W9zypq6j7bexvjvdf5jo

HUEY-LONG CHEN

陳惠龍

Kaggle Competitions Expert: https://www.kaggle.com/alanchen1115


Competitions:

(1) Top 6%: Understanding Clouds from Satellite Images, Can you classify cloud structures from satellites? 2019/11/19. 

There are many ways in which clouds can organize, but the boundaries between different forms of organization are murky. This makes it challenging to build traditional rule-based algorithms to separate cloud features. In this challenge, a keras based Unet model is used to classify cloud organization patterns from satellite images. Techniques used include data augmentation, ensemble modeling, test time augmentation, pseudo label training.

(2) Top 6%: Generative Dog Images, Experiment with creating puppy pics, 2019/08/29.

A generative adversarial network (GAN) is a class of machine learning system with two neural networks competing with each other in a game. Traditional GANs generate high-resolution details as a function of only spatially local points in lower-resolution feature maps. The self-attention GAN allows attention-driven, long-range dependency modeling for image generation tasks. In this competition, a tensorflow based self-attention GAN is used to create images of dogs. There's no ground truth data to predict. The images submitted to be scored are based on how well those images are classified as dogs from pre-trained neural networks.


Off-the-job training: 

.2013: IBM SPSS MODELER, AsiaAnalytics Taiwan- Machine learning 

.2018: AI Engineer, Institute for Information Industry- Deep learning and Machine learning.

.2019: AI Teacher Training, Institute for Information Industry


Experience:

.08/2019- Data science tech-director of Taiwan water resources and agriculture research institute. 

.08/2001- 07/2019 Assistant professor/head to the department of cosmetic science and application, and department of environmental engineering, Lanyang Institute of Technology.

.01/2000- 07/2001 Vice CEO of the water resources management and policy research center, Tamkang University. 


Education:

.Ph.D.: School of Civil Engineering, Purdue University (12, 1999). Ph.D. Thesis: “Stochastic Characteristics of Hydrologic and Environmental Time Series”. 

.Master Degree: Graduate Institute of Water Resource and Environmental Engineering, Tamkang University (06, 1992). Master Thesis: “Studies on the Non-Gaussian and Non-Stationary Time Series”. 

.Bachelor Degree: Department of Chemical Engineering, National Taiwan University (06, 1990). 

      [email protected]

Data Scientist / AI Engineer
Keelung,TW

技能

deep learning with tensorflow/ keras/ machine learning/ opencv/ python/ django/ node.js / javascript/ matlab/ fortran/ c++/ linux/ git/ word/ powerpoint/ excel/ photoshop

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