Licheng Zong(宗理成)
Ph.D. Candidate
Artificial Intelligence in Healthcare Group (AIH)
Department of Computer Science and Engineering (CSE)
The Chinese University of Hong Kong (CUHK)
Office: Rm 1026, Ho Sin-Hang Engineering Building, CUHK
Shatin, N.T., Hong Kong SAR
Email: lczong@link.cuhk.edu.hk
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Research Interests |
I am working at the intersection between Deep Learning and Bioinformatics, including:
- Computational Methodology in Bioinformatics
- Healthcare-Related applications of Deep Learning
- Electronic Health Record Analysis
- Nanopore Sequencing Data Analysis
- GNN in Drug Discovery
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Short Bio |
I started to pursue my Ph.D. degree in the Department of Computer Science and Engineering,
The Chinese University of Hong Kong (CUHK-CSE) from Aug 2021.
I'm a Member of AIH Group, advised by Prof.
Yu Li.
I obtained my Bachelor degree in Automation Science and Technology at Xi'an Jiaotong University in July 2021.
I graduated from Hefei No.1 School, a fantastic High School in July 2014.
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Education |
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Experience
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Publications (*equal contribution, #corresponding)
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Interpretable RNA Foundation Model from Unannotated Data for Highly Accurate RNA Structure and Function Predictions
Jiayang Chen*, Zhihang Hu*, Siqi Sun*#, Qingxiong Tan, Yixuan Wang, Qinze Yu,
Licheng Zong, Liang Hong, Jin Xiao, Irwin King
Yu Li#
arXiv Preprint, 2022
bibtex
We propose a novel RNA foundation model (RNA-FM) that can serve as the foundational model for the field.
The model takes advantage of all the 23 million non-coding RNA sequences through self-supervised learning.
It's effective in downstream tasks including secondary/3D structure prediction, protein-RNA binding preference modeling, and 5' UTR-based mean ribosome loading prediction.
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DeepAcr: Predicting Anti-CRISPR with Deep Learning
Yunxiang Li*, Yumeng Wei*, Qingxiong Tan,
Licheng Zong,
Yixuan Wang, Jiayang Chen,
Yu Li#
bioRxiv Preprint, 2022
bibtex
We propose a novel deep learning method for anti-CRISPR analysis (DeepAcr),
which achieves impressive performance. On both the cross-fold and cross-dataset validation,
our method outperforms the previous state-of-the-art methods significantly.
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Self-supervised contrastive learning for integrative single cell RNA-seq data analysis
Wenkai Han*,
Yuqi Cheng*,
Jiayang Chen*,
Huawen Zhong,
Zhihang Hu,
Siyuan Chen,
Licheng Zong,
Irwin King,
Xin Gao#,
Yu Li#
Genome Biology (IF=13.540), under major revision, 2021
bibtex
We present a self-supervised Contrastive LEArning framework for scRNA-seq (CLEAR) profile representation and the downstream analysis.
CLEAR overcomes the heterogeneity of the experimental data with a specifically designed representation learning task and thus can handle batch effects and dropout events.
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Model Adaption Object Detection System for Robot
Jingwen Fu,
Licheng Zong,
Yinbing Li, Ke Li, Bingqian Yang, Xibei Liu
39th Chinese Control Conference (CCC), 2020
bibtex
We propose a new vision system for robots, the model adaptation object detection system.
Instead of using a single one to solve problems,
we made use of different object detection neural networks to guide the robot in accordance with various situations,
with the help of a meta neural network to allocate the object detection neural networks.
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Honors and Awards
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Execellent Graduate | Xi'an Jiaotong University
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2021
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Execellent Student | Xi'an Jiaotong University
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2020
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First Prize | National College Robot Competition (ROBOCON)
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2019
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Meritorious Winner | Interdisciplinary Contest In Modeling
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2019
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Teaching
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Recent News
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--- Apr 2022, put our RNA Foundation paper on ArXiv.
--- Jan 2022, started to be the TA of AIST4010.
--- Nov 2021, our RBP Review Paper has been accepted by Briefings in Bioinformatics
(IF=11.622). Congratulations, Junkang!
--- Sep 2021, started to be the TA of BMEG3105.
--- Aug 2021, became a Ph.D. student in CUHK!
--- July 2021, put our RBP Review on ArXiv.
--- July 2021, put our CLEAR Paper on bioXiv.
--- July 2021, graduated from Xi'an Jiaotong University!
--- May 2021, decided to pursue a Ph.D. in Computer Science and Engineering at CUHK!
--- Mar 2021, won the Execellent Graduate of Xi'an Jiaotong University.
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