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Sonia Baee
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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
622021
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
55*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
442012
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
252021
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
212020
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
172019
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
62019
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
62018
Web-based interpretation bias training to reduce anxiety: A sequential multiple-assignment randomized trial
JW Eberle, KE Daniel, S Baee, HC Behan, AL Silverman, ...
52024
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
52020
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
22022
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
12022
LonelyText: A Short Messaging Based Classification of Loneliness
MK Ameko, S Baee, LE Barnes
arXiv preprint arXiv:2101.09138, 2021
12021
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
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