Greetings!

Welcome to my corner of the digital world! I am a seasoned Machine Learning Engineer with an extensive 7 years of hands-on experience crafting cutting-edge machine learning models, developing data-driven products, and fostering collaboration within cross-functional teams. Holding a Ph.D. in Statistics, my academic journey spans 5 years, where I immersed myself in the intricate world of statistical methodologies, particularly exploring the nuances of complex spatio-temporal datasets.

Filed of Interests

My passion and expertise lie in several domains, including:

  • Natural Language Processing (NLP)
  • Recommendation Systems
  • Deep Learning
  • Machine Learning
  • Bayesian Statistics
  • Spatial Statistics

I possess proficiency in a diverse range of programming languages tailored for specific tasks, including:

  • General-purpose programming: Python, C++
  • Data processing and analytics: PySpark, R, SQL
  • Machine learning and deep learning frameworks: PyTorch, TensorFlow

Publications

Explore some of my noteworthy publications:

Regularized Spatial Maximum Covariance Analysis

Wen-Ting Wang and Hsin-Cheng Huang, 2018. Environmetrics, 29(2)

Regularized Principal Component Analysis for Spatial Data

Wen-Ting Wang and Hsin-Cheng Huang, 2017. Journal of Computational and Graphical Statistics, 26(1)

Note that you can find my publications on Google Scholar.