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Hi! I'm Jiyun Song, a Chemical Engineering and Computer Science student at the Sogang University, South Korea.
The remarkable ability of AI to analyze data, identify patterns, and generate new insights has captivated me, fueling my drive for research. To deepen my understanding and enhance my research in materials science with AI, I pursued a double major, accumulating extensive knowledge in both fields. With 184 credits, I am set to graduate with a solid foundation in materials informatics.
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Have you ever wondered how all the scientific formulas we know were created? Modern equations might emerge from mathematical combinations of existing principles, but foundational laws like Boyle's and Charles' laws were discovered through countless observations. Throughout scientific advancement, data science has been a silent yet steadfast companion. Today, we have the most powerful data processing and statistical tool in human history: AI! Imagine the possibilities of AI in analyzing human chemical knowledge and discovering new ones—it could reveal truly extraordinary insights!
Aside from my studies in Chemical Engineering and Computer Science, I love many things: painting, knitting, crocheting, and gardening. As a passionate member of Sogang University's art club, GangMi, I’ve participated in four club exhibitions. My creative side does not have a boundary!
Undergraduate Research Assistant @ Sogang U
Mar 2023 - Jul 2023, Mar 2024 - Present
At the Artificial Intelligence & Energy Materials Group, led by Prof. Seoin Back, I worked with VASP, ASE, and Pymatgen to calculate binding energies between catalytic surfaces and intermediates like H, OH, and OOH. I also developed a non-relational database schema for catalyst synthesis information and created code to extract synthesis-relevant data from research papers using Chat GPT fine-tuning. In this ongoing project, I led by directly contacting publishers like Elsevier to access their Text and Data Mining (TDM) services and independently programming all codes to retrieve and extract necessary content. Currently, I am building a catalyst synthesis database, which connects to my ongoing research paper.
Undergraduate Research Assistant @ U of Utah
Aug 2023 - Dec 2023
At the Dr. Wang Research Group, led by Prof. Yunshan Wang, I collaborated on a project aimed at enhancing the performance of TiO₂ photocatalysts by integrating plasmonic nanostructures to improve UV light absorption and catalytic efficiency. My work involved testing the effectiveness of these aluminum nanoparticle-enhanced TiO₂ photocatalysts using UV-vis spectroscopy and the Beer-Lambert law to measure absorption changes. During UV-vis measurement sessions, I enjoyed discussing experimental improvements with team members to refine our methods. Additionally, I prepared PDMS samples utilizing techniques such as spin coating, e-beam deposition, and plasma cleaning, gaining hands-on experience with material fabrication processes.