Zixing Song

Dr Zixing Song

BEng PhD

  • Position Governing Body Fellow Junior Research Fellow
  • School Technology Department of Engineering
  • Email zs456@cam.ac.uk

Zixing is a machine learning researcher specializing in graph data mining with applications across multiple disciplines. His current research interests are centered on deep generative models in molecular science, emphasizing the development of structure-based drug design.

Zixing Song

Zixing received his Bachelor of Engineering from Southeast University in China, majoring in Computer Science. He then moved to Hong Kong and continued his academic journey at The Chinese University of Hong Kong, where he completed his doctoral studies in the Department of Computer Science and Engineering.

During his PhD, he conducted novel research focusing on the theoretical foundations of label-efficient learning on graph-structured data. This innovative framework demonstrates significant potential for interdisciplinary applications, with promising implications for social science, financial science, and material science research.

Currently, he works as a postdoctoral research associate in the Department of Engineering at the University of Cambridge where he continues to push the boundaries of machine learning. Simultaneously, his Junior Research Fellowship at Wolfson College underscores his commitment to advancing deep generative models, particularly in the emerging field of molecular science.

Zixing's current research focuses on advancing structure-based drug design through innovative deep generative models, particularly diffusion models. He aims to propose interdisciplinary approaches that bridge computational chemistry, generative AI, and molecular biology to develop more effective and efficient drug discovery methods.

His primary research objective centres on leveraging advanced deep generative models to generate and optimize molecular structures with potential therapeutic properties. Zixing investigates advanced geometric machine learning models and diffusion models for predicting protein-ligand interactions by incorporating the additional symmetry-based inductive bias.

By combining popular generative AI techniques with molecular science, his research aims to accelerate the identification and development of potential therapeutic compounds, potentially reducing the time and cost associated with traditional drug discovery processes with a huge impact.

What's on

A triptych of abstract images: a smooth round stone nestled in a curved rock, distorted eyeglass frames scattered on a white background, and a high-contrast black and white microscopic image resembling organic or cellular structures.

Art Exhibition: Wolfson at 60

19/07/2025 at 10.00

Celebrating Wolfson’s 60th anniversary year, this exhibition highlights the range of artistic disciplines and styles that have made up our exhibitions over the years.

View more
person takes a photo of a graduand wearing a black gown along with family members.

Graduation Ceremony

26/07/2025 at 09.00

Graduation ceremonies are the culmination of students’ hard work and commitment, and a moment to celebrate the completion of their Cambridge degree.

View more
A diverse group of people sits in rows of chairs, attentively listening during an indoor event or lecture.

Research Appetisers

05/08/2025 at 18.00

Come and hear our part-time students talk about their research at this informal evening of short presentations and friendly discussion.

View more
Wolfson College main drive in Autumn

Open Cambridge - Tree Trail

06/09/2025 at 10.00

A self-guided Tree Trail around the beautiful and varied garden 'rooms' of the grounds at Wolfson College.

View more
A handwritten poem on a black sign is mounted to a tree trunk, inviting readers to embrace the mysterious calm of evening dew.

Open Cambridge - Poetry Trail

12/09/2025 at 10.00

Follow our self-guided trail through the College gardens which feature extracts of poetry written by Wolfson members from our latest WolfWords poetry anthology, press play. 

View more
Show all

News

Show all