HASCA 2020: 8th International Workshop On Human Activity Sensing Corpus And Applications

http://hasca2020.hasc.jp

ORGANIZERS

Kazuya Murao (Ritsumeikan University, Japan), Yu Enokibori (Nagoya University, Japan), Hristijan Gjoreski (Ss. Cyril and Methodius University, Macedonia), Paula Lago (Kyushu Institute of Technology, Japan), Tsuyoshi Okita (Kyushu Institute of Technology, Japan), Pekka Siirtola (University of Oulu, Finland), Kei Hiroi (Nagoya University, Japan), Philipp M. Scholl (University of Freiburg, Germany), Mathias Ciliberto (University of Sussex, UK)

WORKSHOP SUMMARY

The recognition of complex and subtle human behaviors from wearable sensors will enable next-generation human-oriented computing in scenarios of high societal value (e.g., dementia care). This will require large-scale human activity corpuses and much improved methods to recognize activities and the context in which they occur.

This workshop deals with the challenges of designing reproducible experimental setups, running large-scale dataset collection campaigns, designing activity and context recognition methods that are robust and adaptive, and evaluating systems in the real world. We wish to reflect on future methods, such as lifelong learning approaches that allow open-ended activity recognition.

The objective of this workshop is to share the experiences among current researchers around the challenges of real-world activity recognition, the role of datasets and tools, and breakthrough approaches towards open-ended contextual intelligence. This year HASCA will also welcome papers from participants to the Third Sussex-Huawei Locomotion and Transportation Recognition Competition (http://www.shl-dataset.org/activity-recognition-challenge-2020/) as part of a special session.

Beyond Steps: Challenges And Opportunities In Fitness Tracking

https://beyondsteps2020.github.io

ORGANIZERS

Rushil Khurana (CMU, USA), Abdelkareem Bedri (CMU, USA), Patrick Carrington (CMU, USA), Daniel A. Epstein (UC Irvine, USA), Rúben Gouveia (University of Twente, The Netherlands), Jochen Meyer (OFFIS Institute for Information Technology, Germany), Julian Ramos (CMU, USA), Jason Wiese (University of Utah, USA), Paweł Woźniak (Utrecht University, The Netherlands)

WORKSHOP SUMMARY

The quantified-self is a positive and prevalent aspect of our culture that has progressed during the last decade propelled by technological advances in health and fitness tracking. Prior research has shown that self tracking has a myriad of benefits. And we have the ability to sense and track various aspects of fitness and well-being. However one key challenge that remains is what data needs to be shown to the user, and how to present it to the user. Moreover, when is the right time to deliver key information to the user. Secondly, we have noticed that self-monitoring and tracking research has mostly evolved in isolation i.e., researchers have separately studied or built systems for various aspects of fitness like exercise tracking, diet or sleep monitoring. While in reality many of these areas are intertwined and depend on each other: Poor sleep can lead to overeating and consequently weight gain.

In this workshop, we propose to highlight and address these two challenges and explore opportunities to expand beyond the current paradigm of single health factors tracking to a more comprehensive fitness tracking.

UbiTtention 2020: 5th International Workshop On Smart & Ambient Notification And Attention Management

https://www.ubittention.org/2020

ORGANIZERS

Anja Exler (Karlsruhe Institute of Technology (KIT), Germany), Alexandra Voit (Adesso AG, Germany), Martin Gjoreski (Jozef Stefan Institute, Slovenia), Tine Kolenik (Jozef Stefan Institute, Slovenia), Niels van Berkel (Aalborg University, Denmark), Tadashi Okoshi (Keio University, Japan), Veljko Pejovic (University of Ljubljana, Slovenia)

WORKSHOP SUMMARY

In the advancing ubiquitous computing, users are increasingly confronted with a tremendous amount of information proactively provided via notifications from versatile applications and services, through multiple devices and screens in their environment. Thus, human’s attention has been getting a new significant bottleneck. Further, the latest computing trends with emerging new devices including versatile IoT devices, and contexts, such as smart cities, attention representation, sensing, prediction, analysis and adaptive behavior in the computer systems, are needed in our computing systems.

Following the successful UbiTtention 2016 to 2019 workshops, the UbiTtention 2020 workshop brings together researchers and practitioners from academia and industry to explore the management of human attention and smart and ambient notifications with versatile devices and situations to overcome information overload and overchoice. In this workshop, we want to focus on a larger understanding of the different roles notifications can play in a wide variety of computing environments including the office, the home, in cars, and other smart environments. In addition, we introduce an open-data machine learning challenge to advance the field of cognitive load inference in ubiquitous computing. The dataset is the first labelled dataset for cognitive load monitoring with a wristband and it will be fully released after the challenge.

5th International Workshop On Mental Health And Well-Being: Sensing And Intervention

https://ubicomp-mental-health.github.io

ORGANIZERS

Varun Mishra (Dartmouth College, USA), Akane Sano (Rice University, USA), Saeed Abdullah (Penn State, USA), Jakob E. Bardram (TU Denmark, Denmark), Sandra Servia (University of Cambridge, UK), Elizabeth L. Murnane (Stanford University, USA), Tanzeem Choudhury (Cornell University, USA), Mirco Musolesi (UC London, UK), Giovanna Nunes Vilaza (DTU, Denmark), Rajalakshmi Nandakumar (Cornell Tech, USA), Tauhidur Rahman (UMass Amherst, USA)

WORKSHOP SUMMARY

Mental health issues affect a significant portion of the world’s population and can result in debilitating and life-threatening outcomes. To address this increasingly pressing healthcare challenge, there is a need to research novel approaches for early detection and prevention. Toward this, ubiquitous systems can play a central role in revealing and tracking clinically relevant behaviors, contexts, and symptoms. Further, such systems can passively detect relapse onset and enable the opportune delivery of effective intervention strategies.

However, despite their clear potential, the uptake of ubiquitous technologies into clinical mental healthcare is rare, and a number of challenges still face the overall efficacy of such technology-based solutions. The goal of this workshop is to bring together researchers interested in identifying, articulating, and addressing such issues and opportunities. Following the success this workshop in the last four years, we aim to continue facilitating the UbiComp community in developing novel approaches for sensing and intervention in the context of mental health.

AppLens 2020: 3rd International Workshop On Mining And Learning From Smartphone Apps

http://www.shazhao.net/applens2020/

ORGANIZERS

Sha Zhao (Zhejiang University, China), Yong Li (Tsinghua University, China), Sasu Tarkoma (University of Helsinki, Finland), Zhiwen Yu (Northwestern Polytechnical University, China), Anind Dey (University of Washington, USA), and Gang Pan (Zhejiang University, China)

WORKSHOP SUMMARY

Smartphone apps are becoming ubiquitous in our everyday life. Apps on smartphones sense users’ behaviors and activities, providing a lens for understanding users, which is an important point in the community of ubiquitous computing.

The 3rd International workshop AppLens 2020 at UbiComp/iSWC 2020 will fosters discussions covering methodologies and tools, theories and models, design, descriptions or analysis of smartphone app data. We seek participants interested in profiling users from their use of smartphone apps, discovering cultural and social phenomenon by analyzing app usage, modeling app usage behaviors, studying smartphone apps, user privacy issues, etc.

In order to attract more participants, we will open two app datasets consisting of app usage records. This workshop will include paper sessions, invited talks, a panel session, and Best Paper Award, to provide a forum for the participants to communicate and discuss issues to promote the emerging research field. Moreover, we will select a few accepted papers to be extended and published in a prestigious journal special issue.

AppLens 2020: 3rd International Workshop On Mining And Learning From Smartphone Apps

http://www.shazhao.net/applens2020/

ORGANIZERS

Sha Zhao (Zhejiang University, China), Yong Li (Tsinghua University, China), Sasu Tarkoma (University of Helsinki, Finland), Zhiwen Yu (Northwestern Polytechnical University, China), Anind Dey (University of Washington, USA), and Gang Pan (Zhejiang University, China)

WORKSHOP SUMMARY

Smartphone apps are becoming ubiquitous in our everyday life. Apps on smartphones sense users’ behaviors and activities, providing a lens for understanding users, which is an important point in the community of ubiquitous computing.

The 3rd International workshop AppLens 2020 at UbiComp/iSWC 2020 will fosters discussions covering methodologies and tools, theories and models, design, descriptions or analysis of smartphone app data. We seek participants interested in profiling users from their use of smartphone apps, discovering cultural and social phenomenon by analyzing app usage, modeling app usage behaviors, studying smartphone apps, user privacy issues, etc.

In order to attract more participants, we will open two app datasets consisting of app usage records. This workshop will include paper sessions, invited talks, a panel session, and Best Paper Award, to provide a forum for the participants to communicate and discuss issues to promote the emerging research field. Moreover, we will select a few accepted papers to be extended and published in a prestigious journal special issue.

AppLens 2020: 3rd International Workshop On Mining And Learning From Smartphone Apps

http://www.shazhao.net/applens2020/

ORGANIZERS

Sha Zhao (Zhejiang University, China), Yong Li (Tsinghua University, China), Sasu Tarkoma (University of Helsinki, Finland), Zhiwen Yu (Northwestern Polytechnical University, China), Anind Dey (University of Washington, USA), and Gang Pan (Zhejiang University, China)

WORKSHOP SUMMARY

Smartphone apps are becoming ubiquitous in our everyday life. Apps on smartphones sense users’ behaviors and activities, providing a lens for understanding users, which is an important point in the community of ubiquitous computing.

The 3rd International workshop AppLens 2020 at UbiComp/iSWC 2020 will fosters discussions covering methodologies and tools, theories and models, design, descriptions or analysis of smartphone app data. We seek participants interested in profiling users from their use of smartphone apps, discovering cultural and social phenomenon by analyzing app usage, modeling app usage behaviors, studying smartphone apps, user privacy issues, etc.

In order to attract more participants, we will open two app datasets consisting of app usage records. This workshop will include paper sessions, invited talks, a panel session, and Best Paper Award, to provide a forum for the participants to communicate and discuss issues to promote the emerging research field. Moreover, we will select a few accepted papers to be extended and published in a prestigious journal special issue.

CML-IOT 2020: 2nd Workshop On Continual And Multimodal Learning For Internet Of Things

https://cmliot2020.github.io

ORGANIZERS

Susu Xu (Qualcomm AI Research, USA), Tong Yu (Samsung Research America, USA), Shijia Pan (UC Merced, USA)

WORKSHOP SUMMARY

With the deployment of the Internet of Things (IoT), a large number of sensors are connected to the Internet, providing large-amount, streaming, and multimodal data. These data have distinct statistical characteristics over time and sensing modalities, which are hardly captured by traditional learning methods. Continual and multimodal learning allows integration, adaptation, and generalization of the knowledge learned from experiential data collected from distributed and heterogeneous IoT devices to new situations. Therefore, continual and multimodal learning is an important step to enable efficient ubiquitous computing on IoT devices.

We aim at bringing together researchers from different areas to establish a multidisciplinary community and share the latest research in continual learning and multimodal learning for various IoT applications.

WellComp 2020: 3rd International Workshop On Computing For Well-Being

http://wellcomp.org/2020/

ORGANIZERS

Tadashi Okoshi (Keio University, Japan), Jin Nakazawa (Keio University, Japan), JeongGil Ko (Yonsei University, Republic of Korea), Fahim Kawsar (Nokia Bell Labs, UK), Susanna Pirttikangas (University of Oulu, Finland)

WORKSHOP SUMMARY

We have been experiencing that much of the influence from ubicomp technologies are both contributing to a better quality of life (QoL) of our individual and organizational lives, and causing new types of stress and pain at the same time. The term “well-being” has recently gained attention as a term that covers our general happiness and even more concrete good conditions in our lives, such as physical, psychological, and social wellness. Active research in various ubicomp research areas (systems, mobile/wearable sensing, persuasive apps, different viewpoints and layers of computing.

After two consecutive successful workshops in 2019 and 2020, WellComp2020 will share the latest research in such various areas related to users’ physical, mental, and social well-being. Especially this year’s special attention will be paid for “Well-Being Metrics” and “Well-Being Intervention towards behavior change”.