Hyunsoo Park

I'm a postdoc researcher in Prof. Aron Walsh's team at Imperial College London. I received my PhD degree at KAIST, under guidance of Prof. Jihan Kim. During my PhD, I have the privilege of working with Prof. Berend Smit at EPFL as a visiting researcher.

I have strong interests in developing computational tools intergrating AI for materials design, including structure-property relationship, inverse design, and high-throughput screening.
Feel free to explore my Github profile!

Machine Learning

DAC-SIM: a molecular simulation package integrating machine learning force fields in MOFs for CO₂ Direct Air Capture

Accelerating CO₂ Direct Air Capture Screening for Metal-Organic Frameworks with a Transferable Machine Learning Force Field

Submitted (2024)

Chemeleon: a text-guided generative AI model for crystal structures

Exploration of crystal chemical space using text-guided generative artificial intelligence

Submitted (2024)

Perspective on generative AI for inorganic crystal materials

Has generative artificial intelligence solved inverse materials design?

Matter (2024)

Mapping inorganic crystal chemical space

Mapping Inorganic Crystal Chemical Space

Faraday Discussion (2024)

Developing a reinforcement learning framework for inverse design of Metal-Organic Frameworks

Inverse Design of Metal-Organic Frameworks for Direct Air Capture of CO₂ via Deep Reinforcement Learning

Digital Discovery (2024)

Developing a machine learning model to enable transfer learning in porous materials

Enhancing Structure–Property Relationships in Porous Materials through Transfer Learning and Cross-Material Few-Shot Learning

ACS Applied Materials & Interfaces (2023)

Developing a Transformer neural network for universal transfer learning of MOFs

A Multi-modal Pre-training Transformer for Universal Transfer Learning in Metal-Organic Frameworks

Nature Machine Intelligence (2023)

Developing a joint machine-learning/rule-based algorithm to automatically extract synthesis conditions from MOF papers and predict synthesizability

Mining Insights on Metal–Organic Framework Synthesis from Scientific Literature Texts

Journal of Chemical Information and Modeling (2022)

Developing a autoencoer neural network to improve initial guess of minimum energy path

Deep Learning-based Initial Guess for Minimum Energy Path Calculations

Korean Journal of Chemical Engineering (2020)

Molecular Simulation

Modeling various materials including MXene, MO₂C, graphene, MOF, and high-entropy alloy with DFT simulations by collaborating with experimental groups

Understanding Reaction Pathways in High Dielectric Electrolytes Using β-Mo₂C as a Catalyst for Li–CO₂ Batteries

ACS Applied Materials & Interfaces (2020)

Polyelemental Nanoparticles as Catalysts for a Li–O₂ Battery

ACS Nano (2021)

N–p-Conductor Transition of Gas Sensing Behaviors in Mo₂CT_x MXene

ACS Sensors (2022)

Material design

DFT simulation to calculate strain energy of interfacial stability for MOF@MOF structures

Computer-aided Discovery of Connected Metal-organic Frameworks

Nature Communications (2019)

High-through screening that uses MOFs as substrates in order to thoeretically allow hetero-epitaxial growth of 3D COFs

Computational Identification of Connected MOF@COF Materials

journal of Physical Chemistry C (2021)

Publications 📚

2025
18. Laudadio, G.^*, Lavarda, G.^*, Park, H.^*, Cranford, S. Reflections in search of faculty (and other) positions in Europe. Matter (2025).

2024
17. Lim, Y.^*, Park, H.^*, Walsh, A. and Kim, J. Achieving high-throughput screening of CO₂ Direct Air Capture materials with a transferable machine learning force field. ChemRxiv (2024).

16. Park, H.^†, Onwuli, A. and Walsh, A.^† Exploration of crystal chemical space using text-guided generative artificial intelligence. ChemRxiv (2024).

15. Park, H., Li, Z. and Walsh, A. Has generative artificial intelligence solved inverse materials design? Matter. 7, 2355-2367 (2024).

14. Park, H., Ouwuli, A., Butler, K. and Walsh, A. Mapping inorganic crystal chemical space. Faraday Discussion (2024).

13. Han, S., Kang, Y., Park, H., Yi, J., Park, G., and Kim, J. Multimodal Transformer for Property Prediction in Polymers . ACS Applied Materials & Interfaces. 16, 16853-16860 (2024).

12. Park, H.*, Majumdar, S.*, Zhang, X., Kim, J., and Smit, B. Inverse Design of Metal-Organic Frameworks for Direct Air Capture of CO₂ via Deep Reinforcement Learning. Digital Discovery. 4 (2024).

2023
11. Park, H.*, Kang, Y.*, and Kim, J. Enhancing Structure–Property Relationships in Porous Materials through Transfer Learning and Cross-Material Few-Shot Learning . ACS Applied Materials & Interfaces. 15, 56375-56385 (2023)

10. Kang, Y.*, Park, H.*, Smit, B., and Kim, J. A Multi-modal Pre-training Transformer for Universal Transfer Learning in Metal-Organic Frameworks. Nature Machine Intelligence. 5, 309-318 (2023).

2022
9. Choi, J., Chacon B., Park, H., Hantanasirisakul, K., Kim, T., Shevchuk, K., Lee, J., Hohyung Kang, Cho, S., Kim, J., Gogotsi, Y., Kim, S., and Jung, H. N–p-Conductor Transition of Gas Sensing Behaviors in Mo2CTx MXene. ACS Sensors. 8, 2225-2234 (2022).

8. Park, H.*, Kang, Y.*, Choe, W., and Kim, J. Mining Insights on Metal-Organic Framework Synthesis from Scientific Literature Texts. Journal of Chemical Information and Modeling. 62, 1190-1198 (2022).

2021
7. Jung, W., Park, H., Jang, J., Kim, D., Kim, D., Lim, E., Kim, J., Choi, S., Suk, J., and Kang, Y. Polyelemental Nanoparticles as Catalysts for a Li–O2 Battery. ACS nano. 15, 4235-4244 (2021).

6. Park, H., Kwon, O., and Kim, J. Computational Identification of Connected MOF@ COF Materials. The Journal of Physical Chemistry C. 125, 5897-5903 (2021).

5. Park, H., Lee, S., and Kim, J. Deep learning-based initial guess for minimum energy path calculations. Korean Journal of Chemical Engineering. 38, 406-410 (2021).

2020
4. Cho, H., Hyeon, S., Park, H., Kim, J., and Cho, E.S. Ultrathin Magnesium Nanosheet for Improved Hydrogen Storage with Fishbone Shaped One-Dimensional Carbon Matrix. ACS Applied Energy Materials. 3, 8143-8149 (2020).

3. Wu, M.*, Kim, J.*, Park, H.*, Kim, D., Cho, K., Lim, E., Chae, O., Choi, S., Kang, Y., and Kim, J. Understanding Reaction Pathways in High Dielectric Electrolytes Using β-Mo2C as a Catalyst for Li–CO₂ Batteries. ACS Applied Materials & Interfaces. 12, 32633-32641 (2020).

2019
2. Wu, M., Park, H., Cho, K., Kim, J., Kim, S., Choi, S., Kang, Y., Kim, J., and Jung, H. Formation of toroidal Li2O2 in non-aqueous Li–O2 batteries with Mo2CTx MXene/CNT composite. RSC Advances. 9, 41120-41125 (2019).

1. Kwon, O., Kim, J., Park, S., Lee, J., Ha, J., Park, H., Moon, H., and Kim, J. Computer-aided discovery of connected metal-organic frameworks. Nature communications. 10, 1-8 (2019).

Contact Me

Please email me at hpark@ic.ac.uk