Shaping the future of digital health

We are a global research institute rapidly developing digital health solutions that empower patients and healthcare providers.

A collaboration between

About Us

Turning the promise of digital health into a reality

Science has helped humanity to improve and extend life. Today, technological advances have allowed us to understand and analyze information in ways never before possible.


The Hasso Plattner Institute for Digital Health at Mount Sinai (HPI・MS) propels these possibilities through an extraordinary international academic collaboration between the Hasso Plattner Institute for Digital Engineering in Potsdam, Germany, and the Mount Sinai Health System in New York City, USA.

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FACULTY RECRUITMENT

Seeking early and mid-career professorship candidates with expertise in machine learning, AI, and computer science

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To build a world-class research program for AI- and data-driven innovation in human health, the Hasso Plattner Institute for Digital Health at Mount Sinai (HPI.MS) is seeking outstanding candidates for early- and mid-career positions with proven scholarship in computer science, artificial intelligence, and machine learning to join the Icahn School of Medicine at Mount Sinai faculty.

With the innovative platform programs Artificial Intelligence-Ready Mount Sinai (AIR.MS) and Digital Discovery Platform (DDP), HPI.MS offers candidates seamless and secure access to vast amounts of multimodal health data from New York City’s #1 Ranked Hospital.

Why HPI•MS

A new era of digital health

Combining an innovative health care system with world class engineering expertise to offer unprecedented opportunities for improved global well-being and medical discovery.


Expanding possibilities in medicine

Advancements in data science and engineering are rapidly translated into medical discovery in partnership with clinical experts.


Improving access to critical data

Data science powered by 7.6 million clinical records is connected to diverse genomic sequencing, comprehensive medical imaging, and biometric cardiology data, alongside innovative clinical research.


Optimizing human health and well-being

By linking comprehensive patient data from hospital visits, genetic testing, and remote monitoring devices, patients and their physicians will be able to monitor, diagnose and inform personalized treatment plans.


Advancing the state of the art

Leveraging the latest technologies, creating novel methodologies, and bringing together interdisciplinary expertise, HPI⋅MS is leading the digital health revolution.

Research

Leading the digital health revolution

AIR·MS - AI Ready Mount Sinai

AIR·MS - AI Ready Mount Sinai

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 : Mount Sinai's Central Digital Research Platform

Ehive : Mount Sinai's Central Digital Research Platform

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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Explore all research initiatives

Publications

World class research with a global impact

March, 2023

Abstract P458: An Examination of the Influence of Daily Intersectional Minority Stressors on Sleep Health in Sexual and Gender Minority People of Color

Journal

Circulation

HPI·MS Authors

Ipek Ensari

1 HPI•MS authors

Full list of authors

Joseph Belloir, Ipek Ensari, Kasey Jackman, Shayna Feuer, Anisha Bhargava and Billy A Caceres

Conference

Circulation

Open Publication

March, 2021

Genome-Wide Polygenic Risk Score for Retinopathy of Type 2 Diabetes

Journal

Human Molecular Genetics

HPI·MS Authors

Girish Nadkarni

1 HPI•MS authors

Full list of authors

Iain S Forrest , Kumardeep Chaudhary, Ishan Paranjpe , Ha My T Vy, Carla Marquez-Luna, Ghislain Rocheleau, Aparna Saha, Lili Chan, Tielman Van Vleck, Ruth J F Loos, Judy Cho, Louis R Pasquale, Girish N Nadkarni, Ron Do

Journal

Human Molecular Genetics

Open Publication

March, 2021

Relational Learning Improves Prediction of Mortality in COVID-19 in the Intensive Care Unit

Journal

IEEE Transactions on Big Data

HPI·MS Authors

Girish Nadkarni

1 HPI•MS authors

Full list of authors

Tingyi Wanyan, Akhil Vaid, Jessica K De Freitas, Sulaiman Somani, Riccardo Miotto, Girish N Nadkarni, Ariful Azad, Ying Ding, Benjamin S Glicksberg

Journal

IEEE Transactions on Big Data

Open Publication

March, 2021

Using C-JAMP to investigate epistasis and pleiotropy

Journal

Epistasis - Methods and Protocols

HPI·MS Authors

HPI•MS authors

Full list of authors

Stefan Konigorski, Benjamin S. Glicksberg

Book Chapter

Epistasis - Methods and Protocols

Open Publication

Press

HPI·MS in the news