Shitong Luo

I am a first-year Ph.D. student at MIT EECS.

Previously, I received my B.S. degree from Peking University in 2021 and then spent three years at a biotech startup.


Favorite Publications (view all )
Projecting Molecules into Synthesizable Chemical Spaces
Projecting Molecules into Synthesizable Chemical Spaces

Shitong Luo*, Wenhao Gao*, Zuofan Wu*, Jian Peng, Connor W. Coley, Jianzhu Ma (* equal contribution)

International Conference on Machine Learning (ICML) 2024

ChemProjector "projects" any molecular graph into a new molecular representation called postfix notation of synthesis that guarantees synthesizability.

Projecting Molecules into Synthesizable Chemical Spaces

Shitong Luo*, Wenhao Gao*, Zuofan Wu*, Jian Peng, Connor W. Coley, Jianzhu Ma (* equal contribution)

International Conference on Machine Learning (ICML) 2024

ChemProjector "projects" any molecular graph into a new molecular representation called postfix notation of synthesis that guarantees synthesizability.

Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction
Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction

Shitong Luo, Yufeng Su, Zuofan Wu, Chenpeng Su, Jian Peng, Jianzhu Ma

International Conference on Learning Representations (ICLR) 2023

RDE estimates the distribution of amino acid side-chain conformations (rotamers), from which we can predict the effect of mutations on protein-protein interactions by comparing the entropy of the distributions.

Rotamer Density Estimator is an Unsupervised Learner of the Effect of Mutations on Protein-Protein Interaction

Shitong Luo, Yufeng Su, Zuofan Wu, Chenpeng Su, Jian Peng, Jianzhu Ma

International Conference on Learning Representations (ICLR) 2023

RDE estimates the distribution of amino acid side-chain conformations (rotamers), from which we can predict the effect of mutations on protein-protein interactions by comparing the entropy of the distributions.

Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures
Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures

Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma

Conference on Neural Information Processing Systems (NeurIPS) 2022

DiffAb is a diffusion model that can design new antibodies and optimize existing ones for antigen binding.

Antigen-Specific Antibody Design and Optimization with Diffusion-Based Generative Models for Protein Structures

Shitong Luo, Yufeng Su, Xingang Peng, Sheng Wang, Jian Peng, Jianzhu Ma

Conference on Neural Information Processing Systems (NeurIPS) 2022

DiffAb is a diffusion model that can design new antibodies and optimize existing ones for antigen binding.

Deep Learning-Guided Optimization of Human Antibody Against SARS-CoV-2 Variants with Broad Neutralization
Deep Learning-Guided Optimization of Human Antibody Against SARS-CoV-2 Variants with Broad Neutralization

Sisi Shan*, Shitong Luo*, Ziqing Yang*, Junxian Hong*, Yufeng Su, Fan Ding, Lili Fu, Chenyu Li, Peng Chen, Jianzhu Ma, Xuanling Shi, Qi Zhang, Bonnie Berger, Linqi Zhang, Jian Peng (* equal contribution)

Proceedings of the National Academy of Sciences (PNAS) 2022

Optimizing antibodies against SARS-CoV-2 variants with geometric deep learning, experimentally validated.

Deep Learning-Guided Optimization of Human Antibody Against SARS-CoV-2 Variants with Broad Neutralization

Sisi Shan*, Shitong Luo*, Ziqing Yang*, Junxian Hong*, Yufeng Su, Fan Ding, Lili Fu, Chenyu Li, Peng Chen, Jianzhu Ma, Xuanling Shi, Qi Zhang, Bonnie Berger, Linqi Zhang, Jian Peng (* equal contribution)

Proceedings of the National Academy of Sciences (PNAS) 2022

Optimizing antibodies against SARS-CoV-2 variants with geometric deep learning, experimentally validated.

A 3D Generative Model for Structure-Based Drug Design
A 3D Generative Model for Structure-Based Drug Design

Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng

Conference on Neural Information Processing Systems (NeurIPS) 2021

Learning the distribution of atom occurence in protein binding pockets to generate 3D molecules.

A 3D Generative Model for Structure-Based Drug Design

Shitong Luo, Jiaqi Guan, Jianzhu Ma, Jian Peng

Conference on Neural Information Processing Systems (NeurIPS) 2021

Learning the distribution of atom occurence in protein binding pockets to generate 3D molecules.

Diffusion Probabilistic Models for 3D Point Cloud Generation
Diffusion Probabilistic Models for 3D Point Cloud Generation

Shitong Luo, Wei Hu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 Oral

Simply a diffusion model for 3D point cloud generation.

Diffusion Probabilistic Models for 3D Point Cloud Generation

Shitong Luo, Wei Hu

IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) 2021 Oral

Simply a diffusion model for 3D point cloud generation.

All publications