Sang Won Bae
- Other (2017) Carnegie Mellon University (Human-Computer Interaction/Computer Science)
- PhD (2013) Yonsei University (Human-Computer Interaction/Cognitive Science and Engineering)
Predicting Human Behaviors to Enhance Quality of Healthcare Service and to Save Costs: Predicting Hospital Readmissions for Cancer Patients (UbiComp, 16) and Estimation of Symptom Severity During Chemotherapy (JMIR, 17)
Sensing Risky Behaviors (UbiComp, 17; Addictive Behavior, 18) and Developing Detection Algorithms Using Smartphone-based Sensors and Experience Sampling Methods (ESM) in the Wild
Developing Human-Centered AI Systems of Interventions for Human Behavior Changes
Sang Won (Grace) Bae is an assistant professor at the School of Systems and Enterprises. She joined SSE from Carnegie Mellon University, where she was a systems scientist in Human-Computer Interaction Institute at the School of Computer Science. Dr. Bae's research interests are focused on using passive sensing data from smartphones and wearable devices to develop predictive models of human behavior that could reduce health care costs. She has received grants and awards from several foundations, including the R21 grant from the National Institutes of Health.
2017-2019 Systems Scientist, Special Faculty, Human-Computer Interaction Institute, School of Computer Science, Carnegie Mellon University
2014-2017 Postdoctoral Associate, Human-Computer Interaction Institute, School of Computer Science, Carnegie Mellon University
2013-2014 Visiting Scholar, Human-Computer Interaction Institute, School of Computer Science, Carnegie Mellon University
2010-2013 Research Scientist, Yonsei Center for Cognitive Science
2005-2008 UX Designer/Manager/Leader, Asia Pacific Mobile Phone Group, Wireless Product Division, Samsung Electronics
2000-2005 UX Designer/Programmer/Data analyst, SK Corp.
- Women@SSE Chair
- The University Graduate Curriculum Committee Member
- The ACM CHI Conference on Human Factors in Computing Systems Associate Chair (AC) for CHI 2023 ‘Health’ Subcommittee
2019.8-current Assistant Professor, Director, Human-Centered Interaction Lab, School of Systems and Enterprises, Stevens Institute of Technology, Hoboken, NJ
2018-2020 Small Business Innovation Research (SBIR) grant, National Institute on Drug Abuse (NIDA)
2018 IBM Watson AI XPRIZE Round III, Selected 10 Milestone Nominees
Best Research Award, Human-Centered AI System, Google Tri-State ExploreCSR Research, 2021
Best Paper Selected for the 2019 Edition of the IMIA Yearbook, Section Cancer Informatics, 2019
IBM Watson AI XPRIZE Round III, AI Healthcare System, Selected 10 Milestone Nominees, 2018
LATTICE Symposium Selected Top 30 Pre-tenure Track Women Scientists in EECS, USA, 2017
- ACM – Association for Computing Machinery Member
National Institute on Drug Abuse (NIDA) R43 Grant, Small Business Innovation Research (SBIR), 2018
National Science Foundation (NSF), Innovation Corps (I-Corp) Site @Carnegie Mellon University Team, 2018
National Institutes of Health (NIH) R21 Grant, 2017
Apparatus and Method for Supporting Multimedia Service in Mobile Terminal
Bae S, Suffoletto B, Mun E.-Y, Dey A, Ren Y, Chung T (June 28, 2022) Identifying Links between Drinking Behavior and Travel Pattern to Inform Personalized Digital Alcohol Intervention, Alcoholism-Clinical and Experimental Research, WILEY. 46 51A
Korshakova E, Bae S. (May 2022). Exploring Students' Flow States Using Facial Behavior Markers in an Online At-Home Learning Environment, Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, Human-Centered Perspectives in Explainable AI, ACM
Roper S, Bae S. (May 2022). Exploring Students' Flow States Using Facial Behavior Markers in an Online At-Home Learning Environment, Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, the Future of Emotion in Human-Computer Interaction, ACM
Demaliaj A, Bae S. (April 23, 2022). Designing Human-Centered AI Systems, Detecting Emotion and Flow in College Students During the Online Courses, Google Research 2021, Best Research Award
Bae S, Chung T, Islam R, Suffoletto B, Du J, Jang S, Nishiyama Y, Jang S, Mulukutla R, Dey A (Sept 3, 2021). "Mobile Phone Sensor-Based Detection of Subjective Cannabis Intoxication in Young Adults: A Feasibility Study in Real-World Settings", Drug and Alcohol Dependence, Elsevier.
Chung T, Bae S, Mun E, Suffoletto B, Nishiyama Y, Jang S, Dey A. (Mar 10, 2020). "Mobile Assessment of Acute Effects of Marijuana on Cognitive Functioning in Young Adults: Observational Study", JMIR mHealth and uHealth, JMIR Publications Inc. 8 (3)
Bae S, Chung T, Ferreira D, Dey AK, Suffoletto B. (Aug 1, 2018). "Mobile Phone Sensors and Supervised Machine Learning to Identify Alcohol Use Events in Young Adults: Implications for Just-In-Time Adaptive Interventions", Rachel L. Tomko, Erin A. McClure, Addictive behaviors, Elsevier. 83 42-47.
Bae S, Ferreira D, Suffoletto B, Puyana J, Kurtz R, Chung T, Dey A. (Jun 30, 2017). "Detecting Drinking Episodes in Young Adults Using Smartphone-based Sensors", Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, ACM. 1 (2), 1-36.
CA Low, AK Dey, D Ferreira, T Kamarck, W Sun, S Bae, A Doryab. (Dec 19, 2017). "Estimation of Symptom Severity During Chemotherapy From Passively Sensed Data: Exploratory Study", G Eysenbach, Journal of Medical Internet Research., JMIR Publications Inc. 19 (12)
Bae S, Dey A, Low C. (Sep 12, 2016). "Using Passively Collected Sedentary Behavior to Predict Hospital Readmission", Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing. ACM. 616-621.
ISE490: Data Mining and Applied Machine Learning
SYS 515: Systems Engineering Applications to Healthcare
EM 224: Informatics and Software Development
EM 622: Decision Making via Data Analysis Techniques
EM 680: Designing and Managing the Development Enterprise
SYS 800: Special Problems in Systems Engineering