cv
Basics
| Name | Dongjae Shin |
| Label | Chemical Engineer |
| djayshin_at_stanford.edu |
Work
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2024.02 - Present Menlo Park, CA, USA
Postdoctoral Scholar
SUNCAT Center for Interface Science and Catalysis, Stanford University
Developing AI-driven navigation algorithm for catalytic experiments based on uncertainty quantification, and comparability assessment tools for catalytic performance results from multiple sources.
- Advisors: Dr. Kirsten T. Winther and Dr. Christopher J. Tassone
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2023.09 - 2024.01 Seoul, South Korea
Senior Researcher
Research Institute of Advanced Materials (RIAM), Seoul National University
Developing Bayesian optimization framework to optimize synthesis condition maximizing performances for a catalyst.
- Advisor: Prof. Jeong Woo Han
-
2012.03 - 2013.12 Seoul, South Korea
Sergeant
Capital Defense Command (CDC), Republic of Korea Army
Mandatory military service of 21 months in a chemical, biological, and radiological (CBR) unit
Education
-
2019.02 - 2023.08 Pohang, South Korea
Ph.D. in Chemical Engineering
Pohang University of Science and Technology (POSTECH)
Computational Catalysis
-
2016.03 - 2018.02 Daejeon, South Korea
M.S. in Energy, Environment, Water, and Sustainability (EEWS)
Korea Advanced Institute of Science and Technology (KAIST)
Computational Nanoscience
Awards
- 2023.02.01
Graduate Catalyst Research Award
KIChE Catalysis Division
Awarded to only two doctoral students in that year in recognition of their outstanding research achievements in the field of catalysis.
- 2022.06.01
NRF Ph.D. Fellowship
National Research Foundation of Korea (NRF)
~32,000 USD of research fund was provided for two years to support my Ph.D. research on AI-aided catalyst design.
- 2022.04.22
Hoimyung Graduate Research Award
KIChE Catalysis Division
Awarded to only one graduate student in catalysis division at a semi-annual KIChE conference in recognition of outstanding research achievement in the field of catalysis.
Languages
| Korean | |
| Native speaker |
| English | |
| Professional working proficiency |
Interests
| Computational Heterogeneous Catalysis | |
| Density Functional Theory (DFT) | |
| High-throughput Screening | |
| Ab-initio Thermodynamics | |
| Reaction Mechanism | |
| Proactive Catalyst Design |
| Artificial Intelligence | |
| Machine Learning (ML) | |
| Deep Learning (DL) | |
| Bayesian Optimization for Real Experimental Design | |
| Uncertainty Quantification | |
| AI-ready Data Curation |