Rahul Islam
Hello,
I'm Rahul
I'm a Ph.D candidate in the School of Systems and Enterprises at Stevens Institute of Technology, advised by Dr. Sang Won Bae. My research goals focuses on applying my knowledge in applied machine learning, and affective computing to solve problems in various domains, including ubiquitous computing, mental health sensing and interaction techniques.
Before commencing my Ph.D, I graduated with a Bachelors in Technology from IIIT Guwahati, with a major in Computer Science Engineering. As an undergraduate, I worked on multiple research projects under the guidance of Dr. Ferdous Ahmed Barbhuiya, and Dr. Kuntal Dey, among others.
Research
J = Journal / C = Conference / W = Workshop / Po = Poster / A = arXiv
[C.3] MotionTrace: IMU-based Field of View Prediction for Smartphone AR Interactions
Rahul Islam, Vasco Miguel Liang Xu, Karan Ahuja
IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks (BSN 2024)
[C.2] MoodPupilar: Predicting Mood Through Smartphone Detected Pupillary Responses in Naturalistic Settings
Rahul Islam, Tongze Zhang, Priyanshu Singh Bisen, Sang Won Bae
IEEE-EMBS International Conference on Wearable and Implantable Body Sensor Networks (BSN 2024)
[J.6] FacePsy: An Open-Source Affective Mobile Sensing System - Analyzing Facial Behavior and Head Gesture for Depression Detection in Naturalistic Settings
Rahul Islam, Sang Won Bae
Proceedings of the ACM on Human-Computer Interaction (MobileHCI '24)
[Po.4] Moving Toward Personalized Behavioral Medicine: Integrating Smartphone-based GPS Data into a Digital Alcohol Intervention
Tammy Chung, Sang Won Bae, Tongze Zhang, Melik Ozolcer, Rahul Islam, Anind Dey, Yiyi Ren, Brian Suffoletto, Aidan GC Wright, Trishnee Bhurosy
Society of Behavioral Medicine/Annals of Behavioral Medicine 2024
[J.5] Towards Automated, Interpretable and Unobtrusive Detection of Acute Marijuana Intoxication in the Natural Environment: Harnessing Smartphones, Wearables, Machine Learning and Explainable AI to Empower Clinical Decision Support for Just-In-Time Adaptive Interventions
Sang Won Bae, Tammy Chung, Tongze Zhang, Melik Ozolcer, Anind K Dey, Rahul Islam
JMIR AI 2023 (Under Revision)
[J.4] Leveraging Mobile Phone Sensors, Machine Learning, and Explainable Artificial Intelligence to Predict Imminent Same-Day Binge-drinking Events to Support Just-in-time Adaptive Interventions: Algorithm Development and Validation Study
Sang Won Bae, Brian Suffoletto, Tongze Zhang, Tammy Chung, Melik Ozolcer, Rahul Islam, Anind K Dey
JMIR Formative Research 2023
Professional Experience
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Senior Software Architect, Egnify, 2019 (India)
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Data Scientist, ParallelDots, 2017 (India)
Reviewing
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ACM IMWUT '22, '23, '24
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ACM CHI '24
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ACM UIST '24
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Elsevier CVIU '17
Teaching
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2024 Stevens, Decision Making Via Data Analysis Techniques, Guest Lecture
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2024 Stevens, Data-Mining and Applied Machine Learning, TA
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2023 Stevens, Informatics for Engineering Management, Guest Lecture
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2023 Stevens, Fundamentals of Software Engineering, TA