Yu Li

It is my great pleasure to work with these talented and hard-working students!

Resources

In CUHK [Ph.D. student, Postdoc, Research assistants, Master students, Undergraduate students]

Ph.D. students (In alphabetical order)

Licheng Zong [B.E. (XJTU, Automation)]
Email: lczong21ATcse.cuhk.edu.hk

Siyuan Chen [B.E. (UESTC, Engineering&Finance)]
Email: siyuan.chenATkaust.edu.sa
KAUST Ph.D. student, co-supervised with Prof. Xin Gao

Wenkai Han [M.S. (KAUST, CS), B.S. (USTC, Biology, BEI Elite Class)]
Email: wenkai.hanATkaust.edu.sa
KAUST Ph.D. student, co-supervised with Prof. Xin Gao

Zhihang Hu [B.S. (SJTU, Math&CS)]
Email: zhhu21ATcse.cuhk.edu.hk
Co-supervised with Prof. Irwin King

Postdoc

Qingxiong Tan [Ph.D. (HKBU, CS), M.S. (HUST, CS), B.S. (CUMT, IE) ]
Email: csqxtanATgmail.com

Research assistants

2021

Yuqi Cheng [M.S.@Cornell (Computational Biology), B.S. (CAU, Biosciences&Data Science)]
Self-supervised contrastive learning for integrative single cell RNA-seq data analysis.
W Han, Y Cheng, J Chen, H Zhong, Z Hu, S Chen, L Zong, I King, X Gao^#, Y Li^#. Briefings in Bioinformatics(IF=13.994), 2022. Preprint.
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.
Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan^#, Y Li^#. Nature Communications, 2022. Preprint.

Shawn Chen[M.S.@Georgia Tech* (ECE), B.E. (XJTU, EE)]
USPNet: unbiased organism-agnostic signal peptide predictor with deep protein language model.
S Chen, Q Tan, J Li, Y Li. Submitted. Preprint.

Jiayang Chen[MPhil (BUT, ICE), B.E (BUT, EIE)]
Self-supervised contrastive learning for integrative single cell RNA-seq data analysis.
W Han, Y Cheng, J Chen, H Zhong, Z Hu, S Chen, L Zong, I King, X Gao^#, Y Li^#. Briefings in Bioinformatics(IF=13.994), 2022. Preprint.
Contact-Distil: Boosting Low Homologous Protein Contact Map Prediction by Self-Supervised Distillation.
Q Wang, J Chen, Y Zhou, Y Li, L Zheng, Z Li, S Cui. AAAI-22.

Junkang Wei [MPhil@CUHK* (Biology), B.S. (SYSU, Biology) ]
Protein-RNA interaction prediction with deep learning: Structure matters.
J Wei, S Chen, L Zong, X Gao^#, Y Li^#. Briefing in Bioinformatics(IF=13.994), 2021. Preprint.

Liang Hong[B.S.@NJU* (Kuang Yaming Honors School, Neuroscience & Artificial Intelligence)]
fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language.
L Hong, S Sun, L Zheng, Q Tan, Y Li. Submitted.

Pengfei Zhang[B.S. (USTC, CS)]
CLMB: deep contrastive learning for robust metagenomic binning.
P Zhang, Z Jiang, Y Wang, Y Li. The 26th Annual International Conference on Research in Computational Molecular Biology (RECOMB-22). Preprint

Qinze Yu[B.E.@UESTC (Software Engineering, International Elite Class)]
HMD-AMP: Protein Language-Powered Hierarchical Multi-label Deep Forest for Annotating Antimicrobial Peptides.
Q Yu, Z Dong, X Fan, L Zong, Y Li. Submitted. Preprint.

Yanshuo Chen [B.S.@THU (Biosciences)]
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.
Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan^#, Y Li^#. Nature Communications, 2022. Preprint.

Xuesong Wang[M.S. (USTC&Clemson, CS), B.E (WHU, Geomatics Engineering)]
Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.
X Wang, Z Hu, T Yu, R Wang, Y Wei, J Shu, J Ma, Yu Li. Submitted.

Yixuan Wang[B.S.@HIT (Math)]
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.
Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan^#, Y Li^#. Nature Communications, 2022. Preprint. CLMB: deep contrastive learning for robust metagenomic binning.
P Zhang, Z Jiang, Y Wang, Y Li. The 26th Annual International Conference on Research in Computational Molecular Biology (RECOMB-22). Preprint

Xingyu Fan[B.E.@UESTC (Software Engineering)]
HMD-AMP: Protein Language-Powered Hierarchical Multi-label Deep Forest for Annotating Antimicrobial Peptides.
Q Yu, Z Dong, X Fan, L Zong, Y Li. Submitted. Preprint.

Zhengyuan Jiang[B.E.@USTC (Information Science and Technology Elite Class)]
CLMB: deep contrastive learning for robust metagenomic binning.
P Zhang, Z Jiang, Y Wang, Y Li. The 26th Annual International Conference on Research in Computational Molecular Biology (RECOMB-22). Preprint

Yongshuo Zong[B.S. (Tongji University, CS) -> Ph.D. (The University of Edinburgh, CS)]
conST: an interpretable multi-modal contrastive learning framework for spatial transcriptomics.
Y Zong, T Yu, X Wang, Y Wang, Z Hu, Y Li. Submitted.

Yifan Deng[B.E. (WHU, EE)]
Working on protein-drug interaction. Manuscript in preparation.

Jianing Zhang[B.S. (ZJU, Biomedical Engineering)]
Working on scRNA-seq and scATAC-seq. Manuscript in preparation.

Master students

2021

Yumeng Wei
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.
Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan^#, Y Li^#. Nature Communications, 2022. Preprint. Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.
X Wang, Z Hu, T Yu, R Wang, Y Wei, J Shu, J Ma, Yu Li. Submitted.
Also Working on anti-CRISPR data.

Jin Xiao
Working web-server and database development.

Sheng Xu
Working on single-strand break prediction.

Undergraduate students

2021

Tingyang Yu
Professor Charles K. Kao Research Exchange Scholarship-2022 Summer
Best Project Award in Summer Research Project-2021 of CUHK
Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.
X Wang, Z Hu, T Yu, R Wang, Y Wei, J Shu, J Ma, Yu Li. Submitted.
Working on two more projects.

Jiuming Wang
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.
Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan^#, Y Li^#. Nature Communications, 2022. Preprint. Professor Charles K. Kao Research Exchange Scholarship-2022 Summer
Working on scHi-C data.

Jingchen Li
USPNet: unbiased organism-agnostic signal peptide predictor with deep protein language model.
S Chen, Q Tan, J Li, Y Li. Submitted. Preprint.
Working on one more projects.

Yunxiang Li
Deep autoencoder for interpretable tissue-adaptive deconvolution and cell-type-specific gene analysis.
Y Chen, Y Wang, Y Chen, Y Cheng, Y Wei, Y Li, J Wang, Y Wei, TF Chan^#, Y Li^#. Nature Communications, 2022. Preprint. Also Working on anti-CRISPR data.

Ruijie Wang
Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.
X Wang, Z Hu, T Yu, R Wang, Y Wei, J Shu, J Ma, Yu Li. Submitted.

Jialiang Guo & Zihao Huang
Worked on AMR prediction. Manuscript under preparation.

Myratgeldi Jumageldiyev & Manuchehr Tursunov
FYP students. Working on RNA SS prediction.

Ching Fung Yeung
FYP students. Working on single-cell data.

Zechen Li
FYP students. Working on single-cell data.

Zhenxi Wang
Working on sequence embedding.

Hanqun Cao
Working on generative model.

In KAUST (During Ph.D. study, before 2020)

Master students

Siyuan Chen
Lunar Features Detection for Energy Discovery via Deep Learning.
S Chen, Y Li, T Zhang, X Zhu, S Sun, X Gao. Applied Energy (IF=8.558), accepted.
Two more manuscripts under preparation.

Wenkai Han
HMD-ARG: hierarchical multi-task deep learning for annotating antibiotic resistance genes.
Y Li, Z Xu, W Han*, H Cao, R Umarov, A Yan, M Fan, H Chen, L Li, P Ho, X Gao. Microbiome (IF=11.607), 2021.

Rawan Albakri

Visiting students

Siyuan Chen, 2019, from UESTC
Lunar Features Detection for Energy Discovery via Deep Learning.
S Chen, Y Li, T Zhang, X Zhu, S Sun, X Gao. Applied Energy (IF=8.558), accepted.

Noura AlRasheed, Summer, 2019, KGSP student from UCSD

Longxi Zhou, Summer, 2018, from USTC

Ammar Alqatari , Summer, 2018, KGSP student from Stanford
He won the first place in KGSP Poster Competition in 2018.

Zhongxiao Li, Spring, 2018, from SUSTech
SupportNet: solving catastrophic forgetting in class incremental learning with support data.
Y Li, Z Li, L Ding, X Gao , arxiv.org/abs/1806.02942.
Deep learning in bioinformatics: introduction, application, and perspective in big data era.
Y Li, C Huang, L Ding, Z Li, Y Pan, X Gao. Methods, 2019. [PDF] [Code]
Cover article of the Methods issue: Deep Learning in Bioinformatics

Zhenzhen Zou, 2018, from CAS
mlDEEPre: Multi-functional enzyme function prediction with hierarchical multi-label deep learning.
Z Zou, S Tian, X Gao, Y Li#. Frontiers in Genetics, 2019. [PDF] [Server]