"San-Chuan (Leo) Hung"

contact: c2016.tw at gmail.com

Experience

Software Engineer, Google, Mountain View (February 2016 - Present)

Optimized Ads Experience

Software Engineering Intern, Google, Mountain View (May - August 2015)

Optimized Enhanced CPC bid with large scale conversion data

• Developed a new metric for evaluation
• Developed pipelines to process click data (>10TB) in less than three hours

Technologies: Spark like framework, BigTable, Machine Learning, C++, Python

Web Team Intern, Gogolook Co., Ltd, Taipei, Taiwan (March - July 2014)

Designed and programmed the first version of a realtime back-end API server with an analytic dashboard for a mobile app with more than 10 million global users

Technologies: Python, MongoDB, BigQuery, Git, CSS, HTML

Search Team Intern, Yahoo! Taiwan (July - August 2011)

Analyzed mobile search engine query log and implemented a location-based query suggestion system which can improve speed for user typing query by 180%.

Technologies: Natural Language Processing, Python, C, Pig, Hadoop

Education

Carnegie Mellon University, Pittsburgh, PA (December 2015)

• School of Computer Science, Master of Computational Data Science
• GPA: 3.7/ 4.0

National Taiwan University, Taipei, Taiwan (January 2013)

• Department of Computer Science and Information Engineering, M.S. in Computer Science
• GPA: 4.1/ 4.0

National Taiwan University, Taipei, Taiwan (January 2011)

• Department of Computer Science and Information Engineering, B.S. in Computer Science (Double Major in Sociology)
• GPA: 3.9/ 4.0

Personal Projects

"Taiwan Colors"

Taiwan colors palettes, automatically generated by unsupervised clustering algorithms from Taiwan pictures, to inspire next awesome design of Taiwan

Technologies: Machine Learning, Multimedia Analysis, jQuery, CSS

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Technical Skills

• Proficient With: Python, Java, C++, Web Development, Machine Learning, Data Mining
• Familiar With: MongoDB, HBase, MySQL, Git, HTML, CSS, Javascript

Publication

San-Chuan Hung, Miguel Araujo and Christos Faloutsos

"Distributed Community Detection on Edge-labeled Graphs using Spark," in MLG'16 download

Tsung-Ting Kuo, San-Chuan Hung, Wei-Shih Lin, Nanyun Peng, Shou-De Lin, and Wei-Fen Lin,

“Exploiting latent information to predict diffusions of novel topics on social networks,” in ACL ‘12 download

Predict novel topic information diffusion on social network, and the result shows 16% AUC improvement over the baseline models.

Technologies: Social Network Analysis, Natural Language Processing, Machine Learning, JAVA, Python, C