Mr. WONG Ka Chun (黃嘉駿)


Author IDs

Willing to take PhD students: yes


Ka-Chun has spent 3.5 years (2012-13 departmental average: 6 years after master degree) to finish a PhD degree in Department of Computer Science at University of Toronto proudly under the supervision of Professor ZHANG ZhaoLei (CCBR) at the end of 2014. After that, he becomes an independent researcher. He is merited as the first associate editor outside USA and Germany for the open-access journal, BioData Mining, in 2016. He is also on the editorial board of Applied Soft Computing since 2016. He was invited as the plenary speaker for ICBCB 2017 (Hong Kong) in 2017. In addition, he has solely edited 2 books published by Springer and CRC Press, attracting 30 peer-reviewed book chapters around the world (i.e. Argentina, Australia, Belgium, Brazil, China, Egypt, France, Germany, Hong Kong, India, Japan, Spain, USA).


  • 2016 “Early Career Scheme” Engineering, Research Grants Council, Hong Kong.
  • 2015 “Assistant Professorship” CS, Cty University of Hong Kong.
  • 2015 “Doctor of Philosophy” CS, University of Toronto.
  • 2013 “Acres - Joseph Yonan Memorial Fellowship” CS, University of Toronto.
  • 2012 “Kwok Sau Po Scholarship” SGS, University of Toronto.
  • 2012 “Acres - Joseph Yonan Memorial Fellowship” CS, University of Toronto.
  • 2011 “International PhD Funding Package” CCBR, University of Toronto.
  • 2010 “Provost Award” KAUST.
  • 2008 “RGC Postgraduate Studentship” The Chinese University of Hong Kong.
  • 2007 “Dean List” Engineering, The Chinese University of Hong Kong.
  • 2007 “Chiu Fuk San Prize” United College, The Chinese University of Hong Kong.
  • 2005 “Multiple Scholarships for HK A-level” Concordia Lutheran School.
  • 2004 “Championship ” Computer Game Concept Competition by Sha Tin IVE.
  • 2003 “Multiple Scholarships for HKCEE” Concordia Lutheran School.

Research Interests/Areas

  • Computational Biology
  • Bioinformatics
  • Evolutionary Computation
  • Big Data Analytics
  • Applied Machine Learning
  • Natural Computing
  • Computational Science
  • Interdisciplinary Research
  • Applied Data Mining