Guest Speakers

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Dr. Arkom Drawpateep received B.Sc. from King Mongkut's Institute of Technology Ladkrabang (KMITL), Thailand in 2007. He received M.Sc. degree in Applied Polymer Science, Major of Polymer Engineering from Martin-Luther-Universitat Halle-Wittenberg, Germany in 2011. He is awarded a Ph.D. degree from Martin Luther University, Halle, Germany in 2018. He joins the SCG Chemicals from 2011. He is now the lead engineer of the PP Technology group, SCG Chemicals. His interest includes borate co-catalyst, ethylene polymerization and copolymerization.

Title: Applications of Artificial intelligence in Petrochemical business of SCG Chemical

Keywords: Polyolefin, Process technology, Polyolefin catalysis, ROTO molding, Polyolefin wax, Excellent packaging

Abstract

SCG Chemicals is one of the oldest petrochemical company in Thailand originated back in 1983. The company have evolved to be one of the leader of polyolefin producer in South East Asia, having production complex located in Thailand, Indonesia, and Vietnam. In order to do so, the company have embraced power of computer aid engineering, data management, and digital manufacturing on improving the way of work. In this talk I will introduce example on variety of application of artificial intelligence in SCG Chemicals' business.

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Minh Le Nguyen is currently an Associate Professor of School of Information Science, JAIST. He leads the lab on Machine Learning and Natural language Understanding at JAIST. He received his B.Sc. degree in information technology from Hanoi University of Science, and M.Sc. degree in information technology from Vietnam National University, Hanoi in 1998 and 2001, respectively. He received his Ph.D. degree in Information Science from School of Information Science, Japan Advanced Institute of Science and Technology (JAIST) in 2004. He was an assistant professor at School of information science, JAIST from 2008-2013. His research interests include machine learning, natural language understanding, question answering, text summarization, machine translation, legal text processing, and Deep Learning.

Title: Natural Language Processing for Legal Engineering and its Application

Keywords: Legal text processing, Legal engineering, Deep learning, Natural Language Processing

Abstract

Our society is regulated by a lot of laws which are related mutually. When a society is viewed as a system, laws can be viewed as the specifications for the society. In the upcoming e-Society, laws have more important roles for achieving a trustworthy society and we expect a methodology which treats a system-oriented aspect of laws. Legal Engineering is the field that studies the methodology and applies information science, software engineering and artificial intelligence to laws for supporting legislation and to implement laws using computers. As laws are written in natural language, natural language processing is essential for Legal Engineering. In this talk, we present our works on natural language processing for Legal Engineering. We also highlight our current deep learning-based techniques for analyzing legal documents and our system participating on the Fifth Competition on Legal Information Extraction/Entailment (COLIEE-2018).

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