Ming Yang

Ph.D. Student @ Dalian University of Technology

I'm a Ph.D. student at Dalian University of Technology (DUT), China, advised by Prof. Yanqing Guo. I'm also a visiting student at Monash University, working with the Theta Team, an AI for Biology team co-supervised by Prof. Shirui Pan and A/Prof. Vivek Naranbhai. I maintain a close and ongoing collaboration with Assistant Professor Xin Zheng from RMIT University.
My research focuses on: (1) AI for Biology; (2) Protein Design. I work on machine-learning methods for computational protein design and related problems at the interface of AI and biomedicine, with papers accepted by ICML, KDD, and PAKDD.

Postdoctoral opportunities. As a Ph.D. candidate, I am seeking postdoctoral positions at the intersection of AI and biology, with a particular focus on protein design and drug discovery. I am open to discussing research fit and potential collaborations. Please feel free to email me at mingyanglucky@gmail.com for my full CV and research statement.

Ming Yang

Ph.D. Student

Dalian University of Technology, Dalian, China

mingyang@mail.dlut.edu.cn

News

[Aug 2026] Our paper “Graph Data-Centric Evaluator for Test-Time GNN Performance Estimation” was accepted by the 26th IEEE International Conference on Data Mining (ICDM 2026)!
[May 2026] My paper “Natural Language-powered Functional Protein Sequence and Structure Co-Design with Multi-modal Knowledge Fusion” was accepted by 32nd SIGKDD Conference on Knowledge Discovery and Data Mining - AI for Sciences Track (KDD 2026)!
[May 2026] My paper “Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models” was accepted by Forty-third International Conference on Machine Learning (ICML 2026)!
[May 2026] Our paper “LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation” was accepted by Forty-third International Conference on Machine Learning (ICML 2026)!
[Sep 2025] Our team was awarded NVIDIA Academic Grant Program: “Natural Language-Driven Protein Sequence and Structure Co-Design”.
[February 2025] Our paper “Efficient and Diverse De Novo Protein Backbone Design with SE (3)-Equivariant Diffusion” was accepted by Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) 2025!

Selected Research

AI4Science; Protein Design;

Protein Co-design Natural Language-powered Design

Natural Language-powered Functional Protein Sequence and Structure Co-Design with Multi-modal Knowledge Fusion

Ming Yang, Xin Zheng, Yi Li, Yizhen Zheng, Huan Yee Koh, Yanqing Guo, Jian Gao, Feng Xia, Shirui Pan.

32nd ACM SIGKDD Conference on Knowledge Discovery and Data Mining - AI for Sciences Track (KDD), 2026.

Paper Code

Memory-aware test-time scaling protein design visual abstract

Multi-Objective Protein Design Test-time Scaling

Multi-Objective Protein Design via Memory-Aware Test-Time Scaling in Diffusion Models

Ming Yang, Xin Zheng, Yi Li, Yizhen Zheng, Huan Yee Koh, Yanqing Guo, Xiaofeng Cao, Shirui Pan.

Forty-third International Conference on Machine Learning (ICML), 2026.

Paper Poster Code

LineageFlow family-aware protein sequence generation visual abstract

Protein Sequence Generation Flow Matching

LineageFlow: Flow Matching for High-Fidelity Family-Aware Protein Sequence Generation

Langzhang Liang, Ming Yang, Yi Feng, Junfan Li, Shirui Pan, Yinghui Xu, Tianlei Ying, Yizhen Zheng, Zenglin Xu.

Forty-third International Conference on Machine Learning (ICML), 2026.

Paper Code

SE(3)-equivariant diffusion protein backbone design visual abstract

Protein Backbone Design SE(3)-Equivariant Diffusion

Efficient and Diverse De Novo Protein Backbone Design with SE(3)-Equivariant Diffusion

Ruipeng Zhou, Ming Yang, Yi Li, Xin Zheng, Alan Wee-Chung Liew, Shirui Pan, Yanqing Guo.

Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), 2025.

Paper