Tahsin’s research interest lies in the confluence of artificial intelligence and human mental health analysis and prediction. His research looks into the role of passive mobile and fitness sensors in developing the MoodRing application for detecting and predicting changes in adolescent depression. The aim of the project is to enable patients, caregivers, and parents with early intervention alerts to prevent the worsening of symptoms. This project is a reflection of the lab’s goals to promote health and well being through intelligent learning of patterns and trends.

Tahsin graduated with his PhD in Systems Engineering in Summer 2024.

Projects

Mood Ring Detecting Changes in Adolescent Depression

depression anxiety affective-forecasting

Past Projects

Publications

2024

Framework for Ranking Machine Learning Predictions of Limited, Multimodal, and Longitudinal Behavioral Passive Sensing Data: Combining User-Agnostic and Personalized Modeling

Tahsin Mullick, Sam Shaaban, Ana Radovic, Afsaneh Doryab

JMIR AI  ·  20 May 2024  ·  doi:10.2196/47805

mood-ring

2022

Predicting Depression in Adolescents Using Mobile and Wearable Sensors: Multimodal Machine Learning–Based Exploratory Study

Tahsin Mullick, Ana Radovic, Sam Shaaban, Afsaneh Doryab

JMIR Formative Research  ·  24 Jun 2022  ·  doi:10.2196/35807

mood-ring

2021

An Automated Machine Learning Pipeline for Monitoring and Forecasting Mobile Health Data

Anna Bonaquist, Meredith Grehan, Owen Haines, Joseph Keogh, Tahsin Mullick, Neil Singh, Sam Shaaban, Ana Radovic, Afsaneh Doryab

2021 Systems and Information Engineering Design Symposium (SIEDS)  ·  30 Apr 2021  ·  doi:10.1109/SIEDS52267.2021.9483755

mood-ring

News