In this 2021 first Annual World AI-BigData Convergence (ABC) Forum, seven world-renowned speakers from both academia and industry will discuss the issues and problems surrounding the vision of Artificial Intelligence (AI) and Big Data confluence and propose ground-breaking solutions with a full awareness of potential benefits and risks.
The objective of this World Forum is to explore the current status and R&D opportunities and issues in the convergence (or confluence) of AI and BigData from a data centric perspective. The objective of the ABC initiative, as defined by Prof. Won Kim in his keynote for iiWAS-2021, is to help propel the current smart data processing to the next level. The ABC vision is based on advancing both AI and Big Data through fuller uses of data and through AI and big data leveraging each other. The fuller uses of data include the use of higher quality data and multimodal data for both AI and Big Data.
Due to the large number of speakers and the importance of what they have to offer, we will organize the World Forum into two sessions over two days: four speakers on November 29, and three speakers on November 30. Please join us in what we expect will be a very informative, productive, and exciting Forum.
Won Kim, Woong-Kee Loh, School of Computing, Gachon University, South Korea
Woong-Kee Loh received his B.S., M.S., and Ph.D. degrees in computer science from the Korea Advanced Institute of Science and Technology (KAIST), South Korea, in 1991, 1993, and 2001, respectively. He was a Visiting Scholar with the Department of Computer Science and Engineering, University of Minnesota, USA. He is currently a Full Professor with the School of Computing, Gachon University, South Korea. His research interests include massively parallel largescale data mining, nearest neighbor search in road networks, federated learning, and fault detection and classification using sensor streaming data.
He has served as a Program Committee Member and an Organizing Committee Member for many international conferences, including DaWaK 2007~2008, CIKM 2009, PAKDD 2011~2014, ICDE 2015, SSTD 2015, DASFAA 2017, and BigComp 2017~2018 and 2020~2021.
Program and Speakers
Day 1 (Monday, November 29):
- Mining Hidden Structures from Massive Unstructured Text
Prof. Jiawei Han (University of Illinois at Urbana-Champaign, USA)
- Deep Knowledge from Shallow Data: Machine Learning on Wearables Data for Medical Insights into Chronic Conditions
Prof. Jaideep Srivastava (University of Minnesota, USA)
- AI and BigData for Molecular Diagnostics, a Seegene’s Approach
Dr. Kyungoh Min (Seegene, Inc., South Korea)
- AsterixDB Meets Machine Learning
Prof. Michael J. Carey (University of California at Irvine, USA)
Co-contributors: Ian Maxon and Phanwadee (Gift) Singthong (UC Irvine)
Day 2 (Tuesday, November 30):
- AI-Powered Network Security
Prof. Elisa Bertino (Purdue University, USA)
- Applying Deep Learning to New Vision Sensors for Extreme Imaging Conditions
Prof. Yong Ju Jung (Gachon University, South Korea)
- Towards Trustworthy Data Science
Prof. Jian Pei (Simon Fraser University, British Columbia at Burnaby, Canada)