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Hello,

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I'm Rahul

I'm a Ph.D candidate in the School of Engineering & Science 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.

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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.

  • Google Scholar
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  • GitHub

Research

J = Journal / C = Conference / W = Workshop / Po = Poster / A = arXiv

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[C.5] MoodCam: Mood Prediction Through Smartphone-Based Facial Affect Analysis in Real-World Settings (To appear)

Rahul Islam, Tongze Zhang, Sang Won Bae

IEEE International Conference on Ubiquitous Intelligence and Computing (UIC 2024)

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[C.4] MotionTrace: IMU-based Trajectory 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)

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[C.3] 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)

FacePsy

[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)

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[C.2] PupilSense: Detection of Depressive Episodes Through Pupillary Response in the Wild

Rahul Islam, Sang Won Bae

Activity and Behavior Computing 2024

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[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

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[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)

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[W.1] Revolutionizing Mental Health Support: An Innovative Affective Mobile Framework for Dynamic, Proactive, and Context-Adaptive Conversational Agents

Rahul Islam, Sang Won Bae

ACM IMWUT/Ubicomp 2023, GenAI4PC Symposium

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[Po.3] Towards Designing Empathetic and Trustworthy AI Chatbots: an Exploratory Study

Melik Ozolcer, Rahul Islam, Abdullah Mohammed, Tongze Zhang, Sang Won Bae, Ting Liao

CESUN 2023

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[Po.2] MicroFlow: Advancing Affective States Detection in Learning Through Micro-Expressions

Rahul Islam, Sang Won Bae

CESUN 2023

[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

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[J.3] Mobile phone sensor-based detection of subjective cannabis intoxication in young adults: A feasibility study in real-world settings

Sang Won Bae, Tammy Chung, Rahul Islam, Brian Suffoletto, Jiameng Du, Serim Jang, Yuuki Nishiyama, Raghu Mulukutla, Anind K Dey

Drug and Alcohol Dependence 2021

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[J.2] EyeSpyVR: Interactive Eye Sensing Using Off-the-Shelf, Smartphone-Based VR Headsets

Karan Ahuja, Rahul Islam, Varun Parashar, Kuntal Dey, Chris Harrison, Mayank Goel

ACM IMWUT/Ubicomp 2018

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[J.1] Convolutional neural networks for ocular smartphone-based biometrics

Karan Ahuja, Rahul Islam, Ferdous Barbhuiya, Kuntal Dey

Pattern Recognition Letters, Volume 91. 2017

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[Po.1] EyamKayo: Interactive Gaze and Facial Expression Captcha

Utkarsh Dwivedi,Karan Ahuja, Rahul Islam, Ferdous Barbhuiya, Seema Nagar, Kuntal Dey

ACM IUI 2017

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[C.1] A Preliminary Study of CNNs for Iris and Periocular Verification in the View Spectrum

Karan Ahuja, Rahul Islam, Ferdous Barbhuiya, Kuntal Dey

ICPR 2016

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[A.1] SenTion: A framework for Sensing Facial Expressions

Rahul Islam, Karan Ahuja, Sandip Karmakar, Ferdous Barbhuiya

arXiv preprint arXiv:1608.04489

Using Mobile Phones

Selected Media Coverage

WIRED. Depression can be detected simply by looking at a smartphone; new technology reveals its hidden potential

Neuroscience News. AI Detects Depression Through Eyes and Facial Cues

Modern Optometry. Cataract Patients Looking to Avoid Surgery? - Significant Findings

Medical Xpress. AI-powered apps show potential for detecting depression through eye snapshots

News Medical. Smartphone-based AI systems track subtle facial, pupil signals to identify depression

Science Daily. When detecting depression, the eyes have it 

Hindustan Times. You smile more when you're depressed: Pilot AI-powered apps can detect depression early ...

StudyFinds.org. Sad eyes are real — Apps may soon recognize depression in your face

New Scientist. AI can detect if you have recently smoked cannabis

Forbes. Your Smartphone Can Tell If You’re High On Marijuana, Study Finds

Stripes

Professional Experience

  • Senior Software Architect, Egnify, 2019 (India)

  • Data Scientist, ParallelDots, 2017 (India)

Reviewing

  • ACM IMWUT '22, '23, '24

  • ACM CHI '24, '25

  • ACM UIST '24

  • Elsevier CVIU '17

Teaching

  • 2024 Stevens, Decision Making Via Data Analysis Techniques, Guest Lecture

  • 2024 Stevens, Data-Mining and Applied Machine Learning, TA

  • 2023 Stevens, Informatics for Engineering Management, Guest Lecture

  • 2023 Stevens, Fundamentals of Software Engineering, TA

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