Yehlin Cho

Research Focuses

• Machine Learning for Protein Engineering

• Protein Stability Prediction

• De novo Protein Design

• Enzyme Engineering

BoltzDesign1: Inverting All-Atom Structure Prediction Model for Generalized Biomolecular Binder Design

Yehlin Cho,Martin Pacesa, Zhidian Zhang, Bruno Correia, Sergey Ovchinnikov

bioRxiv, 2025.04

Artificial intelligence methods for protein folding and design

Zhidian Zhang, Chenxi Ou, Yehlin Cho, Yo Akiyama, Sergey Ovchinnikov

Current Opinion in Structural Biology, 2025

Implicit modeling of the conformational landscape and sequence allows scoring and generation of stable proteins

Yehlin Cho, Justas Dauparas, Kotaro Tsuboyama, Gabriel Rocklin, and Sergey Ovchinnikov, 

bioRxiv, 2024.09. 30.615802

BindCraft: one-shot design of functional protein binders

Martin Pacesa, Lennart Nickel, Joseph Schmidt, Ekaterina Pyatova, Christian Schellhaas, Lucas Kissling, Ana Alcaraz-Serna, Yehlin Cho, Kourosh H Ghamary, Laura Vinue, Brahm J Yachnin, Andrew M Wollacott, Stephen Buckley, Sandrine Georgeon, Casper A Goverde, Georgios N Hatzopoulos, Pierre Gonczy, Yannick D Muller, Gerald Schwank, Sergey Ovchinnikov, Bruno E Correia

bioRxiv, 2024.09. 30.615802

Enhancing Protein Design Robustness through Noise-Informed Sequence Design

Yehlin Cho, Christopher Frank, Sergey Ovchinnikov,

ICML 2024 AI for Science Workshop

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 Gomez-Bombarelli, Bradley L Pentelute

ChemRxiv, 2023 

Enhanced Vaccine Immunogenicity Enabled by Targeted Cytosolic Delivery of Tumor Antigens into Dendritic Cells

Nicholas L Truex, Aurélie Rondon, Simon L Rössler, Cameron C Hanna, Yehlin Cho, Bin-You Wang, Coralie M Backlund, Emi A Lutz, Darrell J Irvine, Bradley L Pentelute

ACS Central Science 9 (9), 1835-1845

FRACTAL: Signal amplification of immunofluorescence via cyclic staining of target molecules

Yehlin Cho, Junyoung Seo, Yeonbo Sim, Jinkyoung Chung, Chan E Park, Chun Gwon Park, Doory Kim, Jae-Byum Chang

Nanoscale 12 (46), 23506-23513

Simultaneous amplification of multiple immunofluorescence signals via cyclic staining of target molecules using mutually cross-adsorbed antibodies

Haemin Yeon, Yehlin Cho, Junyoung Seo, Yeonbo Sim, Jae-Byum Chang

Scientific reports 12 (1), 8780

Education

Massachusetts Institute of Technology                                                               

Ph. D. in Department of Materials Science and Engineering (DMSE)                                         

Sep. 2021 - Current

Korea Advanced Institute of Science and Technology (KAIST)                    

B.S. in Materials Science and Engineering (MSE)                                                 

Mar. 2017 – Feb. 2021

Graduated as the 1st rank student of the department

Experience

Xaira                                              

Seattle (Jun 2025 - Aug 2025)

AI Research Intern (Mentors : Justas Duaparas and  Philip Leung)

Invited Talks & Seminars

EMBO Practical Course, Integrative modelling of biomolecular interactions, Izmir, Türkiye, Oct. 2025 

• Structure Prediction and Protein Design

Winter RosettaCon 2025, Boston, MA, March. 2025

• Structure-Aware Language Models Trained on Ultra-Mega-Scale Metagenomic Data Improve Protein Folding Stability Prediction

Summer RosettaCon 2024, Seattle, WA, Aug. 2024

• Enhancing Protein Design Robustness through Noise-Informed Sequence Design

Machine Learning in Biology Working Group (MLBWG), Cambridge, MA, Apr. 2024

• Modeling the joint probability distribution of structure and sequence is critical for protein design

Poster Presentation

MOML 2024, Cambridge, MA, Nov. 2024

• Retraining ProteinMPNN with Family-Specific Proteins for Enhanced Thermostability and Enzymatic Activity of Lysozyme at Elevated Temperatures.

ICML 2024, Vienna, Aug.2024

ISMB 2024, Montreal, Canada, July. 2024 (BEST PDB Poster Award)

• Enhancing Protein Design Robustness through Noise-Informed Sequence Design

Winder RosettaCon 2024, Cambridge, MA, March. 2024

• Modeling the joint probability distribution of structure and sequence is critical for protein design

Awards and Honors

• 2025 Summer RosettaCon Poster Award (Aug 2025)

• MIT-Takeda Fellowship (Sep 2024 - 2025)

• MOGAM-KASBP Scholarship  (Oct. 2022)

• SBS Foundation Scholarship (Sep. 2021)

Community Service

• MIT The Department Committee on Graduate Studies Representative (Aug. 2022 – Aug. 2024)

• MIT Polymer Day Symposium: Polymer Day 2023 Organizing Board (Aug. 2022 – Aug. 2023)