CV

Work experience

• Data Scientist / AI Engineer at aetherAI, May 2018 - now
  • Deep learning applications in medical image fields, including classification, detection, and segmentation.
    
    • Whole Slide Images (WSIs) cancer screening
    • Computational pathology with cancer quantification
    • Computational pathology with immonohistochemistry (IHC) identificaion and quantification
• Data Scientist / Lecture Lead at Taiwan AI Academy, Jan 2018 - April 2018 (position inherit from Academia Sinica)
• Reserach assistant at Data Insight Research Lab, DIRL, Institute of Information Science, Academia Sinica, May 2016 - Jan 2018
  • Projects
       - Team project THETA: provide deep learning solutions for serveral manufacturer such as 台塑石化, 長春石化, 研華電子, etc
    
    • 1) Defect classification, successfully reduced OR/LR (overkill rate/leakage rate) to 0.8%/0.1% with processing speed 240k images/day from 30%/10% human perforamce with 1 day
      
    • 2) Predictive maintenance, use both CNN and LSTM model to predict machine shutdown (air compressor) befroe 5 mins, which is enough for clients to prepare warm up the backup machine.
      
    • 3) parameter optimization, stenter machine speed up.
      
    • Team leader, coorperation with EASYCARD Co.Ltd
      
      • 1) E-ticket use rate prediction, use machine learning method to predict the E-ticket use rate for new marketing channels.
        
      • 2) marketing strategies analysis
        
    • Team leader, coorperation with books.com.tw
      
      • 1) exploratory data analysis for e-commerce
        
      • 2) books sales predition model 3) features analysis of books
        
    • Investigation project (with Jimmy Yang), cooperation with Sunfun Co.Ltd
      
      • 1) exploratory data analysis for on-line dating pattern - why and how male and female select their ideal mates.
      • 2) fruad detection in on-line dating Apps, the AUC is over 0.98.
    • Investigation project, the polis Taiwan.
      • 1) the ideology and on-line comment/voting behavior pattern exploration by using the matrix factorization method.
  • Other duties:
    
    • GPU server management
      
    • Lecturer / Tutorials
      
      • R
        • Introduction and basis of R
          
        • Exploratory data analysis and data visualization
          
      • Deep learning
        
        • Hands-on tutorial of deep learning
          
        • Introduction and basis of TensorFlow
          
• Adjunct Research Assistant at Vision Neuroscience Lab, VNL, Department of Psychology, National Tawian University, March 2016 - May 2016
  • Duties included: Magnetic Resonance Imaging (MRI) data analysis, build up analysis script and SOP
  • Main tools: Matlab, Linux shell script

Education

• M.S. in Psychology, National Taiwan University, 2015
• B.S. in Psychology, National Cheng Kung University, 2012

Skills

• Specialist
  • Neuroscience & Behavioral science
  • Statistical analysis & Machine learning
      - Data ETL, traditional statistical analysis, prediction analysis with modern machine learning agorithm (e.g. XGBoost, SVM, etc)
  • Deep learning (Computer Vision)
    • Network design in 2D and 3D CNN model for classification and segmentation tasks.
• Programming
  • Languages
    • R (proficient)
    • Python (proficient)
    • Shell (familiar)
    • Web: html-css-javascript (familiar)
  • Deep Learning Framework
    • Python - Tensorflow (proficient), PyTorch (familiar)