Zheng Sun

PHD STUDENT

https://scholar.google.com/citations?user=UI_cno8AAAAJ&hl=en

Company:King Abdullah University of Science and Technology
Role:PHD STUDENT

Zheng Sun

PHD STUDENT

RESEARCH
Zheng’s research lies at the intersection of artificial intelligence and systems biology, with three primary focus areas:

Spatial Transcriptomics

Development of self-supervised and graph-based models for reconstructing gene expression in 3D tissue architecture.

Integration of optimal transport, vector field networks, and diffusion processes to model spatial and temporal gene dynamics.

Protein Modeling and Design

Application of geometric deep learning and generative models (e.g., Vector Field Networks, diffusion models) for predicting and designing protein structures, including antibody interfaces and multimeric assemblies.

Single-Cell Causal Inference

Leveraging deep learning and language models to uncover regulatory programs from high-dimensional single-cell data.

Exploring causal gene networks and perturbation effects through interpretable and generative AI frameworks.

BIOGRAPHY
Zheng Sun is a PhD student in the Biological and Environmental Science and Engineering at KAUST, working under the supervision of Prof. Jesper Tegnér. His research focuses on developing artificial intelligence models for life sciences, with particular emphasis on spatial transcriptomics, protein design, and single-cell biology. His work integrates vector field networks, diffusion models, and large language models to explore causality in biological systems.
Prior to KAUST, Zheng earned two master’s degrees in Computer Science from Swansea University (UK), where he developed deep learning systems for protein modelling. He has co-authored papers in top machine learning venues such as ICLR and ICML, including a Spotlight presentation, and currently serves as a reviewer for NeurIPS 2025. His interdisciplinary background spans mechanical engineering, data science, and computational biology.

Zheng Sun

PHD STUDENT

Zheng Sun

PHD STUDENT

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