Tong He

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About me M.Sc. from the Data Mining lab at Simon Fraser University, under the supervision of Prof. Martin Ester. A student in the MADD-Gen program Received B.Sc. in Statistics from Sun Yat-Sen Univeristy Email: hetongh [at] sfu.ca

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Research Interests

My research interests include data mining, machine learning and algorithm for bioinformatics.

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Publications

Bioinformatics

• Zeng, X., Huang, J. X., Zhang, G., He, T., Liang, Z. H., & Cai, Y. F. (2013, December). Augmenting LASSO regression with decision tree for identifying the correlation of genetic polymorphism and adverse events. In 2013 IEEE International Conference on Bioinformatics and Biomedicine (pp. 355-360). IEEE.

Machine Learning

• Chen, T., & He, T. (2015). Higgs boson discovery with boosted trees. In Cowan et al., editor, JMLR: Workshop and Conference Proceedings (No. 42).

Books

• Translation of Introductory Statistics with R, originated by Peter Dalgaard

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Experience

• SupStat, Data Scientist, Beijing, China, 2014
• Douban, Algorithm Engineer Intern, Beijing, China, 2013
  • Predict user profile based on interests.
  • Mining folksonomy data from movie database.
• Giordano, Buisness Analyst Intern, Guangzhou, China, 2012
  • Mining influencial factors associated with sales trends

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Selected Awards and Talks

• John M. Chambers Statistical Software Award, ASA, 2016
• Graduate Fellowship, Simon Fraser University, 2015
• Graduate Fellowship, NSERC, 2015
• Special High Energy Physics meets Machine Learning Award, CERN, 2014
• Cleansing and analysis of folksonomy in Douban, Sixth useR China conference in Shanghai, Fall 2013

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Software and Packages

• SwarmSVM
  • R package for fast ensemble SVM models.
• XGBoost
  • R package for fast gradient boosting model.
• rLTP
  • R package for ltp-cloud service.
• pullword
  • R package for pullword service.

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Courses and Projects

• CMPT 894, Direct Reading on Probabilistic Graphical Model
  • Project: Bayesian Probability Matrix Factorization
• CMPT 843, Statistical Sampling and Estimation, Spring 2015
  • Project: Filling Missing Value with Gibbs-Sampling-Based Matrix Factorization
  • Presentation: Efficient Spatial Sampling of Large Geographical Tables
• CMPT 705, Introduction to Algorithm design, Spring 2015
• CMPT 726, Machine Learning, Fall 2014
  • Project: Latent Information Aware Network Labeling
  • The poster won the Best Poster Award
• CMPT 711, Introduction to Computational Biology, Fall 2014
• Undergraduate thesis, Single feature polymorphisms gene detection based on Bayes model, 2013
  • Classification of gene with hierarchical Bayes model, use false discovery rate to deal with multiple testing problem.
  • Top level undergraduate thesis