Jonathan is a Research Scientist at PARC, where his research focuses on the use of machine learning and deep learning in biomedical and physiological data. He is interested in the analysis of data from mobile and wearable devices for pervasive and ubiquitous health management purposes. He has investigated how mobile and wearable technology can be used within health condition management systems for disorders such as panic disorder, post-traumatic stress disorder and depressive disorder. He is particularly interested in the analysis of physiological data in order to infer information about psychological state. His research interests include affective computing, ubiquitous computing, artificial intelligence, machine learning, deep learning, and physiological data analysis. Jonathan holds a Ph.D. from the University of Auckland where his research focused on the use of artificial intelligence for strategy generation in computer games.
Jonathan will use the data that CrowdSignals.io provides to improve and broaden the types of activity recognition that currently exist. In addition, he will use physiological data from wearable devices for affective computing purposes.
At PARC: https://www.parc.com/about/people/2670/jonathan-rubin.html
On GitHub: https://github.com/jrubin01
Adam has a first degree in Psychology from the University of London (Goldsmiths College), and a PhD in social psychology from the University of Hertfordshire (on self-esteem and motivation). Immediately after my PhD, he worked at the University of Glamorgan as a lecturer in social psychology (from 1995 until 1999). He then joined the Institute of Educational Technology at the Open University as a lecturer (and then senior lecturer) in ICT and Social Science (from 1999 until 2007). Adam joined the University of Bath, School of Management in June 2007, first as a senior lecturer, then as a Reader in ‘Information Systems’. In September 2012 he joined UWE Bristol as Professor of Behavioural Change, and returned to the University of Bath in January 2016 to become Professor of Information Systems. Adam works at the intersection between human sciences and technology – on topics such as communication, social media, wearable technology and behaviour, and privacy / surveillance / cyber-security.
Adam is particularly interested in issues of public-private space and activity, mood and use, and patterns of behaviour. He also hopes to use the CrowdSignals.io data sets in a new Masters course at Bath to help train future data scientists.
University of Bath Homepage
Connect with Adam on LinkedIn
Christian is an Associate Professor at the University of Notre Dame Department of Computer Science and Engineering where he directs the Mobile Computing Lab (M-Lab). His team studies systems and methods that combine various types and sources of information to develop new or improved context-aware applications and services. Examples of such research challenges include: how can we reduce localization and tracking errors using opportunistic sharing of data between mobile devices; how can we detect and assess health problems using information collected from mobile device and wearables; and what can we learn about the relationships between behaviors, health and wellbeing, social ties, etc., using data collected from smartphones?
The key to building context-aware services is access to large-scale and longitudinal data sets, which are difficult to collect. The CrowdSignals.io data will provide contextual information that can help Christian’s team to answer various questions about human behavior and correlations between various forms of activities, traits, and preferences.
Homepage at Notre Dame: http://www3.nd.edu/~cpoellab/
M-Lab site: http://m-lab.cse.nd.edu/
Our second in a series of expert guest posts comes from Bilgin Kosucu, a doctoral student in the WiSe group at Bogazici University Computer Engineering Department. He provides a brief history of their unique and diverse group and writes about their work with wireless sensors and wearables in Turkey.
WiSe, the Wireless Sensor Research group of Bogazici University Computer Engineering Department, is one of the largest research groups in its area in Turkey. Currently the group consists of 4 full time faculty members, a medical doctor, 12 PhD candidates and 10 MS students.
WiSe was established by a computer networks researcher who then extended the work to wireless sensors. Eventually, the research on wireless sensor networks expanded to include wearable/ambient sensors and mobile phones. Currently, we are involved with the analysis of daily activities, ambient assisted living and elderly healthcare including but not limited to the UBI-HEALTH Project, supported by the EC Marie Curie IRSES Program.
As a group we are experienced of designing and developing mobile data collection platforms (e.g. on Android phones and Samsung Galaxy Gear S smartwatches), but we believe that CrowdSignals.io will build a unique database, having dedicated data annotators and considering the immense difficulty of gathering the ground truth data. This database will serve as common platform, owing its popularity to being a crowd funded collaboration, for researchers to test and compare their algorithms.
In addition to the opportunity of applying our previous research of activity recognition to a well defined and standardized dataset, we hope to reach out to the wearable computing community and build the pavement for finer research through advanced collaboration.
How to reach us:
WiSe group: http://netlab.boun.edu.tr/WiSe/doku.php/home?id=home
Computer Engineering Department: http://www.cmpe.boun.edu.tr/
UBI-HEALTH Project: http://www.ubihealth-project.eu/
Dr. Flora Salim is a Senior Lecturer at the Computer Science and IT department, School of Science, RMIT University. Her research interests are mobile data mining, context-aware computing, activity and behaviour recognition, and context and semantic learning. Her research seeks to enhance user experience by monitoring their behaviours and how they use and interact with their environments, such as in smart home, smart cities, urban transport and mobility, using ambient technologies and ubiquitous computing. Her recent work focuses on analysing and predicting the fine-grained behaviours in human mobility by leveraging heterogeneous sensor data. Previously, she was a Research Fellow at RMIT Spatial Information Architecture Laboratory and an Honorary Research Fellow and Associate Lecturer at Faculty of Information Technology, Monash University. She obtained her PhD in Computer Science from Monash University in 2009. She has secured grants from Australian Research Council, IBM Smarter Cities Lab, Australian Urban Research Infrastructure Network, and numerous industry partners.
Flora will use the CrowdSignals.io data to conduct multiple activity recognition tasks for the purpose of situation recognition.
Follow Flora on Twitter