The past decade has seen a substantial development of mobile systems and networks enabling the development of several novel mobile services and applications. With the current extreme miniaturization of components of many sensor systems, the availability of advanced computing resources, the expansion of the Internet of Things (IoT), mobile systems and networks are growing increasingly complex and becoming smarter. Smart mobile systems, networks, and applications will be the major technology behind smart-computing domains like smart homes, connected health, connected cars, automated enterprise workflows, smart cities, and smart grids.

In recent years, the world has seen many major breakthroughs in machine learning (ML) and artificial intelligence (AI) research. For example, the recent researches in learning techniques have brought revolutionary advances in machine learning allowing devices and systems to learn to function on their own. By integrating the advances in mobiles systems and the advances in machine learning, the future role of smart mobile systems, networks, and applications is becoming limitless and it’s expected to revolutionize the future of the world within the next few years. This is especially important as mobile systems generate ever-growing and evolving collections of data, calling for dedicated ML/AI techniques capable of handling streaming and lifelong learning problems.

ThinkSys’19 is focused on providing a significant contribution to the problem of designing intelligent, robust, and adaptive mobile systems, networks and applications with the aid of machine learning algorithms that are able to autonomously and continuously adapt and improve their performance. ThinkSys’19 aims at bringing together experts from several research communities spanning mobile systems, networking, machine learning, sensing, and big data to discuss significant contributions, community interests, challenges to be addressed, tools to be developed, and new research problems to the problem of designing intelligent, robust, and adaptive mobile systems, networks and applications with the aid of machine learning algorithms.

Topics of Interest

We encourage inter-disciplinary contributions bridging the gap between machine learning and mobile systems and networks from either a theoretical perspective or a practical point of view. We put special emphasis on adaptive, evolving, and streaming ML systems, as well as on lifelong learning architectures. The research topics of interest to ThinkSys 2019 workshop include (but are not limited to) the following:

• Theoretical foundations of ML for mobile systems, networks, and applications
• ML probabilistic and statistical models for mobile systems, networks, and applications
• ML techniques for sensing and sensor systems
• New knowledge discovery theories and models from mobile systems data
• Explainable AI and ML for mobile systems
• Mobile systems and network-oriented big data and data analytics
• Adaptive ML architectures for handling network-oriented evolving data streams
• ML techniques for lifelong learning from mobile and network data
• ML techniques for cloud and edge systems, applications and services
• New approaches of data pre-processing, post-processing, sampling approaches, feature selection, and feature transformation for mobile applications
• Personalized/transfer learning for mobile systems
• ML for smart cities and cyber-physical systems.
• ML for Internet of Things (IoT) devices, Complex systems, and systems-of-systems
• Data collection and analytic techniques for mobile systems and applications
• Experiences in real-world mobile systems and applications
• Human factors in ML and human-ML interactions for mobile systems
• Privacy-protecting and secure ML
• ML for localization and location based services
• Measurements, experimental systems and test-beds of smart mobile systems, networks, and applications
• Blockchain and other consensus approaches for mobile systems and applications
• ML for cooperative driving, intelligent and autonomous vehicles
• ML for robotic networks and swarm intelligent computing domains
• ML for intelligent Wireless Communications and networking architecture

Workshop Organizers

• Tamer Nadeem - Virginia Commonwealth University - Department of Computer Science
• Bartosz Krawczyk - Virginia Commonwealth University - Department of Computer Science

Important Dates

• Paper submission deadline: April 14, 2019 - 11:59:59pm PST - Extended
• Notification of acceptance: April 21, 2019
• Camera-ready copy due: May 1, 2019
• Workshop date: June 21, 2019

Paper Submission

All submissions must be original research not under review at any other venue. Submissions will be evaluated on the basis of technical quality, novelty, potential impact, and clarity. Solicited submissions include both full technical workshop papers and white position papers. The maximum length of such submissions is 6 pages, and if accepted they will be published by ACM and appear in the ACM Digital Library. Formatting for all submissions (excluding page length) must adhere to the guidelines here: https://www.sigmobile.org/mobisys/2019/submission/.

All submissions must be uploaded to the workshop submission site https://thinksys19.hotcrp.com/paper/new/. In accordance with MobiSys 2019 conference, this workshop will adopt the double-blind review policy. Any questions regarding submission issues should be directed to Tamer Nadeem (tnadeem@vcu.edu).