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Soujanya Chatterjee, Ph.D.
Amazon AI
Soujanya Chatterjee, Ph.D., is an Applied Scientist II at Amazon, specifically working within the Halo Health Technology Team, which is part of Amazon Devices and Machine Learning. She earned her Ph.D. in Computer Science from the University of Memphis in 2021.12
Her role at Amazon involves applying her expertise in machine learning and data science to develop technologies that enhance health monitoring and related applications. Chatterjee's academic background and professional experience position her as a significant contributor to advancements in health technology at Amazon.13
Highlights
Majority of chronic diseases can be prevented or better managed by improving health-related behaviors. Over the years, several works on passive detection of digital health biomarkers (using wearable and mobile sensors) have created new opportunities to improve the effectiveness of behavioral interventions. However, a key goal has been to be able to find opportune moments for delivering interventions by passively detecting the rising risk of an imminent adverse behavior.
In our recently published UbiComp paper, we outline the major challenges, propose new methods, and a loss function for developing deep learning models to continuously estimate the risk of an impending smoking lapse (an adverse behavior) in newly abstinent smokers in their natural environment. We do so using multi-modal signals including the users' internal states, personal behaviors, and environmental contexts. We hope that this work opens the door for exciting new opportunities in the design and delivery of efficacious behavioral interventions to help people live healthier lives.
Accolades and gratitude to the entire team, including the lead author Md Azim Ullah and my doctoral advisor for working so hard and for so long to make this idea successful.
Paper Link: https://lnkd.in/gwQNxA7u
#acmubicomp #imwut #mhealth #healthai #behavioralinterventions #smokingcessation
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