Tutorial

Title: Research Methodology on Pursuing Impact-Driven Research

Speaker: Prof. Tao Xie, IEEE Fellow, University of Illinois at Urbana-Champaign, USA

Time: 09:30-10:30, 10:50-11:50, 13:30-14:30, 3, January 2019 (Thursday)

Address: Lecture Hall, Science Museum, Hangzhou Dianzi University(杭州电子科技大学科技馆二楼扇形会议室)

Tao Xie

Abstract

Conducting research to produce impact has been an important, yet challenging task for the research community. This technical debriefing presents experience sharing of research methodology on pursuing impact-driven research, such as how to select research problems to work on, how to map out a research agenda, and how to write research papers. General advice materials on research methodology can be found on the presenter's advice portal: http://taoxie.cs.illinois.edu/advice/

Speaker’s Biography

Tao Xie is a Professor and Willett Faculty Scholar in the Department of Computer Science at the University of Illinois at Urbana-Champaign, USA. He worked as a visiting researcher at Microsoft Research. His research interests are in software engineering, with focus on software testing, software analytics, software security, and intelligent software engineering. He received an NSFCAREER Award, a Microsoft Research Outstanding Collaborators Award, Microsoft Research Software Engineering Innovation Foundation (SEIF) Award, a Google Faculty Research Award, an IBM Jazz Innovation Award, and three-time IBM Faculty Awards. He served as the ISSTA 2015 Conference Program Chair and the Tapia 2017/2018 Conference Program/General Chair, and will serve as an ICSE 2021 Program Co-Chair. He has been an Associate Editor of the IEEE Transactions on Software Engineering (TSE) and the ACM Transactions on Internet Technology (TOIT), along with an Editorial Board Member of Communications of ACM (CACM). He is an ACM Distinguished Speaker and was an IEEE Computer Society Distinguished Visitor. He was named an ACM Distinguished Scientist in 2015 and an IEEE Fellow in 2018. His homepage is at http://taoxie.cs.illinois.edu.

Keynote Talks

Keynote I

Title: On Landing Reinforcement Learning in Real-World Applications

Speaker: Dr. Yang Yu, Nanjing University

Time: 09:00-10:00, 4, January 2019 (Friday)

Address: Lecture Hall, Science Museum, Hangzhou Dianzi University(杭州电子科技大学科技馆二楼扇形会议室)

Yang Yu

Abstract

Reinforcement learning achieved significant successes include being part of the AlphaGo system and playing Atari games. However, it is also criticized for applicability only in virtual worlds due to the requirement of huge amount of interaction data. In this talk, we will report our recent experience towards real-world reinforcement learning, including virtualizing real-world environments and reusing virtual-world policies in the real world.

Speaker’s Biography

Yang Yu is an associate professor of computer science in Nanjing University, China. He joined the LAMDA Group as a faculty since he got his Ph.D. degree in 2011. His research interest is in machine learning, a sub-field of artificial intelligence. Currently, He is working on reinforcement learning in various aspects, including optimization, representation, transfer, etc. He was recommended as AI’s 10 to Watch by IEEE Intelligent Systems in 2018, invited to have an Early Career Spotlight talk in IJCAI’18 on reinforcement learning, and received the Early Career Award of PAKDD in 2018. His homepage is at http://lamda.nju.edu.cn/yuy/.

Keynote II

Title: Intelligent Software Engineering: Synergy between AI and Software Engineering

Speaker: Prof. Tao Xie, IEEE Fellow, University of Illinois at Urbana-Champaign, USA

Time: 09:00-10:00, 5, January 2019 (Saturday)

Address: Lecture Hall, Science Museum, Hangzhou Dianzi University(杭州电子科技大学科技馆二楼扇形会议室)

Abstract

As an example of exploiting the synergy between AI and software engineering, the field of intelligent software engineering has emerged with various advances in recent years. Such field broadly addresses issues on intelligent [software engineering] and [intelligence software] engineering. The former, intelligent [software engineering], focuses on instilling intelligence in approaches developed to address various software engineering tasks to accomplish high effectiveness and efficiency. The latter, [intelligence software] engineering, focuses on addressing various software engineering tasks for intelligence software, e.g., AI software. This talk will discuss recent research and future directions in the field of intelligent software engineering.