Soojung Yang

Research

2026

Learning Collective Variables from BioEmu with Time-Lagged Generation

Seonghyun Park, Kiyoung Seong, Soojung Yang, Rafael Gómez-Bombarelli, Sungsoo Ahn

ICLR 2026

2025

Universally Converging Representations of Matter Across Scientific Foundation Models

Sathya Edamakada1, Soojung Yang1*, Ben Blaiszik, Ju li, Rafael Gómez-Bombarelli*

NeurIPS AI4Mat Workshop, NeurIPS UniReps Workshop (Oral Spotlight), 1co-first, *co-corresponding

👉 Representations of matter (molecules, materials, proteins, ...) are converging to an optimal solution space. 

Guided Diffusion for A Priori Transition State Sampling

Hyukjun Lim1, Soojung Yang1*, Lucas Pinede1, Miguel Steiner, Yuanqi Du, Rafael Gómez-Bombarelli*

NeurIPS FPI & AI4Mat Workshop (Oral Spotlight), 1co-first, *co-corresponding

Bayesian Optimization for Biochemical Discovery with LLMs

Mattias Akke, Soojung Yang*, Jurgis Ruza, Jinyeop Song, Elton Pan, Rafael Gómez-Bombarelli*

NeurIPS AI4Science (Spotlight) & SPIGM Workshop, *co-corresponding

Unifying Force Prediction and Molecular Conformation Generation Through Representation Alignment

Lucas Pinede1, Soojung Yang*1, Juno Nam, Rafael Gómez-Bombarelli*

ICML GenBio Workshop, 1co-first, *co-corresponding

👉 Training of diffusion model-based Boltzmann emulator can be accelerated via alignment with pretrained MLIPs. 

Scalable emulation of protein equilibrium ensembles with generative deep learning

Sarah Lewis1, Tim Hempel1, José Jiménez Luna1, Michael Gastegger1, Yu Xie1, Andrew Y. K. Foong1, Victor García Satorras1, Osama Abdin1, Bastiaan S. Veeling1, Iryna Zaporozhets, Yaoyi Chen, Soojung Yang, Arne Schneuing, Jigyasa Nigam, Federico Barbero, Vincent Stimper, Andrew Campbell, Jason Yim, Marten Lienen, Yu Shi, Shuxin Zheng, Hannes Schulz, Usman Munir, Cecilia Clementi, Frank Noé

Science (front cover!)

👉 I developed PPFT (Property Prediction Fine-Tuning), a method to fine-tune a diffusion model with ensemble statistics. 

Transferable Learning of Reaction Pathways from Geometric Priors

Juno Nam, Miguel Steiner, Max Misterka, Soojung Yang, Avni Singhal, Rafael Gómez-Bombarelli

The Journal of Physical Chemistry Letters

Flow matching for accelerated simulation of atomic transport in crystalline materials

Juno Nam, Sulin Liu, Gavin Winter, KyuJung Jun, Soojung Yang, Rafael Gómez-Bombarelli

Nature Machine Intelligence

2024

Probing the Embedding Space of Protein Foundation Models through Intrinsic Dimension Analysis

Soojung Yang, Juno Nam, Tynan Perez, Jinyeop Song, Xiaochen Du, Rafael Gómez-Bombarelli

NeurIPS AIDrugX Workshop

👉 Protein foundation models are aligned with each other, across modalities and architectures. 

Learning Collective Variables for Protein Folding with Labeled Data Augmentation through Geodesic Interpolation

Soojung Yang1, Juno Nam1, Johannes C. B. Dietschreit, Rafael Gómez-Bombarelli

JCTC, 1co-first 

👉 Geodesic interpolations can serve as a prior for CV for accelerated MD simulations.

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 

Chemically Transferable Generative Backmapping of Coarse-Grained Proteins

Soojung Yang, Rafael Gómez-Bombarelli

ICML

👉 Protein local fluctuations can be transferably learned from a structural ensemble database. 

2022

PIGNet: A physics-informed deep learning model toward generalized drug-target interaction predictions

Seokhyun Moon1, Wonho Zhung1, Soojung Yang1, Jaechang Lim, Woo Youn Kim

Chemical Science, 1co-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

NeurIPS

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

A comprehensive study on the prediction reliability of graph neural networks for virtual screening

Soojung Yang, Kyung Hoon Lee, Seongok Ryu

arXiv 

Community Service

• Program chair and organizer of the integrating Generative and Experimental platforms for bioMolecular design (GEM) at ICLR 2024 in Vienna, ICLR 2025 in Singapore, and ICLR 2026 in Rio.  

• Program chair and organizer of the AI for Science workshop at ICML 2026 in Seoul.  

Experience

Microsoft Research AI4Science

Research Intern (Mentor: Yu Xie, PI: Frank Noe)

AITRICS

ML Researcher

ACE (Advanced Computational Engine) Team, Dept. of Chemistry, KAIST 

Undergraduate Researcher (supervised by Prof. Woo Youn Kim)

Wellman Center of Photomedicine, MGH

Research Intern (supervised by Prof. Walfre Franco)

Selective Honors

• FutureHouse Postdoctoral Fellow, 2026-

• Takeda Fellowship, 2023-2024

• D.E.Shaw Research Graduate Women's Fellowship, 2023

• Ilju Foundation Scholarship for Ph.D Studies, 2021-2025