Soojung Yang
soojungy [at] mit [dot] edu / she/her
Hi, I am a third-year PhD candidate at MIT in Computational & Systems Biology program, advised by Prof. Rafael Gómez-Bombarelli. My research focuses on sampling protein conformational ensembles by leveraging molecular simulations and geometric machine learning.
Prior to joining grad school, I was a Drug Discovery & ML researcher of AITRICS, mentored by Prof. Sung Ju Hwang and Dr. Seongok Ryu. Before that, I received B.S. in Chemistry at KAIST where I was an undergrad researcher at ACE Lab, guided by Prof. Woo Youn Kim.
Linkedin / Google Scholar / twitter /
[News!] I'll be attending the IMSI workshop Learning Collective Variables and Coarse Grained Models (April 22-26) in Chicago in-person. If you are also going and want to grab a coffee there ☕ please reach out!
[News!] I am co-organizing the workshop of integrating Generative and Experimental platforms for bioMolecular design (GEM) at ICLR 2024 in Vienna, Austria. You can find more details about the workshop, including an exciting lineup of speakers and panelists who have been pioneers in the space, at https://www.gembio.ai/.
Research
Modeling of protein dynamics and conformational ensembles with molecular simulations and geometric machine learning.
2024
Soojung Yang, Juno Nam, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli
arXiv, 2024
2023
Regularized indirect learning improves phage display ligand discovery
Joseph S. Brown, Yitong Tseo, Michael A. Lee, Jeffrey Y.-K. Wong, Soojung Yang, Yehlin Cho, Chae Rin Kim, Andrei Loas, Ratmir Derda, Rafael Gómez-Bombarelli, Bradley L. Pentelute
ChemRxiv, 2023
Chemically Transferable Generative Backmapping of Coarse-Grained Proteins
Soojung Yang, Rafael Gómez-Bombarelli
ICML, 2023
2022
Seokhyun Moon1, Wonho Zhung1, Soojung Yang1, Jaechang Lim, Woo Youn Kim
Chemical Science, 2022, 1 co-first
2021
Hit and Lead Discovery with Explorative RL and Fragment-based Molecule Generation
Soojung Yang, Doyeong Hwang, Seul Lee, Seongok Ryu, Sung Ju Hwang
Neural Information Processing Systems (NeurIPS), 2021
2020
Comprehensive Study on Molecular Supervised Learning with Graph Neural Networks
Doyeong Hwang, Soojung Yang , Yongchan Kwon , Kyung Hoon Lee, Grace Lee, Hanseok Jo, Seyeol Yoon, Seongok Ryu
J Chem Inf Model, 2020 Dec 28;60(12):5936-5945.
A comprehensive study on the prediction reliability of graph neural networks for virtual screening
Soojung Yang, Kyung Hoon Lee, Seongok Ryu
arXiv preprint
2019
Coarse-Grained Self-Assembly Simulation in Two-Dimensional Lattice
Soojung Yang, Sangyeon Hwang, Woo Youn Kim
Poster presentation, The 1st Workshop of Center for Multiscale Chiral Architectures (Korea)
Invited Talks
Learning Collective Variables for Protein Folding with Labeled Data Augmentation through Geodesic Interpolation
MIT Computational & Systems Biology Student Seminar (Feb 2024)
Chemically Transferable Generative Backmapping of Coarse-Grained Proteins
Learning on Graphs and Geometry (LoG) Reading Group (Apr 2023)
POSTECH ML Learning Group Seminar (Apr 2023)
Flagship Pioneering Journal Club (May 2023)
Boston Protein Design and Modeling Club Seminar (Dec 2023)
Hit and Lead Discovery with Explorative RL and Fragment-based Molecular Generation
KAIST AI Student Colloquium (Oct 2021)
Selective Honors
Takeda Fellowship, 2023-2024
D.E.Shaw Research Graduate Women's Fellowship, 2023
ILJU Foundation Scholarship for Ph.D Studies, 2021-
Qualcomm-KAIST Innovation Awards, 2019
Shim Hong-Ku Scholarship (Dept. of Chemistry at KAIST), 2019
KAIST Presidental Fellowship, 2017-2020
National Presidental Scholarship for Science, 2017-2020
Hansung Scholarship for Gifted Students, 2015-2016
Experience
AITRICS
Seoul, Korea (Aug 2020 - Jun 2021)
ML Researcher
ACE (Advanced Computational Engine) Team, Dept. of Chemistry, KAIST
Daejeon, Korea (Jun 2018 - Aug 2020)
Undergraduate Researcher (supervised by Prof. Woo Youn Kim)
Wellman Center of Photomedicine, MGH
Boston, MA, U.S. (Jun 2019 - Aug 2019)
Research Intern (supervised by Prof. Walfre Franco)