYWORDS: Data modeling, Process modeling, Machine learning, Optical proximity correction, Statistical modeling, Calibration, Instrument modeling, Metrology, Design and modelling, Resolution enhancement technologies

Read Abstract +

Proceedings Article | 27 April 2023 Paper

AI-guided reliability diagnosis for 5,7nm automotive process

Dongin Kim, Hyung Joo Lee, Sanghyun Choi, Seungpyo Hong, Seungjae Lee, Doohwan Kwak, Srividya Jayaram, Seungwon Paek, Minho Kwon, Yeongdo Kim, Hyobe Jung, Ivan Kissiov, Melody Tao, Andres Torres, Nathan Greeneltch, Ho Lee

Proceedings Volume 12496, 124963J (2023) https://doi.org/10.1117/12.2662880

KEYWORDS: Reliability, Semiconducting wafers, Data modeling, Manufacturing, Fabrication, Semiconductors, Industry, High volume manufacturing, Model-based design, Metrology

Read Abstract +

Proceedings Article | 23 March 2020 Presentation + Paper

Reduction of systematic defects with machine learning from design to fab

Yuansheng Ma, Le Hong, James Word, Fan Jiang, Vlad Liubich, Liang Cao, Srividya Jayaram, Doohwan Kwak, YoungChang Kim, Germain Fenger, Ananthan Raghunathan, Joerg Mellmann

Proceedings Volume 11329, 1132909 (2020) https://doi.org/10.1117/12.2551703

KEYWORDS: Machine learning, Optical proximity correction, Photomasks, Etching, Data modeling, Process modeling, Neural networks, Semiconducting wafers, Inspection

Read Abstract +

Proceedings Article | 20 March 2019 Presentation + Paper

Predictable etch model using machine learning

Youngchang Kim, Sunwook Jung, DooHwan Kwak, Vlad Liubich, Germain Fenger

Proceedings Volume 10961, 1096106 (2019) https://doi.org/10.1117/12.2515271

KEYWORDS: Etching, Optical proximity correction, Mahalanobis distance, Machine learning, Convolution, Statistical modeling, Metals, Calibration, Optical lithography, Lithography

Read Abstract +

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years