PAKDD2017

The Pacific-Asia Conference on Knowledge Discovery and Data Mining

May 23-26, 2017, Jeju, South Korea

Photograph courtesy of Jeju Tourism Organization

Keynote speakers

Sang Kyun Cha

Title

Toward Digital Transformation of Industry, Education, and Government for the Fourth Industrial Revolution

Abstract

The world is in race for compelling AI services such as digital assistant and autonomous driving. The big data collected from these services not only improve the service quality but also enable expansion to new services. The formation of this virtuous cycle between AI services and big data leads to transformation of industry, which involves dismantling vertical and horizontal industrial boundaries and shifting the overall industrial leadership to those leading this race. The so-called “fourth industrial revolution” refers to this broad scale of digital transformation.

If the ongoing transformation is indeed a new industrial revolution, the history tells that the shift of job demand is inevitable and many people will suffer from the mismatch between the new job demand and the slowly changing educational institutions. The exponential growth of data scientist and engineers in the leading Silicon Valley companies is an early indication of this job shift.

In this talk, I will review the efforts of digital transformation across the globe and provide recommendations on universities and governments to lead the digital transformation in the era of the fourth industrial revolution.

Bio

Dr. Sang Kyun Cha is a professor at Seoul National University and also an innovator and entrepreneur who achieved his dream of shifting enterprise software industry to the real-time in-memory big data paradigm. After SAP’s secret acquisition of his Silicon Valley startup Transact In Memory, Inc. in late 2005, he led SAP’s internal research on enterprise-scale in- memory big data technology. This effort led SAP to start the company-wide project of developing HANA in-memory computing platform, and SAP’s business transformation around HANA. Professor Cha took the co-responsibility of leading SAP HANA project with German colleagues. SAP’s market value as of March 2017 has more than doubled to 110 billion euros since HANA announcement.

In early 2014, after seeing SAP HANA’s success in the market, he fully returned to Seoul National University and started Big Data Institute to promote trans-disciplinary data science research across all academic disciplines. In April 2017, he led the establishment of Urban Data Science Laboratory downtown in Gangnam of Seoul, to solve urban problems such as mobility, gentrification, and environmental issues with data science approach. Seoul city government sponsors $9 million for three years. He also led the establishment of Korean-government-sponsored center for transformation of young talents to big data, AI, and robotics specialist.

As a general chair of IEEE Data Engineering Conference held in Seoul in 2015, he led the conference to become the most successful one in a decade, and since then he has been serving on the conference steering committee, and leading the ten-year most influential paper award committee. He has been serving on numerous boards such as a member of trustees of Seoul National University from 2014 to 2016, a member and vice-chairman of Aumni-Netwerk Deutschland Korea from 2015, and an external director of Korea Telecom. Professor Cha received his BS and MS at Seoul National University in 1980 and 1982, respectively, and his PhD at Stanford University in 1991. He received Korean medal of honor in 2014 for his pioneering research and his entrepreneurial role of creating the market paradigm shift starting from academic research.

Rakesh Agrawal

Title

Big Data or Big Garbage? A Tale of a Quest for Insights from Social Data

Abstract

We present the story of a research expedition (code-named WaveFour) into building an enterprise-scale, real-time business intelligence system over social data. We discuss what drove us to undertake this journey and the system prototype we built. We also describe the investigation we carried out to assess the overlap between Google and Bing search results and whether including social data in the mix can produce different and useful results. We conclude with lessons learned and future directions.

Bio

Rakesh Agrawal is the President and Founder of the Data Insights Laboratories, San Jose, USA. He is also the Rukmini Visiting Chair Professor at the Indian Institute of Science, Bangalore, India and a Visiting Professor at EPFL, Lausanne, Switzerland. He is a member of the National Academy of Engineering, both USA and India, a Fellow of ACM, and a Fellow of IEEE. He has been both an IBM Fellow and a Microsoft Fellow. ACM SIGKDD awarded him its inaugural Innovations Award and ACM SIGMOD the Edgar F. Codd Award. He was named to the Scientific American’s First list of top 50 Scientists. Rakesh has been granted 80+ patents and published 200+ papers, including the 1st and 2nd highest cited in databases and data mining. Five of his papers have received “test-of-time” awards. His papers have received 100,000+ citations. His research formed the nucleus of IBM Intelligent Miner that led the creation of data mining as a new software category. Besides Intelligent Miner, several other commercial products incorporate his work, including IBM DB2 and WebSphere and Microsoft Bing.

Dacheng Tao

Title

Meet Artificial Intelligence in Sydney

Abstract

Since the concept of Turing machine has been first proposed in 1936, the capability of machines to perform intelligent tasks went on growing exponentially. Artificial Intelligence (AI), as an essential accelerator, pursues the target of making machines as intelligent as human beings. It has already reformed how we live, work, learning, discover and communicate. In this talk, I will review our recent progress on AI by introducing some representative advancements from algorithms to applications, and illustrate the stairs for its realization from perceiving to learning, reasoning and behaving. To push AI from the narrow to the general, many challenges lie ahead. I will bring some examples out into the open, and shed lights on our future target. Today, we teach machines how to be intelligent as ourselves. Tomorrow, they will be our partners to get into our daily life.

Bio

Dacheng Tao is Professor of Computer Science and ARC Future Fellow in the School of Information Technologies and the Faculty of Engineering and Information Technologies at The University of Sydney. He was Professor of Computer Science and Director of the Centre for Artificial Intelligence in the University of Technology Sydney. He mainly applies statistics and mathematics to Artificial Intelligence and Data Science. His research interests spread across computer vision, data science, image processing, machine learning, and video surveillance. His research results have expounded in one monograph and 500+ publications at top journals and conferences, such as IEEE T-PAMI, T-NNLS, T-IP, JMLR, IJCV, IJCAI, AAAI, NIPS, ICML, CVPR, ICCV, ECCV, ICDM; and ACM SIGKDD, with several best paper awards, such as the best theory/algorithm paper runner up award in IEEE ICDM’07, the best student paper award in IEEE ICDM’13, and the 2014 ICDM 10-year highest-impact paper award. He received the 2015 Australian Scopus-Eureka Prize, the 2015 ACS Gold Disruptor Award and the 2015 UTS Vice-Chancellor’s Medal for Exceptional Research. He is a Fellow of the IEEE, OSA, IAPR and SPIE.


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