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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 Â鶹ËÞÉáµçÊÓ¾çCollege 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: Â鶹ËÞÉáµçÊÓ¾çat 60

21/06/2025 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.

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WolfWords Launch and Poetry Reading

27/06/2025 at 11.00

Please come and join us for the launch of this year's WolfWords poetry anthology, which brings together poems from the entire Â鶹ËÞÉáµçÊÓ¾çcommunity.

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Â鶹ËÞÉáµçÊÓ¾çChampagne Credit Ian Olsson

Wolfson's 60th Birthday Party

27/06/2025 at 18.30

Come party like it's 1965 as we celebrate Wolfson's 60th birthday!

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Graphic for "Cambridge Zero Community Day" on 28 June 2025 from 10:00 to 20:30, with the tagline "Forging a Future for Our Planet" and descriptors "Innovative, Inclusive, Impactful."

Cambridge Zero Community Day

28/06/2025 at 10.00

Â鶹ËÞÉáµçÊÓ¾çCollege will showcase its commitment to Sustainability and Conservation and Green Impact by exhibiting a number of projects around the College at the Cambridge Zero Community Day.

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A large stone church with a tall spire and ornate Gothic-style windows stands on a grassy hill under a clear blue sky.

Thaxted Festival Mass

29/06/2025 at 11.00

Haydn’s delightful Little Organ Mass will be sung by Â鶹ËÞÉáµçÊÓ¾çChamber Singers, accompanied by the historic Lincoln Organ played by Tom Williamson.

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