SCSS wins best paper award at the ACM CHI Conference2019 May 8
Four papers from the School were presented at the ACM CHI Conference on Human Factors in Computing Systems this week. CHI is generally regarded as the most prestigious venue for Human-Computer Interaction Research.
A paper by Kevin Doherty, Gavin Doherty and collaborators in Imperial College London and Microsoft Research has not only received a best paper award (top 1% of 2960 paper submissions), but also an award for overall best paper at the conference, sponsored by the ACM Europe Council.
The award acknowledges groundbreaking research for its importance and contribution to the area and to highlight theoretical and practical innovations that are likely to shape the future of computing both in Europe and worldwide. This paper presents the results of the first feasibility study to examine the potential of mobile devices to engage women in antenatal (pre-birth) mental health screenings, given that it is estimated that at least 50 percent of perinatal (the period immediately before and after birth) depression (PND) cases go undiagnosed.
Two papers with SCSS authors have also received honorable mention awards (top 5% of submissions), including a paper in collaboration with UCD, UCC, Toronto and Voysis, with SCSS Adapt Centre authors; Vincent Wade, Emer Gilmartin and Brendan Spillane "What Makes a GoodConversation? Challenges in Designing Truly Conversational Agents”. The authors aim to understand what people value in conversation and how this should manifest in agents.
A second honorable mention award was given to a paper with SCSS authors Camille Nadal and Gavin Doherty, with collaborators in Lancaster and KTH. “HCI and Affective Health: Taking stock of a decade of studies and charting future research directions” presents the results of a systematic literature review of recent research addressing technology in mental health.
A further accepted paper by Chengcheng Qu, Corina Sas (Lancaster) and Gavin Doherty “Exploring and Designing for Memory Impairments in Depression” explores limitations of existing memory technologies and identifies factors to consider when designing new technologies to help people with depression.
Posted by: Catherine O'Connor, Head of External Relations, School of Computer Science and Statistics, Trinity College Dublin.
catherine.oconnor at tcd.ie