Cong Liu (刘聪)

I am a second year PhD candidate at AMLab and AI4Science Lab at University of Amsterdam. My PhD project is about using deep learning tools for protein stabilization and peptide design. I work with Dr.Patrick Forré. I also collaborate with Janssen Vaccine Design. Prior to that, I obtained my Master's degree from University College London in Data Science and Machine Learning, and Bachelor's joint degree from UESTC (电子科技大学) and University of Glasgow in Communication Engineering.

Email  /  Google Scholar  /  Github

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News

[Dec 2024] I will be joining ByteDance AML AI4Science team as a research scientist intern!

[Aug 2024] I am happy to give a presentation related to Clifford Neural Nets and Message Passing Simplicial Networks at AGACSE2024.

[Jun. 2024] Our paper on Faster and Better Clifford GNNs was accepted by ICML 2024 GRaM workshop.

[Feb. 2024] Our paper "Clifford Group Equivariant Simplicial Message Passing Networks" was accepted by ICLR 2024!

Research

I'm interested in AI4Science, Machine Learning, Geometric Deep Learning, Protein Engineering, Generative Modelling and Efficient Deep Learning.

Multivector Neurons: Better and Faster O(n)-Equivariant Clifford Graph Neural Networks
Cong Liu, David Ruhe, Patrick Forré,
ICML GRaM workshop,2024
paper / code

This paper focuses on faster and performance-wise better Clifford GNNs.

Clifford Group Equivariant Simplicial Message Passing Networks
Cong Liu*, David Ruhe*, Floor Eijkelboom, Patrick Forré,
ICLR, 2024
paper / code

This paper proposes a general framework that considers both topological and geometric informatiom in general geometric graphs by leveraging Clifford group equivariant networks and simplicial message passing networks.