Zhao Yang (杨钊)

I am a fourth-year PhD student at the Gaoling School of Artificial Intelligence, Renmin University of China, supervised by Prof. Bing Su. I also work closely with Prof. Chuan Cao.

My research interests focus on Language Models and Diffusion Models, with a particular emphasis on their applications in AI4Science.

I expect to graduate in 2027 and will be entering the job market. Feel free to reach out!

yangyz1230@gmail.com  /  Google Scholar  /  GitHub  /  CV

Research

(* indicates equal contribution)

Preprints

We present D3LM, a discrete DNA diffusion language model that unifies bidirectional DNA understanding and DNA generation.

We investigate the ability of diffusion-based language models to implicitly determine the optimal infilling lengths.

A sequence-based science foundation model that unifies molecules, proteins, DNA and RNA for cross-domain scientific discovery.

A hybrid Transformer-Mamba2 long-context DNA language model for genomic understanding and generation.

We propose ProtDETR, a novel framework that reframes enzyme function prediction as an object detection problem by identifying active sites as "objects".

We propose MoMu, a foundation model associating molecular graphs with natural language, enabling multimodal understanding in molecular science.

2026

We propose Prism, a multimodal framework that effectively integrates diverse epigenomic signals with DNA sequences for gene expression prediction, achieving state-of-the-art performance.

2025

We leverage MoE to better model cross-species and cross-genomic profile information in genomic data and hence make sequence-to-function genomic models to be powerful DNA foundation models.

We propose a reinforcement learning framework for designing regulatory DNA sequences using transcription factor binding site rewards.

2023

A text-driven diffusion-based framework for synthesizing long-term human motions, achieving coherent and realistic sequences.

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