Title: Challenges in Complexity Science--Exploring the case of Human Behavior

     14:00-14:45, Tuesday, June 19, 2018

Speaker: Zhen Wang, Northwestern Polytechnical University, China

Abstract:  One of the most elusive scientific challenges for over 150 years has been to explain why cooperation survives despite being a seemingly inferior strategy from an evolutionary point of view. Over the years, various theoretical scenarios aimed at solving the evolutionary puzzle of cooperation have been proposed, eventually identifying several cooperation-promoting mechanisms: kin selection, direct reciprocity, indirect reciprocity, network reciprocity, and group selection. We report the results of repeated Prisoner’s Dilemma experiments with anonymous and onymous pairwise interactions among individuals. We find that onymity significantly increases the frequency of cooperation and the median payoff per round relative to anonymity. Furthermore, we also show that the correlation between players’ ranks and the usage of strategies (cooperation, defection, or punishment) underwent a fundamental shift, whereby more prosocial actions are rewarded with a better ranking under onymity. Our findings prove that reducing anonymity is a valid promoter of cooperation, leading to higher payoffs for cooperators and thus suppressing an incentive—anonymity—that would ultimately favor defection.

Short Bio:  Zhen Wang is a Distinguished Professor (via National 1000 Talents Program, the Recruitment Program of Global Experts) at Northwestern Polytechnical University (NPU). He is also a Senior Member of Japanese Society for the Promotion of Science (JSPS), honorary/guest professor in several China, Japan and Europe universities. His research focuses on complex networks, information networks and data science. Heretofore, Prof. Wang has published more than 100 papers and books, including 4 Physics Reports (IF>17), 2 PNAS, 1 Nature Communications, 1 Science Advances, 4 Physics of Life Reviews (IF>13), and IEEE Transaction journals, etc. His total citation is around 7000, H-index is 41. His researches were highlighted in Nature, Science, PNAS, etc., broadly reported by well-known academic media such as Science, Nature News, LiveScience, Science Daily, Phys. Org, EurekAlert, Yahoo!News, Scientific American ScienceNet, etc. Based on his research, Prof. Wang obtained MIT Technology Review (China) Innovators Under 35, Annual Best/highlighted Paper Awards, Annual Excellent Reviewer Award from Elsevier and IOP journals for several times, and won the Most Downloaded Articles, the Most Cited Articles with Elsevier and Nature Publishing Group journals. He also serves as the editors of 7 scientific journals.

Title: 7 Language-oriented Tasks that Have Not Been Explored Enough by Deep Learning

     14:45-15:30, Tuesday, June 19, 2018

Speaker: Kyubyong Park, Kakao Brain, Korea

Abstract: Deep Learning has made a real breakthrough across domains. As for language, the performance of deep learning in some tasks such as machine translation for major languages or speech synthesis with enough training data seems close to that of humans. However, of course, there are still a lot of language-related tasks waiting for the further exploration of deep learning. Seven interesting projects among them are briefly introduced in this talk.

Short Bio: Kyubyong Park is an A.I. Researcher at Kakao Brain. He studied Linguistics at SNU and Univ. of Hawaii. Park is a generic/computational linguist who loves both language and computers equally. His research interests include language, natural language processing, lexicography, machine learning, and A.I.

Title: Integrity Assurance for Outsourced Databases in Cloud Computing Era

     08:30-09:15, Wednesday, June 20, 2018

Speaker: Haibo Hu, Hong Kong Polytechnic University

Abstract: With the increasing availability of cloud computing facilities and their decresing costs, there is a trend for data owners to host their databases in the cloud, by subscribing a database-as-a-service such as Amazon RDS, Google Cloud Bigtable, and Microsoft Azure SQL Database. However, despite the reduced operation costs, such an outsourced database can have trust issues. That is, the integrity of both the data and the query results from this database can be compromised by server tampering and fabrication. In this talk, I will discuss the basic tools in integrity assurance for outsourced databases. Then I will show some concrete examples on how they are adopted in state-of-the-art database research.

Short Bio: Dr. Haibo Hu is an assistant professor in the Department of Electronic and Information Engineering, Hong Kong Polytechnic University. His research interests include information security, privacy-aware computing, wireless data management, and location-based services. He has published over 60 research papers in refereed journals, international conferences, and book chapters. As principal investigator, he has received over 6 million HK dollars of external research grants from Hong Kong and mainland China. He is the Panel Co-chair of DASFAA 2011, and Program Co-chair of DaMEN 2011, 2013 and CloudDB 2011. He is also the recipient of a number of titles and awards, including WAIM Distinguished Young Lecturer, ACM-HK Best PhD Paper Award, Microsoft Imagine Cup, and GS1 Internet of Things Award.

Title: Tencent Realtime Protect (TRP): An AI-driven Anti-virus Engine for Android

     09:15-10:00, Wednesday, June 20, 2018

Speaker: Pu Wang, Tencent Anti-fraud Lab, China

Abstract: Tencent Anti-fraud Lab has more than ten years of experience in combating and fighting against underground economy, and is one branch of TenSec United Lab. Generally, phishing, malware and phone spoofing are common fraud means, which can cause billions of losses to the victim. Our anti-fraud detection in three aspects represent the top level in the industry, escorting Tencent products (such as QQ, Wechat, etc.) and protecting the majority of Internet users (by Tencent Mobile Manager, Tencent PC Manager). Especially, the APK-virus detection engine detects 2.5 million malicious program by responding 10 billion times and processing 15 million files every day. An AI-driven anti-virus engine TRP for Android will also be introduced in this talk.

Short Bio: Dr. Wang Pu received B.Eng. and Ph.D. in Computer Science from University of Science and Technology of China in 2008 and 2013, respectively. He was a Research Fellow in Center for Computational Intelligence of Nanyang Technological University in Singapore from 2013 to 2014.
Dr. Wang currently is a Senior Researcher with Tencent Anti-fraud Lab, which mainly aims at detecting risks from APK virus, malicious websites and phone numbers. Dr. Wang is the core researcher in building Lingkun financial security big data platform. In particular, He develops device fingerprint techniques for financial anti-fraud, including trusted devices and device tracking. Dr. Wang and his team also focus on large-scale gragh mining techniques such as graph based classification, clustering and embedding, used for analysis of illegal groups in heterogeneous graph scenarios with a scale of one billion vertices and nearly one hundred billion edges.