Shuan Chen

PhD Student in KAIST CBE

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RESUME

Experience

Postdoctorial research, Seoul National University, South Korea
Sep. 2023 ~ present
Research topic: AI for chemical synthesis
Advisor: Yousung Jung

Research Intern, Academia Sinica, Taiwan
Jun. 2018 ~ Aug. 2018
Research topic: Lithium Sulfur Battery
Advisor: Chih-Wei Chu

EDUCATION

Ph.D. in Korea Advanced Institute of Science and Technology (KAIST), South Korea
Sep. 2020 ~ 2023
Major: Chemical and Biomolecular Engineering
Research topic: Machine learning: Reaction prediciton
Advisor: Yousung Jung

M.S. in Korea Advanced Institute of Science and Technology (KAIST), South Korea
Aug. 2018 ~ Jun. 2020
Major: Chemical and Biomolecular Engineering
Research topic: Machine learning: Drug interaction prediciton
Advisor: Hyun Uk Kim

(Exchange) M.S. in Royal Institute of Technology (KTH), Sweden
Sep. 2017 ~ Jan. 2018
Major: Energy Technology

B.S. in National Cheng Kung University (NCKU), Taiwan
Sep. 2013 ~ Jan. 2018
Major: Chemical Engineering
Research topic: Omniphobic polymer, Photocatalyst for CO2 reduction
Advisor: Yu-Min Yang, Jih-Jen Wu

Publications

  1. S Chen and Y Jung, “Assessing the Extrapolation Capability of Template-Free Retrosynthesis Models”, arXiv 2024
  2. S Chen, S An, R Babazade, and Y Jung, “Precise Atom-to-Atom Mapping for Organic Reactions via Human-in-the-Loop Machine Learning”, Nature Communications 2024
  3. S Chen and Y Jung, “A Generalized Template-based Graph Neural Network for Accurate Organic Reactivity Prediction”, Nature Machine Intelligence 2022
  4. S Chen and Y Jung, “Deep Retrosynthetic Reaction Prediction using Local Reactivity and Global Attention”, JACS Au 2021

Conference - Talks

  1. S Chen and Y Jung,”Precise atom-to-atom mapping for chemical reaction data via human-machine collaboration”, ACS Fall Meeting, online, 2023
  2. S Chen and Y Jung,”Designing chemist-like machine intelligence for retrosynthesis and reaction outcome prediction”, ACS Fall Meeting, Chicago, US, 2022
  3. S Chen and Y Jung,”Designing Chemist-Like AI for retrosynthesis prediction”, Nano Korea, Youngsan, Korea, 2022

Conference - Posters

  1. S Chen and Y Jung, “Assessing the Extrapolation Capability of Template-Free Retrosynthesis Models”, NeurIPS AI4Materials, online, 2023
  2. S Chen and Y Jung, “Learning single-step retrosynthesis with simulated reactions” ICLR AI4Materials, online, 2023
  3. S Chen and H Kim, “Designing Novel Functional Peptides by Manipulating a Temperature in the Softmax Function Coupled with Variational Autoencoder”, IEEE Big Data, Los Angeles, US, 2019
  4. S Chen and H Kim, “A simple, but powerful machine learning method for efficient processing of chemical structures”, KIChE Fall Meeting and International Symposium, Daejeon, Korea, 2019.

Awards

  1. 2023 Oral Presentation Prize, COMP Virtual Asia-Pacific Symposium, ACS Fall
  2. 2022 Microsoft Research Asia Fellowship (Finalist)
  3. 2022 Young Scientis Awards, Nano Korea (Finalist)
  4. 2022 Daewoong AI & Big Data Global Scholarships
  5. 2021 Daewoong AI hackathon: 1st prize
  6. 2021 Samsung AI callenge (prediction of molecular T1-S1 enegy gap): Rank 8
  7. 2020 KAIST-Taiwan Top University Scholarships (教育部與世界百大合作設置獎學金)