By Ms Nan Gao

Preprints

Gao N; Ananthan S; Yu C; Wang Y; Salim FD, 2023, Critiquing Self-report Practices for Human Mental and Wellbeing Computing at Ubicomp, , http://arxiv.org/abs/2311.15496v1

Gao N; Yu Z; Yu C; Wang Y; Salim FD; Shi Y, 2023, Automated Mobile Sensing Strategies Generation for Human Behaviour Understanding, , http://arxiv.org/abs/2311.05457v1

Gao N; Nolan S; Ji K; Rumi SK; Heinisch JS; Anderson C; David K; Salim FD, 2023, "Living Within Four Walls": Exploring Emotional and Social Dynamics in Mobile Usage During Home Confinement, , http://arxiv.org/abs/2310.13304v2

Heinisch JS; Gao N; Anderson C; Deldari S; David K; Salim F, 2022, Investigating the Effects of Mood & Usage Behaviour on Notification Response Time, , http://arxiv.org/abs/2207.03405v1

Gao N; Rahaman MS; Shao W; Ji K; Salim FD, 2021, Individual and Group-wise Classroom Seating Experience: Effects on Student Engagement in Different Courses, , http://dx.doi.org/10.1145/3550335

Li D; Wang S; He Q; Yang Y, 2021, Cost-effective Land Cover Classification for Remote Sensing Images, , http://arxiv.org/abs/2107.12016v2

Gao N; Rahaman MS; Shao W; Salim FD, 2021, Investigating the Reliability of Self-report Data in the Wild: The Quest for Ground Truth, , http://arxiv.org/abs/2107.00389v2

Gao N; Marschall M; Burry J; Watkins S; Salim FD, 2021, Understanding occupants' behaviour, engagement, emotion, and comfort indoors with heterogeneous sensors and wearables, , http://arxiv.org/abs/2105.06637v3

Gao N; Xue H; Shao W; Zhao S; Qin KK; Prabowo A; Rahaman MS; Salim FD, 2020, Generative Adversarial Networks for Spatio-temporal Data: A Survey, , http://dx.doi.org/10.1145/3474838

Gao N; Shao W; Rahaman MS; Salim FD, 2020, n-Gage: Predicting in-class Emotional, Behavioural and Cognitive Engagement in the Wild, , http://arxiv.org/abs/2007.04831v4

Gao N; Shao W; Rahaman MS; Zhai J; David K; Salim FD, 2020, Transfer Learning for Thermal Comfort Prediction in Multiple Cities, , http://arxiv.org/abs/2004.14382v3

Li D; Wang S; Gao N; He Q; Yang Y, 2019, Cutting the Unnecessary Long Tail: Cost-Effective Big Data Clustering in the Cloud, , http://arxiv.org/abs/1909.10000v1

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