Keynote Title: Creating a Conversational Search System
Abstract: The Conversational Search Paradigm promises to satisfy information needs using human-like dialogs, be it in spoken or in written form. This kind of “information-providing dialogs” will increasingly happen en-passant and spontaneously, probably triggered by smart objects with which we are surrounded such as intelligent assistants (Alexa, Siri, etc.), domestic appliances, environmental control devices, toys, or autonomous robots and vehicles. Currently, our understanding is still too limited to exploit the Conversational Search Paradigm for effectively satisfying the existing diversity of information needs. In this talk, I will describe a roadmap for establishing a new interdisciplinary research community around Conversational Search.
Biography: Professor Sanderson is a researcher in information retrieval (IR) (e.g. web search engines). He is particularly interested in evaluation of search engines, but also works in geographic search, cross language IR (CLIR), summarisation, image retrieval by captions and word sense ambiguity.
Mark is an Associate Editor of ACM Transactions on the Web and IEEE Transactions on Knowledge and Data Engineering. He is co-editor of Foundations and Trends in Information Retrieval and a visiting professor at the National Institute of Informatics (NII) in Tokyo.
Keynote Title: Translational Computer Science
Abstract: Given the increasingly pervasive role and growing importance of computing and data in all aspects of science and society fundamental advances in computer science and their translation to the real world have become essential. Consequently, there may be benefits to formalizing translational computer science (TCS) to complement the traditional foundational and applied modes of computer science research, as has been done for translational medicine. TCS has the potential to accelerate the impact of computer science research overall. In this presentation, I will discuss the attributes of TCS, and formally define it. We enumerate a number of roadblocks that have limited its adoption to date and sketch a path forward.
Biography: David Abramson has been involved in computer architecture and high performance computing research since 1979. Previous to joining the University of Queensland in 2013, he has held appointments at Monash University, Griffith University, CSIRO, and RMIT. At CSIRO, he was the program leader of the Division of Information Technology High Performance Computing Program and was also an adjunct associate professor at RMIT in Melbourne. He served as a program manager and chief investigator in the Co-operative Research Centre for Intelligent Decisions Systems and the Co-operative Research Centre for Enterprise Distributed Systems. At Monash, he served as the Science Director of the Monash e-Research Centre and Director of the Monash e-Education Centre. He is currently the director of the UQ Centre for Research Computing and an adjunct professor in the School of IT and EE. He is a fellow of the Association for Computing Machinery (ACM), the Institute of Electrical and Electronic Engineers (IEEE), the Australian Academy of Technology and Engineering (ATSE), and the Australian Computing Society (ACS).
Keynote Title: Collective Computing by Complex Intelligent Robotic Systems
Abstract: We consider the necessity of decentralized collective computing for effective operations of complex intelligent robotic systems deployed in unstructured environments. Specifically, we consider the problem of collectively exploring unknown and dynamic environments with a decentralized heterogeneous multi-robot system afforded with significant computing capabilities. Our swarm of floor-mapping robots exhibiting scalability, robustness and flexibility. These properties are systematically tested and quantitatively evaluated in unstructured and dynamic environments, in the absence of any supporting infrastructure. The results of repeated sets of experiments show a consistent performance for all three features, as well as the possibility to inject units into the system while it is operating. Although the occupancy-grid maps obtained can be large, they are fully distributed. Not a single robotic unit possesses the overall map, which is not required by our cooperative path-planning strategy.
Biography: : Roland Bouffanais is Associate Professor and Director of Graduate Studies at the Singapore University of Technology and Design (SUTD). He received his Ph.D. from EPFL (Lausanne, Switzerland) in computational science for which he received the prestigious IBM Research Prize in Computational Sciences (2008) and the ERCOFTAC Da Vinci Award Silver Medal (2007). He has been a postdoctoral fellow and associate at MIT and still is a research associate with the Department of Mechanical Engineering at MIT. Bouffanais’ research group focuses on fundamental and applied interdisciplinary problems rooted in the field of complexity science. Bouffanais leads a number of active projects at SUTD related to complex networks and self-organizing systems, including swarming systems. He has recently authored a monograph titled “Design and Control of Swarm Dynamics”, published by Springer in their Complexity Series in 2016.
Keynote Title: Context-rich behaviour recognition for proactive intelligent assistance
Abstract: User contexts are the most influential signals in analysing human behaviours, particularly when dealing with heterogenous multivariate sensor data from smartphones and wearables, buildings, cities, and urban areas.
I will present our generic temporal segmentation techniques that we have used for processing multivariate sensor data, especially for modelling complex human activities, routine behaviours, and urban dynamics. I will also present our trajectory modelling and spatio-temporal prediction and recommendation techniques that we have used for multiple applications, leveraging context-rich information from human behaviours, towards developing proactive and personalised intelligent assistance.
Biography: Flora Salim is an Associate Professor at School of Science, RMIT University. Her research interests include context and behaviour modelling, time-series and spatio-temporal data mining, and pattern recognition and machine learning. She is a Humboldt-Bayer Fellow (from Bayer Foundation GmbH), Humboldt Fellow — experienced researcher (from Alexander von Humboldt Foundation), Victoria Fellow 2018 (frome Victorian government). She was the recipient of the the RMIT Vice-Chancellor’s Award for Research Excellence – Early Career Researcher 2016; the RMIT Award for Research Impact – Technology 2018; Victorian iAwards (2014), Australian Research Council (ARC) Postdoctoral Research Industry (APDI) Fellow (2012-2015); IBM Smarter Planet Industry Skills Innovation Award (2010); and a Google Anita Borg Scholar (2008). She obtained her PhD from Monash University in 2009, prior to which she worked as a Senior Software Engineer in the IT sector, developing real-time signal and content monitoring solutions for the broadcasting industry. She also had a 3-year experience working as a postdoc in an ARC Linkage project in the Architecture, Engineering, and Construction domain prior to her APDI fellowship. She obtained her Bachelor of Computing (Hons) with First Class Honours from Monash University in 2004, and she received the Best Thesis Award in her undergraduate Honours from Australian DSTC. She is an Associate Editor of the PACM on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), and an Area Editor of Pervasive and Mobile Computing. She is the Deputy Director of RMIT Centre for Information Discovery and Data Analytics, and the Co-Lead Investigator of Microsoft Cortana Intelligence Institute at RMIT.