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PhD Student / PostDoc Recruitment (Multiple Positions) for Applied Machine Learning; Applied Data Mining; Bioinformatics

@ City University of Hong Kong (We are recruiting NOW !!!)
(PhD admission deadline: December each year) Please put down "Ka-Chun Wong" as your potential supervisor in your applications; otherwise, your applications may not reach us.


Ka-Chun was born and raised in Hong Kong where he was lucky enough to be immersed in a multi-cultural environment. He received his B.Eng. in Computer Engineering from United College, the Chinese University of Hong Kong in 2008. He has also obtained his M.Phil. degree in the Department of Computer Science and Engineering at the same university in 2010. From 2011 to 2014, he has spent 3.5 years to finish his PhD degree in the Department of Computer Science at the University of Toronto. With exposures to different aspects (academic, industrial, spiritual ,and social), he hopes to strike a balance and contribute to the society.

News: Right after his PhD study, Ka-Chun has started his research lab as Assistant Professor in the Department of Computer Science, City University of Hong Kong (4th in QS World University Ranking aged under 50 and 14th in Times University Ranking aged under 50) in 2015. Interested applicants can contact him via email. Especially, PhD applicants are highly encouraged to apply for the Hong Kong PhD Fellowship Scheme (USD$ 3200 per month (tax free)). The scheme is real merit-based and does not have any preference toward nationality, which reflects the open humanity and freedom of Hong Kong. Here are some facts about Hong Kong:

Research Interests

  • Computational Biology & Bioinformatics
  • Data Mining & Machine Learning
  • Natural Computing
  • Computational Science
  • Quantitative & Interdisciplinary Research

Selected Publications

(*corresponding authorship, #co-first authorship)

[Book 3] Xiangtao Li, Ka-Chun Wong: Natural Computing for Unsupervised Learning., Book Series under Unsupervised and Semi-Supervised Learning, Springer (New York) 2019
[Book 2] Ka-Chun Wong: Big Data Analytics in Genomics. Springer (New York) 2017 (Content: 13 Peer-Reviewed Book Chapters with 46 Authors from Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, USA)
[Book 1] Ka-Chun Wong: Computational Biology and Bioinformatics: Gene Regulation. CRC Press (Taylor & Francis Group) 2016 (Content: 17 Peer-Reviewed Book Chapters with 52 Authors from Australia, Belgium, Brazil, Egypt, Germany, Hong Kong, India, Japan, USA)

[J23] Shixiong Zhang, Xiangtao Li, Qiuzhen Lin, Ka-Chun Wong* Synergizing CRISPR/Cas9 Off-Target Predictions for Ensemble Insights and Practical Applications Bioinformatics 2019
[J22] Ka-Chun Wong* DNA Motif Recognition Modeling from Protein Sequences iScience 2018
[J21] Jiecong Lin, Ka-Chun Wong* Off-target predictions in CRISPR-Cas9 gene editing using deep learning (ECCB 2018) Bioinformatics 2018
[J20] Xiangtao Li, Ka-Chun Wong* Evolutionary Multiobjective Clustering and Its Applications to Patient Stratification IEEE Transactions on Cybernetics 2018
[J19] Ka-Chun Wong* MotifHyades: Expectation Maximization for de novo DNA Motif Pair Discovery on Paired Sequences Bioinformatics 2017
[J18] Jiao Zhang, Sam Kwong, Yuheng Jia, Ka-Chun Wong*: NSSRF: global network similarity search with subgraph signatures and its applications. Bioinformatics 2017
[J17] Ka-Chun Wong*, Yue Li, Chengbin Peng: Identification of coupling DNA motif pairs on long-range chromatin interactions in human K562 cells. Bioinformatics 2016, 32(3): 321-324
[J16] Ka-Chun Wong*, Yue Li, Chengbin Peng, Alan M Moses, Zhaolei Zhang*: Computational Learning on Specificity-Determining Residue-Nucleotide Interactions. Nucleic Acids Research 2015, 43 (21): 10180-10189 2015 Impact Factor = 9.202
[J15] Ka-Chun Wong, Yue Li, Chengbin Peng, Zhaolei Zhang*: SignalSpider: Probabilistic Pattern Discovery on Multiple Normalized ChIP-Seq Signal Profiles. Bioinformatics 2015, 31 (1): 17-24 Supplementary Data Website Link
[J14] Graham Cromar, Ka-Chun Wong, Noeleen Loughran, Tuan On, Hongyan Song, Xuejian Xiong, Zhaolei Zhang, John Parkinson. New tricks for ‘old’domains: How novel architectures and promiscuous hubs contributed to the organization and evolution of the ECM. Genome Biology and Evolution 2014, Vol. 6 2897-2917
[J13] Yue Li#*, Liang Cheng#, Ka-Chun Wong, Jiawei Luo, Zhaolei Zhang*: Mirsynergy: detecting synergistic miRNA regulatory modules by overlapping neighbourhood expansion. Bioinformatics 2014, 30 (18): 2627-2635
[J12] Ka-Chun Wong*, Chengbin Peng, Yue Li, Tak-Ming Chan: Herd Clustering: A synergistic data clustering approach using collective intelligence. Applied Soft Computing 2014, Volume 23, Pages 61-75
[J11] Yue Li, Liang Cheng, Ka-Chun Wong, Ke Jin, Zhaolei Zhang*: Inferring probabilistic miRNA-mRNA interaction signatures in cancers: a role-switch approach. Nucleic Acids Research 2014, 42 (9): e76
[J10] Ka-Chun Wong, Zhaolei Zhang*: SNPdryad: Predicting Deleterious Non-synonymous human SNPs Using Only Orthologous Protein Sequences. Bioioformatics 2014, 30 (8): 1112-1119 Supplementary Data Website Link (Forward-twitted by the editor-in-chief, Alfonso Valencia, who handled its submission) Proteomic Data Download
[J9] Yue Li*, Anna Goldenberg, Ka-Chun Wong, Zhaolei Zhang*: A probabilistic approach to explore human miRNA targetome by integrating miRNA-overexpression data and sequence information. Bioinformatics 2014, 30 (5): 621-628.
[J8] Ka-Chun Wong, Tak-Ming Chan, Chengbin Peng, Yue Li, Zhaolei Zhang*: DNA Motif Elucidation using Belief Propagation. Nucleic Acids Research 2013, 41 (16): e153. Supplementary Data Website Link
[J7] Ming Fan, Ka-Chun Wong, Taewoo Ryu, Timothy Ravasi, Xin Gao*: SECOM: A Novel Hash Seed and Community Detection Based-Approach for Genome-Scale Protein Domain Identification. PLoS ONE 2012 7(6): e39475.doi:10.1371/journal.pone.0039475
[J6] Chengbin Peng, Xiaogang Jin, Ka-Chun Wong, Meixia Shi, Pietro Lio*: Collective Human Mobility Pattern from Taxi Trips in Urban Area. PLoS ONE 2012 7(4): e34487. doi:10.1371/journal.pone.0034487 Request Data
[J5] Ka-Chun Wong*, Chun-Ho Wu, Ricky K.P. Mok, Chengbin Peng, Zhaolei Zhang: Evolutionary multimodal optimization using the principle of locality. Information Sciences, Volume 194, 1 July 2012, Pages 138-170
[J4] Y.Leung*, M.H.Wong, K.C.Wong, W.Zhang, K.S.Leung: A Novel Web-based System for Tropical Cyclone Analysis and Prediction. International Journal of Geographical Information Science Vol. 26, Iss. 1, 2012, Pages 75-97 Website Link
[J3] Tak-Ming Chan*, Ka-Chun Wong, Kin-Hong Lee, Man-Hon Wong, Chi-Kong Lau, Stephen K. W. Tsui, Kwong-Sak Leung: Discovering approximate-associated sequence patterns for protein-DNA interactions. Bioinformatics, 27, 4:471-8, 2011.
[J2] Ka-Chun Wong*, Chengbin Peng, Man-Hon Wong, Kwong-Sak Leung: Generalizing and learning protein-DNA binding sequence representations by an evolutionary algorithm. Soft Computing, 15:1631-1642, 2011.
[J1] Kwong-Sak Leung, Ka-Chun Wong*, Tak-Ming Chan, Man-Hon Wong, Kin-Hong Lee, Chi-Kong Lau, and Stephen K. W. Tsui: Discovering protein–DNA binding sequence patterns using association rule mining Nucleic Acids Research 2010 38: 6324-6337. (among the top NAR articles in Computational Biology as of Oct 2011 - August 2013)

[C9]Junyi Chen, Shankai Yan, Ka-Chun Wong: Aggressivity Detection on Social Network Comments. ISMSI 2017
[C8]Yueming Lyu, Qingfu Zhang, Ka-Chun Wong: A Cone Order Sequence based Multi-objective Evolutionary Algorithm. IEEE CEC 2016
[C7] Ka-Chun Wong: A Short Survey on Data Clustering Algorithms. ISCMI 2015 Best Oral Presentation (1 out of 14 Presentations, Session 1)
[C6] Ka-Chun Wong: Data Analytics for Protein-DNA Binding Interactions. IEEE SMC 2015 Franklin V. Taylor Memorial Best Paper Award Nominee (5 out of 946 submissions)
[C5] Chengbin Peng, Zhihua Zhang, Ka-Chun Wong, Xiangliang Zhang, David Keyes: A Scalable Community Detection Algorithm for Large Graphs Using Stochastic Block Models. IJCAI 2015 (Acceptance rate: ~25%)
[C4] Chengbin Peng, Ka-Chun Wong, Alyn Rockwood, Xiangliang Zhang, Jinling Jiang, David E. Keyes: Multiplicative Algorithms for Constrained Non-negative Matrix Factorization. IEEE ICDM 2012 (Acceptance Rate: ~20%) DOI pdf
[C3] Ka-Chun Wong, Kwong-Sak Leung, Man-Hon Wong: Protein Structure Prediction on a Lattice Model via Multimodal Optimization Techniques. ACM GECCO 2010: 155-162 DOI pdf ppt Source Codes
[C2] Ka-Chun Wong, Kwong-Sak Leung, Man-Hon Wong: Effect of Spatial Locality on an Evolutionary Algorithm for Multimodal Optimization. EvoApplications (1) 2010: 481-490 DOI pdf ppt
[C1] Ka-Chun Wong, Kwong-Sak Leung, Man-Hon Wong: An evolutionary algorithm with species-specific explosion for multimodal optimization. ACM GECCO 2009: 923-930 DOI pdf ppt

[W1] Chengbin Peng, Ka-Chun Wong: Exploring Mixed Membership Stochastic Blockmodels via Non-negative Matrix Factorization. IEEE ICDM 2014, IDP Workshop (Regular Paper Acceptance Rate: 26.3%)

Teaching Course Leaderships

In Hong Kong,
CS8695 : Research in Computer Science (Seasonal)
CS4465 : Computational Biology and Bioinformatics (Spring 2015-now [TLQscore:~6/7])
CS4480 : Data-Intensive Computing (Fall 2018-now)
CS5488 : Big Data Algorithms and Techniques (Fall 2018-now)
GE1319 : Interdisciplinary Research for Smart Professionals (Seasonal)
GE2324 : The Art and Science of Data (Fall 2015-2017 [TLQscore:~6/7])

Teaching Assistantships

In Toronto,
CSC108 : Introduction to Computer Programming (Fall 2011)
CSC209 : Software Tools and Systems Programming (Summer 2013)
CSC263 : Data Structures and Analysis (Spring 2012)
CSC309 : Programming on the Web (Spring 2014, Summer 2014)
CSC343 : Introduction to Databases (Fall 2012, Spring 2013, Fall 2013)
CSC401/2511 : Natural Language Computing (Spring 2013)
In Hong Kong,
CSC3420 : Computer System Architectures (Spring 2009, Spring 2010)

Recent Awards and Achievements

2018 General Research Fund, Research Grant Council (Hong Kong, 57 out of 175 CS professors)
2017 General Research Fund, Research Grant Council (Hong Kong, 56 out of 188 CS professors)
2016 Early Career Scheme, Research Grant Council (Hong Kong, largest ECS grant in CS area)
2015 Assistant Professorship without any Posdoc Placement, City University of Hong Kong
2013 Acres - Joseph Yonan Memorial Fellowship, Computer Science, University of Toronto
2012 Kwok Sau Po Scholarship, School of Graduate Studies, University of Toronto
2012 Acres - Joseph Yonan Memorial Fellowship, Computer Science, University of Toronto
2011-2014 International Research and Teaching Assistantship, University of Toronto

Recent Open Software Contributions

MotifHyades FullSignalRanker SignalSpider SNPdryad kmerHMM LatticeModel

Journal Associate Editorship

BioData Mining (2016-now, Impact Factor~=2)
(First Associate Editor outside USA and Germany)

Journal Editorial Board Memberships

Applied Soft Computing (2016-now, Impact Factor~=4)
Artificial Intelligence Research (2015-now)
Big Data Analytics (2015-now, BioMedCentral)
Big Data (2015-now, Frontiers)
Bioinformatics and Computational Biology (2015-now, Frontiers)
Cancer Informatics (2017-now)
Journal of Bioinformatics and Proteomics Review (2015-now)
OMICtools (2014-now,, Curatorship)
Soft Computing (Guest Editorship, ISCMI 2016 Special Issue)
Neural Computing and Applications (Guest Editorship, ISMSI 2017 Special Issue)

Conference Chairships

DSIT 2018 (Publication Co-Chair)
ICIST 2018 (Registration Co-Chair)
ICONIP 2018 (Registration Co-Chair)
ISCBI 2018 (Program Co-Chair)
ISCMI 2018 (Publication Co-Chair)
ISMSI 2018 (Program Co-Chair)
ISNN 2018 (Registration Co-Chair)
ICIST 2017 (Registration Co-Chair)
ISCBI 2017 (Program Co-Chair)
ISCMI 2017 (Program Co-Chair)
ISMSI 2017 (Organizing Chair) (3 keynote speeches from Hong Kong, Sinagpore, and Switzerland; 35 accepted papers for oral presentations from China, Germany, Hong Kong, India, Indonesia, Italy, Japan, Korea, South Africa, Singapore, Slovenia, Switzerland, Taiwan, and Thailand)
ISNN 2017 (Registration Co-Chair)
ICICIP 2016 (Regisration Co-Chair)
ISCBI 2016 (Publication Co-Chair)
ISCMI 2016 (Program Co-Chair)
ISCBI 2015 (Publication Co-Chair)
IEEE SMC 2015 (Session Chair)

Conference Invited Talks

ISACIT 2018 (Keynote Speech)
IWSG 2018 (Invited Speech)
HKU & ND Workshop 2018 (Invited Speech)
ICBCB 2017 (Plenary Speech)

Conference Program Committee Memberships

BICOB 2015,2016,2017,2018
BIGCOM 2015,2016,2017,2018
DMBD 2016,2017,2018
DMCIT 2017,2018
ICBBT 2017,2018
ICBCI 2017,2018
ICIC 2015,2016,2017,2018
ICNC-FSKD 2016,2017,2018
ICSCA 2016,2017,2018
ICSI 2015,2016,2017,2018
IEEE BIBE 2016,2018
IEEE BIBM 2014,2015,2016,2017,2018
IEEE BigData 2015,2016,2017,2018
IEEE SmartData 2018
ISCBI 2015,2016,2017,2018
ISCMI 2015,2016,2017,2018
IWBBIO 2017,2018
PIC 2016,2017
Others: APBC 2016-18, IEEE CIBCB 2016, GIW 2016, BIOKDD 2017, ICMLC 2017, ICBEB 2015-17, ICoBN 2018, DSIT 2018

Review Services (Sorted by Alphabet)

Algorithms for Molecular Biology
Applied Soft Computing
Bioinformatics and Biology Insights
Biomedical Engineering and Computational Biology
Biomedical Informatics Insights
BMC Bioinformatics
Cancer Informatics
Computational and Structural Biotechnology Journal
Computational Biology and Chemistry
Evolutionary Bioinformatics
Evolutionary Computation
Expert Systems With Applications
Gene Expression to Genetical Genomics
Genomics, Proteomics & Bioinformatics
Genomics Insights
IEEE Access
IEEE Journal of Biomedical and Health Informatics
IEEE Transactions on Big Data
IEEE Transactions on Cybernetics
IEEE Transactions on Evolutionary Computation
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Industrial Informatics
IEEE Transactions on NanoBioScience
IEEE/ACM Transactions on Computational Biology and Bioinformatics
International Journal of Data Science and Analytics
International Journal of Geographical Information Science
International Journal of Machine Learning and Cybernetics
International Journal of Molecular Sciences
Journal of Bioinformatics and Computational Biology
Journal of Biomedical Informatics
Journal of Genomes and Exomes
Nature Methods
Neural Processing Letters
Nucleic Acids Research
PLoS Computational Biology
PLoS Genetics
Scientific Reports
The Computer Journal