Education

Aug.2014 Doctor of Philosophy Monash University, Australia

Dissertation: Event detection, classification and analysis on atmospheric time series

Supervisors: Professor Kate Smith-Miles and Professor DanijelDanijel Beluˇsic´

Thesis advisory committee: Professor Fima Klebanerand Professor Rob Hyndman

Jul.2010 Master’s coursework inStatistics Renmin University of China

Jul.2009 Bachelor in Statistics Shandong University of Finance and Eco- nomics

Research Interests

Statistical computing·Time seriesanalysis·Big Data and machine learning

Working Experience

Nov. 2016–present

Associate Professor

School of Economics and Manage- ment, Beihang University

Aug. 2015–Aug. 2016

Senior R&D engineer

Big Data Group, Baidu Inc.

Projects: Credit scoring with BigData; Bigretails data analysis;Quantitative investment

Aug. 2014–Jul. 2015 Postdoctoral Research Fellow Monash University

Topic: Visualising forecastingalgorithm performance usingevolved time series instancespaces

Research Projects

Stress-testing algorithms: generating new test instances toelicit insights funded by Australian Research Council, investigator. (2014 – 2015)

Computer Skills

•Good at deploying and developing statistical models in Big Data distributed system with Hadoop and Spark

• Daily usage of Hive and HBase for Big Data

• Skilled in Python and R for web scraping with complicated web pages, data processing for complex data, statistical modeling and machine learning

• Have the background in parallel computing

Publications

1.Kang,Y. (2012).Real-time change detection in time series based on growing feature quantization.

In: Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN). IEEE, pp.1–6, EI.

2. Kang, Y., K. Smith-Miles, and D. Belusˇic´ (2013). How to extract meaningful shapes from noisy time-series subsequences? In: Proceedings ofthe 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM).IEEE, pp.65–72, EI.

3. Kang, Y., D. Belusˇic´ , and K. Smith-Miles (2014). Detecting and Classifying Events in Noisy Time Series. Journal of the Atmospheric Sciences 71(3), 1090–1104, SCI.

4. Kang, Y., D. Belusˇic´ , and K. Smith-Miles (2014). A note on the relationship between turbulent coherent structures and phase correlation. Chaos: An Interdisciplinary Journal of NonlinearScience

24(2), 023114,SCI.

5. Kang, Y., D. Belusˇic´ , and K. Smith-Miles (2015). Classes of Structures in the Stable Atmospheric Boundary Layer. Quarterly Journal of the Royal MeteorologicalSociety 141 (691),2057–2069, SCI.

6. Kang, Y., D. Belusˇic´ , and K. Smith-Miles (2015). Detection, Classification and Analysis of Events in Turbulence Time Series.Bulletin of the AustralianMathematical Society 91 (3), 521–522,SCI.

7. Kang, Y., R. J. Hyndman, and K. Smith-Miles (2016). Visualising Forecasting Algorithm Performance using Time Series Instance Spaces. International Journal of Forecasting (inpress).

Recent presentations

• The 7th International Forum on Statistics ofRenmin University ofChina, 2016,China

• The 2014 Conference -Mathematics of Planet Earth (MPE)Australia, Australia

• The 2013 IEEESymposium on ComputationalIntelligence and Data Mining (CIDM), Singapore

• The 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia

• The 2011 Australian Mathematical Sciences Institute (AMSI) Graduate Winter School, Brisbane, Australia

Teaching Associate Experience

• Optimisation, Estimation and Numerical Methods,Monash University(2014)

• Advanced Engineering Mathematics, Monash University (2011 – 2013)

Awards & Scholarships

• “100-Talent” Program, by Beihang University, Nov. 2016

• AMSI Winter School Travel Award, by Australia Mathematical Science Institute, May

2012

• Ph.D. scholarship for oversea studies, byChinese Scholarship Council(CSC), May 2010

• First Class Scholarship, byRenmin University ofChina, 2009– 2010

• Outstanding Graduate of Shandong University ofFinance and Economics, May 2009

• National Scholarship, by Ministry of Education of China, Oct.2008