Keynote Speakers

Hui-Huang Hsu

Hui-Huang Hsu
Professor
Tamkang University

Title: Sentiment Analysis and its Applications

Abstract:
Sentiment analysis tries to determine the attitude of a person or a group of people. The attitude can be positive, neural or negative. Sentiment analysis is based on emotion detection on text, voice, facial expression or even postures. It helps us better understand the feeling or intention of people. Sentiment analysis can be useful for marketing, customer services, health care and various kinds of trend prediction. In this talk, we will introduce the technologies and tools for sentiment analysis. Interesting applications will also be presented.

Biodata:
Dr. Hui-Huang Hsu is a Professor in the Department of Computer Science and Information Engineering at Tamkang University in Taipei, Taiwan. He also serves as the Dean of College of Engineering since August 2016. He was the Chairman of the Department from August 2012 to July 2016. Prof. Hsu received his Ph.D. and M.S. Degrees in Electrical and Computer Engineering from the University of Florida, USA. Prof. Hsu is very active in international academic activities, as conference organizer, journal editor/reviewer and invited speaker. Prof. Hsu has published over 140 referred papers in international journals and conference proceedings. He also edited a book titled Big Data Analytics for Sensor-Network Collected Intelligence published by Elsevier, USA in Feb. 2017. He has worked in the areas of machine learning, data mining, ambient intelligence, bio-medical informatics, and multimedia processing. Prof. Hsu is a Senior Member of the IEEE. He is also the current President of Taiwanese Association for Artificial Intelligence (TAAI).

Horst Lichter

Horst Lichter
Professor
RWTH Aachen University

Title: Reconstruction and Evaluation of Software Architectures

Abstract:
In civil engineering, the architecture of large constructions such as industrial buildings or entire cities plays an important role to achieve their desired properties. Similar, a software system’s architecture defines how the system is built from individual elements and how these are interconnected. In this talk, we will introduce the most important concepts of software architecture and discuss its overall importance to software quality and will give an overview on existing techniques to reconstruct a software architecture based on static and dynamic data. Furthermore, we will present a new and innovative approach to check the conformance of a given (reconstructed) software architecture in order to control the inevitable drift between the prescriptive and descriptive architectures of a software system during its evolution. This finally leads to an architecture evaluation process that can be applied to monitor the quality of software architectures and to evaluate possible evolution scenarios.

Biodata:
Horst Lichter is a Professor at RWTH Aachen University and head of the Software Construction Research Group. Horst research interests cover many fields, e.g., software architecture, quality assurance, or modern development processes. Horst has published books, many scientific papers and has organized many international workshops (e.g., QuASoQ, CES workshop series). He is a member of IEEE, German Computer Science Association and Swiss Computer Science Association. Furthermore, Horst is a visiting lecturer for Software Engineering at the Thai German Graduate School of Engineering, Bangkok, Thailand since 2005.Horst Lichter received a Diploma degree in Computer Science and Economics from Technical University Kaiserslautern, Germany in 1986 and a Dr. rer.nat. degree from Stuttgart University, Germany, in 1993. Afterwards, he was with the Union Bank of Switzerland Zurich, where he headed many development projects and with ABB Corporate Research, Heidelberg, where he was responsible for many software process improvement activities at several business units.

Thadpong Pongthawornkamol

Thadpong Pongthawornkamol
Principal Visionary Architect
KASIKORN Labs Co., Ltd.

Title: Machine Lending: Leveraging AI for fun and financial freedom

Abstract:
Lending has been considered one of the main banking functionalities to provide financial liquidity to individual customers and power national economic growth. In the past, the traditional lending process has proved to be slow and low in coverage. At KASIKORNBANK, we look into using machine learning techniques to improve the decision process of loan approval and loan offering. Together with mobile technology and process automation, we create a friction-less personalized lending experience for mobile banking application users. Since launched, the new lending system has tripled the personal loan conversion rate when compared to the traditional method.

Biodata:
Thadpong Pongthawornkamol is a Principal Visionary Architect and head of Machine Learning team at Kasikorn Business-Technology Group (KBTG), Thailand. He received the B.Eng. degree in Computer Engineering from Kasetsart University, Thailand, in 2003 and the M.S. and Ph.D. degrees in Computer Science from the University of Illinois at Urbana-Champaign in 2006 and 2010, respectively. Prior to his current job, Dr. Pongthawornkamol has worked in various organizations from academia and industry in Thailand and US including Bloomberg and Google. His main research interest is in artificial intelligence, machine learning, data science, and distributed systems.

Chia-Hui Chang

Chia-Hui Chang
Professor
National Central University

Title: From Web information extraction to information management: A road to message understanding

Abstract:
World Wide Web is the best and largest information resources. To enable higher levels of automation, transforming human readable web data into structured format has been an important issue for semantic Web. In the past decades, information extraction from static Web (free-text) and deep Web (semi-structured) has attracted many research focuses both from academy and industry. For information extraction from static pages, while it can be used to populate Web knowledge base (KB) such as DBpedia, YAGO, Web KB can also guide information extraction. Deep web data extraction, on the other hand, can further speed up the extraction procedure for data instances of the same relational schema (even though we need to construct one wrapper for each website) and create Web KB with the help of proper ontology learning. In this talk, we will introduce two information extraction tools, namely WebETL and DS4NER for static and deep Web respectively, and demonstrate their applications for event search, disaster report management, and POI search.

Biodata:
Dr. Chia-Hui Chang is a full Professor at National Central University, Taiwan. Dr. Chang obtained her Ph.D. in Computer Science and Information Engineering from National Taiwan University, Taiwan in 1999. Her research interests focus on Information Extraction, Web Intelligence, Data Mining, Machine Learning and System Integration. Dr. Chang has published more than 80 papers at refereed conferences and journals including WWW, PAKDD, TKDE, IEEE Intelligent Systems, etc. She served as area co-chairs for ACL 2017, NAACL 2018 and PC members for ICDE, CIKM, PAKDD, AAAI, ICTIR, etc. She is also an executive director of Taiwan Association for Artificial Intelligence (TAAI) and currently vice president for Association for Computational Linguistic and Chinese Language Processing (ACLCLP).

Rodney Van Meter

Rodney Van Meter
Associate Professor
Keio University

Title: The Quantum Internet

Abstract:
The coming Quantum Internet will bring us new capabilities: advanced cryptographic functions, high-precision sensor networks for uses such as high-resolution astronomy, and secure distributed quantum computing. Experimental progress toward quantum repeaters -- the quantum equivalent of the Internet's switches and routers -- is moving at a dizzying rate, and theorists have proposed half a dozen approaches to managing errors to create high-fidelity quantum entanglement. I will give an overview of the issues in quantum networks, then discuss the even more daunting challenge of creating networks of networks -- a true quantum Internet.

Biodata:
Rodney Van Meter received a B.S. in engineering and applied science from the California Institute of Technology in 1986, an M.S. in computer engineering from the University of Southern California in 1991, and a Ph.D. in computer science from Keio University in 2006. His current research centers on quantum computer architecture and quantum networking. Other research interests include storage systems, networking, and post-Moore's Law computer architecture. He is now an Associate Professor of Environment and Information Studies at Keio University's Shonan Fujisawa Campus. He is the Vice Dean of the Graduate School of Media and Governance, and the Vice Center Chair of Keio's new Quantum Computing Center. Dr. Van Meter is a member of AAAS, ACM and IEEE.

Wallapak Tavanapong

Wallapak Tavanapong
Professor
Iowa State University

Title: Real-time Artificial Intelligence Technology for Improving Patient Care

Abstract:
Good health and well-being is everyone’s dream. We wish we do not get sick. When we do get sick, we wish for quick recovery. Excellent patient care is vital for disease prevention and quick recovery. In recent years, we have seen a flourish of Artificial Intelligence (AI) technologies in various domains. Among them is the application of Convolutional Neural Network (CNN) for classification of different types of medical images. Nevertheless, class imbalance (class distribution imbalance) and the expensive time-consuming process to create a large labeled dataset prevents CNN from being effective in a routine medical practice. Under class imbalance, there are many more normal images than target images of interest (e.g., images showing a certain disease). This talk will present a novel active deep learning technology for CNN-based classification. The technique is aimed to cut down domain experts’ labeling time significantly while providing high classification accuracy. The technology is incorporated into a novel computer-aided application that assists the endoscopist in real-time toward optimal colon inspection during colonoscopy to reduce the chance of missing polyps or cancers.

Biodata:
Wallapak Tavanapong is a Professor of Computer Science and Director of Computational Media Lab at Iowa State University, USA. She is also a co-founder and a Chief Technology Officer of EndoMetric Corporation that offers cutting-edge computer-assisted technology for improving patient care for endoscopy. She has given invited talks at institutions such as Georgia Tech and Mayo Clinic Grand Round Lecture Series in the US, Simula Research Laboratory in Norway, and Nankai Hospital in China. Her expertise is in multimedia analysis, databases and information retrieval, applied machine learning and data science applications in various domains ranging from healthcare to political science and journalism.
Prof. Tavanapong received the B.S. degree in Computer Science from Thammasat University, Thailand, in 1992 and the M.S. and Ph.D. degrees in Computer Science from the University of Central Florida in 1995 and 1999, respectively. Since joining Iowa State University, her research has been supported by the US National Science Foundation (NSF), US Agency for Healthcare Research and Quality, the National Institute of Diabetes and Digestive and Kidney Diseases, Mayo Clinic Rochester, and Iowa Department of Economic Development. She was awarded a NSF Career award, the 2006 American College of Gastroenterology Governors Award for Excellence in Clinical Research for “The Best Scientific Paper”, a US patent on Colonoscopy Video Processing for Quality Metrics Determination, the Association for Education in Journalism and Mass Communication “Top Teaching Paper” award. She has served as an editorial board member for ACM SIGMOD Digital Symposium Collection, an NSF panel reviewer, a program committee member, and a referee for reputable conferences and journals.


Related Events

JCSSE2018

Important dates

Full Paper Submission:
May 22, 2018
May 27, 2018
Acceptance Notification:
June 19, 2018
Camera-ready Manuscript:
June 29, 2018
Author Registration:
June 19-30, 2018

Early-bird Registration:
June 19-30, 2018
Regular Registration:
July 1-13, 2018
Online Registration Deadline:
July 5, 2018
On-site Registration:
July 11-13, 2018
Tutorial and Conference Dates:
July 11-13, 2018