Leading the digital health revolution

Our research leverages the latest technologies to create novel methodologies and bring together interdisciplinary expertise.

Cutting Edge Research

Connected Technology

We are working towards a more connected health care system by leveraging patient-generated health data and building digital applications utilizing remote sensors and wearable technologies.

Health IT Systems Engineering

We are building state-of-the-art computational frameworks and architectures to enable rapid scientific discovery alongside translational applications into real-world clinical settings.

Multimodal Data

By creating an innovative environment to access electronic health records, imaging, -omics, and sensor data, we will advance healthcare-driven Artificial Intelligence (AI)-based solutions.

Machine Learning and Artificial Intelligence

We are advancing data science methodologies in medicine with insights that benefit patients and healthcare providers through better clinical prediction and early warning systems.

Core Research Projects

Leveraging expertise in computer science and engineering, we've built a platform where researchers can access the vast datasets held at Mount Sinai for data science and machine learning endeavors.
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Ehive, created by the Digital Discovery Program, is comprehensive digital health research platform of patient-centric health studies using wearable, mobile and sensor technologies to better understand complex diseases.
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The Warrior Watch platform will help predict asymptomatic or pre-symptomatic COVID-19 infections as well as how the pandemic is impacting the stress and resilience of our workforce, here at Mount Sinai
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Co-Innovation Research Exchange
The HPI・MS research exchange is a co-mentorship program supported by research faculty at the Hasso Plattner Institute and the Icahn School of Medicine at Mount Sinai, wherein trainees lead innovative projects that leverage the unique clinical data resources of Mount Sinai with the applied digital engineering training of HPI in order to improve clinical computational understanding.
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Our Labs

Thomas Fuchs Lab

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Ipek Ensari Lab

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