Deeptake: Prediction of driver takeover behavior using multimodal data E Pakdamanian, S Sheng, S Baee, S Heo, S Kraus, L Feng Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems …, 2021 | 60 | 2021 |
Medirl: Predicting the visual attention of drivers via maximum entropy deep inverse reinforcement learning S Baee, E Pakdamanian, I Kim, L Feng, V Ordonez, L Barnes Proceedings of the IEEE/CVF international conference on computer vision …, 2021 | 54* | 2021 |
Passenger boarding/alighting management in urban rail transportation S Baee, F Eshghi, SM Hashemi, R Moienfar ASME/IEEE Joint Rail Conference 44656, 823-829, 2012 | 43 | 2012 |
Multi-session online interpretation bias training for anxiety in a community sample JL Ji, S Baee, D Zhang, CP Calicho-Mamani, MJ Meyer, D Funk, ... Behaviour research and therapy 142, 103864, 2021 | 23 | 2021 |
A framework for understanding the relationship between social media discourse and mental health S Mendu, A Baglione, S Baee, C Wu, B Ng, A Shaked, G Clore, ... Proceedings of the ACM on Human-Computer Interaction 4 (CSCW2), 1-23, 2020 | 20 | 2020 |
Do I really feel better? Effectiveness of emotion regulation strategies depends on the measure and social anxiety KE Daniel, S Baee, M Boukhechba, LE Barnes, BA Teachman Depression and Anxiety 36 (12), 1182-1190, 2019 | 16 | 2019 |
SocialText: A framework for understanding the relationship between digital communication patterns and mental health S Mendu, M Boukhechba, A Baglione, S Baee, C Wu, L Barnes 2019 IEEE 13th international conference on semantic computing (ICSC), 428-433, 2019 | 6 | 2019 |
A social cognitive theory-based framework for monitoring medication adherence applied to endocrine therapy in breast cancer survivors M Boukhechba, S Baee, AL Nobles, J Gong, K Wells, LE Barnes 2018 IEEE EMBS International Conference on Biomedical & Health Informatics …, 2018 | 6 | 2018 |
Web-based interpretation bias training to reduce anxiety: A sequential multiple-assignment randomized trial JW Eberle, KE Daniel, S Baee, HC Behan, AL Silverman, ... | 5 | 2024 |
A Framework for Addressing the Risks and Opportunities In AI-Supported Virtual Health Coaches S Baee, M Rucker, A Baglione, A Mawulolo K., L Barnes 14th EAI International Conference on Pervasive Computing Technologies for …, 2020 | 5 | 2020 |
Use of a mobile health intervention by older versus younger people with HIV: analysis of usage, social support, and network interactions TE Flickinger, BR Campbell, A Timm, S Baee, D Datta, SV Shenoi, ... Telemedicine Reports 3 (1), 191-200, 2022 | 2 | 2022 |
Dara: Development of a chatbot support system for an anxiety reduction digital intervention RX Schwartz, A Ramanan, D Patel, A Lynch, S Baee, L Barnes 2022 Systems and Information Engineering Design Symposium (SIEDS), 139-144, 2022 | 1 | 2022 |
LonelyText: A Short Messaging Based Classification of Loneliness MK Ameko, S Baee, LE Barnes arXiv preprint arXiv:2101.09138, 2021 | 1 | 2021 |
Behavioral Engagement and Psychosocial Outcomes in Web-Based Interpretation Bias Training for Anxiety AFV de la Garza Evia, JW Eberle, S Baee, EC Wolfe, M Boukhechba, ... | | 2024 |
1.2. 1 Considering human/machine interactions E Pakdamanian, S Sheng, S Baee, S Heo, S Kraus, L Feng | | 2021 |
Redesigning the Quantified Self Ecosystem with Mental Health in Mind S Mendu, S Baee, A Baglione, L Barnes CHI 2020 Workshop on Technology Ecosystems: Rethinking Resources for Mental …, 2020 | | 2020 |
What is effective? Assessing different aspects of emotion regulation effectiveness in daily life. KE Daniel, S Baee, L Barnes, B Teachman The Association for Psychological Science Annual Convention, Washington, D.C., 2019 | | 2019 |
Ecological Momentary Assessment of Differential Impact of Emotion Regulation Strategies on Negative Affect Based on Social Anxiety Severity. KE Daniel, S Baee, L Barnes, B Teachman 52nd Annual Association for Behavioral and Cognitive Therapies Convention …, 2018 | | 2018 |
Behavioral Engagement and Psychosocial Outcomes in Web-Based Interpretation Bias Training for Anxiety AFV de la Garza, JW Eberle, S Baee, E Wolfe, M Boukhechba, D Funk, ... OSF, 0 | | |
MEDIRL: Predicting the Visual Attention of Drivers via Maximum Entropy Deep Inverse Reinforcement Learning (Supplementary Material) S Baee, E Pakdamanian, I Kim, L Feng, V Ordonez, L Barnes | | |