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

Resources

• [On Ph.D. study: from the perspective of a fresh Ph.D. and a junior faculty member]
• [Ph.D. study in CSE@CUHK: especially at AIH group]
• [Resources from Fredo Durand]
• [Advice compiled by Michael Ernst]
• [Advice compiled by CS@Columbia]

In CUHK [Ph.D. student, Postdoc, Research assistants, Alumni]

Ph.D. students

Yimin Fan [2023, B.E. (USTC, AI&IS, School of the Gifted Young, 3*National Scholarship)]
Email: fym0503ATmail.ustc.edu.cn

Jiuming Wang [2023, HKPFS, B.E. (CUHK, AIST, ELITE Steam, HK Government Scholarship-UG)]
Email: 1155141482ATlink.cuhk.edu.hk

Dongchen He [2023, B.E. (NJU, EE)]
Email: dc23.heATgmail.com

Jiyue Jiang [2023, MPhil (HKU, CS)]
Email: jiangjyATconnect.hku.hk

Xiang Xiao [2023, M.S. (HKU, Statistics)]
Email: 1155107832ATlink.cuhk.edu.hk
CUHK Medicine Ph.D. student, co-supervised with Prof. Louis Lau

Liang Hong [2022, B.S. (NJU, Kuang Yaming Honors School, Neuroscience & Artificial Intelligence)]
Email: liang.hongATlink.cuhk.edu.hk

Qinze Yu [2022, B.E. (UESTC, Software Engineering, International Elite Class, National Scholarship)]
Email: qinze979ATgmail.com

Yixuan Wang [2022, B.S. (HIT, Math, National Scholarship)]
Email: yixuan000518ATgmail.com

Xuesong Wang [2022, M.S. (USTC&Clemson, CS)]
Email: xuesonwATlink.cuhk.edu.hk

Chuanyang Zheng [2021, B.S. (HKBU, CS)]
Email: cyzheng21ATlink.cuhk.edu.hk

Zhihang Hu [2021, B.S. (SJTU, Math&CS)]
Email: zhhu21ATcse.cuhk.edu.hk
Co-supervised with Prof. Irwin King

Licheng Zong [2021, 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 [B.S. (USTC, Biology, BEI Elite Class)]
Email: wenkai.hanATkaust.edu.sa
KAUST Ph.D. student, co-supervised with Prof. Xin Gao

Postdoc

Lei Li [Ph.D. (THU, CST)]
Email: lei-li18ATmails.tsinghua.edu.cn


Tiantian Zhu [Ph.D. (HIT(SZ), CST)]
Email: zhu.tiantian110ATgmail.com


Qing Li [Ph.D. (CAS, CST, National Scholarship)]
Email: liqingchduAT163.com


Qingxiong Tan [Ph.D. (HKBU, CS)]
Email: csqxtanATgmail.com

Research assistants

Jiayang Chen[MPhil (BUT, ICE)]
AcrNET: Predicting anti-CRISPR with Deep Learning.
Y Li, Y Wei, S Xu, Q Tan, L Zong, J Wang, Y Wang, J Chen, L Hong, Y Li^#. Bioinformatics, 2023. [Full text]
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.


Han Huang [Ph.D.@(BUAA, CSE)]


Tianhao Chen [B.S. (CUHK, CS)]

Lingshi Meng [B.S.@(CUHK, CS)]

Yuxin Li [M.S. (CUHK, CS)]

Meitong Liu [B.S.@(HKU, CS)]

Jiaqi Dong [M.S.@(NUS, BMI)]

Hanlin Zhang [B.S.@(TJU, CS)]

Junbo Shen [B.S.@(Washington University in St. Louis, CS)]

Mufan Zhang [B.S.@(NTU, CS)]

Alumni (The list may not be up-to-date or complete)

Dongchen He (RA) [B.S. (NJU, EE) -> Ph.D. (CUHK, AIH)]


Yuqi Cheng (RA) [B.S. (CAU, Biosciences&Data Science), M.S.@Cornell (Computational Biology) -> Ph.D. (Georgia Tech, CSE)]
A scalable sparse neural network framework for rare cell type annotation of single-cell transcriptome data.
Y Cheng, X Fan, J Zhang, Y Li^#. Communications Biology, 2023. [Full text]
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 (RA) [B.E. (XJTU, EE) -> M.S. (Georgia Tech, ECE)]
USPNet: unbiased organism-agnostic signal peptide predictor with deep protein language model.
S Chen, Q Tan, J Li, Y Li. Preprint.


Junkang Wei (RA) [B.S. (SYSU, Biology), MPhil@CUHK (Biology) -> Ph.D. (University of Michigan-Ann Arbor, Computational 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.

Liang Hong (RA) [B.S. (NJU, Kuang Yaming Honors School, Neuroscience & Artificial Intelligence) -> Ph.D. (CUHK, AIH)]
fastMSA: Accelerating Multiple Sequence Alignment with Dense Retrieval on Protein Language.
L Hong, S Sun, L Zheng, Q Tan, Y Li.


Pengfei Zhang (RA) [B.S. (USTC, CS) -> Ph.D. (UCI, 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 (RA) [B.E. (UESTC, Software Engineering, International Elite Class) -> Ph.D. (CUHK, AIH)]
HMD-AMP: Protein Language-Powered Hierarchical Multi-label Deep Forest for Annotating Antimicrobial Peptides.
Q Yu, Z Dong, X Fan, L Zong, Y Li. Preprint.


Yanshuo Chen (RA) [B.S. (THU, Biosciences) -> Ph.D. (PITT, CS)]
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 (RA) [M.S. (USTC&Clemson, CS) -> Ph.D. (CUHK, AIH)]
Con-AAE: Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.
X Wang, Z Hu, T Yu, Y Wang, R Wang, Y Wei, J Shu, J Ma, Y Li^#. Bioinformatics, 2023. [Full text]


Yixuan Wang (RA) [B.S. (HIT, Math) -> Ph.D. (CUHK, AIH)]
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 (RA) [B.E. (UESTC, Software Engineering) -> Ph.D. (CUHK, CSE)]
A scalable sparse neural network framework for rare cell type annotation of single-cell transcriptome data.
Y Cheng, X Fan, J Zhang, Y Li^#. Communications Biology, 2023. [Full text]


Zhengyuan Jiang (RA) [B.E. (USTC, Information Science and Technology Elite Class) -> Ph.D. (Duke, ECE)]
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 (RA) [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.

Yifan Deng (RA) [B.E. (WHU, EE) -> Ph.D. (University of Wisconsin-Madison, CS)]


Jianing Zhang (RA) [B.S. (ZJU, Biomedical Engineering)]
Y Cheng, X Fan, J Zhang, Y Li^#. Communications Biology, 2023. [Full text]


Yumeng Wei (M.S.)
AcrNET: Predicting anti-CRISPR with Deep Learning.
Y Li*, Y Wei*, S Xu, Q Tan, L Zong, J Wang, Y Wang, J Chen, L Hong, Y Li^#. Bioinformatics, 2023. [Full text]
X Wang, Z Hu, T Yu, Y Wang, R Wang, Y Wei, J Shu, J Ma, Y Li^#. Bioinformatics, 2023. [Full text]
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. Con-AAE: Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.


Jin Xiao (M.S.) [M.S. (CUHK, CSE) -> Ph.D. (HKBU, CS)]


Sheng Xu (M.S.) [M.S. (CUHK, CSE) -> Ph.D. (Fudan, CS)]
AcrNET: Predicting anti-CRISPR with Deep Learning.
Y Li, Y Wei, S Xu, Q Tan, L Zong, J Wang, Y Wang, J Chen, L Hong, Y Li^#. Bioinformatics, 2023. [Full text]


Yerzhan ABDRAKHMANOV (UG)
Best Project Award in Summer Research Project-2022 of CUHK


Tingyang Yu (UG) [B.S. (CUHK, IE) -> Ph.D. (EPFL, CS)]
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.
Con-AAE: Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration.
X Wang, Z Hu, T Yu, Y Wang, R Wang, Y Wei, J Shu, J Ma, Y Li^#. Bioinformatics, 2023. [Full text]


Jiuming Wang (UG) [B.S. (CUHK, AIST) -> Ph.D. (CUHK, AIH)]
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


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

Yunxiang Li (UG) [B.S. (CUHK, CS) -> M.S. (MBZUAI, CS)]
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 (UG) [B.S. (CUHK, CS) -> M.S. (HKU, CS)]
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.


Jialiang Guo & Zihao Huang
Worked on AMR prediction.

Myratgeldi Jumageldiyev (UG) & Manuchehr Tursunov (UG) [B.S. (CUHK, CS) -> Industry]
FYP students. Worked on RNA SS prediction.

Hanqun Cao (UG) [B.S. (CUHK, CS) -> Ph.D. (CUHK, CSE)]

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

Master students

Siyuan Chen
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, L Hong, TF Chan, I King, X Gao^#, Y Li^#. Briefing in Bioinformatics, 2022. Deep learning identifies and quantifies recombination hotspot determinants.
Y Li*,^#, S Chen*, T Rapakoulia, H Kuwahara, KY Yip, X Gao^#. Bioinformatics, 2022.
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), 2021.


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]