WHAT IS SMARTGUIDANCE?
SmartGuidance'17 is the 2nd International Workshop on Intelligent Personal Support of Human Behavior. The workshop is held in conjunction with UbiComp'17 at Maui, Hawaii, USA.
In today's fast-paced environment, humans are faced with various problems such as information overload, stress, health and social issues. So-called anticipatory systems promise to approach these issues through personal guidance or support within a user's daily and professional life. We believe that anticipatory mobile computing is one of the next emerging research field after mobile sensing, context recognition and prediction.
The workshop aims to share experiences of current researches on anticipatory systems in order to understand the extent of how such systems could be a solution and how they could provide personal guidance given the discovered traits of human behavior.
We invite the submission of papers in the emerging, interdisciplinary research field of anticipatory mobile computing which focus on understanding, design, and development of such systems. We also welcome contributions that investigate human behaviors, underlying recognition and prediction models; conduct field studies; as well as propose novel HCI techniques to provide personal support.
Please submit to Easychair. The deadline for submission is June 19, 2017, 23:59 AoE.
All accepted papers will be included in the ACM Digital Library and adjunct proceedings of the main conference.
June 19, 2017, 23:59 AoE (deadline extended!)
July 04, 2017 (extended)
July 14, 2017 (extended)
September 11, 2017
University College London, UK
He is a postdoctoral research associate working with Mirco Musolesi at University College London. His main areas of interest include mobile sensing, context-aware computing and anticipatory computing. His research focuses on understanding and predicting human behaviour for interacting with mobile devices by using contextual information obtained from the embedded sensors.
Keynote: "Modeling Human Behavior through Mobile Sensing"
Smartphones have graduated over a period of time from merely calling instruments to smart and highly personal devices. Besides being technically advanced and pervasive, these devices have a plethora of embedded sensing capabilities that enables us to passively log users' context and collect such data at an unprecedented scale. In this talk I will be discussing the understanding and modeling of human behavior through mobile sensing and machine learning. More specifically, I will focus on modeling users' interaction with mobile devices, and anticipatory monitoring of health and well-being.