Scientific Computing and Data / AIR·MS (AI Ready Mount Sinai) / News and Updates
News and Updates
Appointment of Mr. Herve DiBello as Director of Technology, AI-Ready Mount Sinai (AIR·MS), and Dr. Ashwin Sawant as Medical Director, AI-Ready Mount Sinai (AIR·MS).
March 2026
Herve DiBello brings 30 years of experience in the technology sector as a senior data engineer. Prior to joining Mount Sinai, he spent a significant portion of his IT career as a consultant for Systems, Applications, and Products in Data Processing (SAP), where he worked across various technologies and industries, focusing exclusively on healthcare solutions in recent years. In his new role, Mr. DiBello will lead an engineering team in bringing new data modalities to AIR·MS and serve as chief technical architect for new technology solutions integrated into the platform. His expertise will be pivotal in advancing the technological capabilities of AIR·MS and ensuring its seamless integration with healthcare research initiatives.
NEW!! Spring 2026 AIR·MS Training Sessions
We will be holding 3 AIR·MS training sessions this Spring. These sessions will introduce you to the AIR·MS environment and AI-related tools through live demonstrations you can follow along with. Each session will be offered in a hybrid format, with our team onsite to provide support and answer questions. Material will be provided 1 week prior to each session for registered users.
Register and attend the Spring 2026 training and use AIR·MS tools and you will be eligible to receive a free exclusive AIR·MS jacket!
Session 1: Getting Started with AIR·MS: Health Data Fundamentals
Tuesday April 7 (9:00 am – 10:00 am) | Hybrid In-Person & Zoom
- Zoom attendees: Register here for Getting Started with AIR·MS: Health Data Fundamentals
- In-Person Attendees (Annenberg Classroom 10-70): Register here
Session 2: From AI Agents to AIR·MS: Leveraging Large Language Models
Tuesday April 14 (9:00 am – 10:00 am) | Hybrid In-Person & Zoom
- Zoom attendees: Register here for From AI Agents to AIR·MS: Leveraging Large Language Models (LLM)
- In-Person Attendees (Annenberg Classroom 10-70): Register here
Session 3: Advanced AIR·MS: Deep Dive into Data Modalities and AI/Machine Learning (ML) Applications
Tuesday April 21 (9:00 am – 10:00 am) | Hybrid In-Person & Zoom
- Zoom attendees: Register here for Advanced AIR·MS: Multimodal Data
- In-Person Attendees (Annenberg Classroom 10-70):Register here
Please register ahead of time for sessions. Direct any questions through our new ticketing support system.
ALERT – MARK YOUR CALENDARS!
Digital Health Partnership Workshop and Datathon/Hackathon New York 2026
Mark your calendars for May 4–8, 2026: The Digital Health Partnership is coming to New York at the Mount Sinai Health System.
Stay tuned for more details!
January 2026
Artificial Intelligence – Ready Mount Sinai (AIR·MS). One Platform. Rapid Answers. Improved Research.
Research flourishes when ideas flow naturally into evidence, and each discovery builds on the last. AIR·MS has been created to bring this vision to life —a platform where data, analysis, and collaboration converge effortlessly, providing Mount Sinai with a single environment in which complex research can be conducted with clarity, efficiency, and speed.
At its core, AIR·MS combines clinical records, imaging, signals, and other research data in one unified system designed for both scale and performance. Large datasets reside in memory, allowing analyses to be performed interactively and iteratively. By supporting both relational and graph-based approaches, AIR·MS captures the richness of clinical and biological relationships, enabling researchers to explore questions in a manner that more closely reflects the real world.
AIR·MS Champions
Lothar H. Wieler, DVM
“Great solutions come with great minds, candor, integrity, and sincere teamwork that make them come into living. Through collaborative measures AIR·MS got momentum, and with our trusted partnership we will leverage this platform based on high quality data to generate excellent information, serving public health and health care.”
Dr. Ben Illigens
“Too often, biomedical research is slowed by fragmented data, complex access, and disconnected tools. AIR·MS addresses this challenge by making one of the world’s richest clinical datasets accessible in a high-performance, AI-ready environment. We´re now on track in onboarding 1,000 new users in 2026 – this marks a turning point in how we scale real-world evidence and empower researchers with everything they need on one platform to turn data into impact.”
Girish N. Nadkarni, MD, MPH
“The success of AIR·MS is grounded in teamwork. Advancing AI in real-world clinical settings requires clinicians, data scientists, engineers, and operational leaders working as one. It’s the collective effort, aligned around clear goals, that allows us to move from ideas to impact.”
AIR·MS Researcher Stories: Real Research. Real Impact.
To grow the AIR·MS (AI- Ready Mount Sinai) research community, we are launching the AIR·MS Researcher Stories campaign – putting researchers and their real-world use cases at the center.
We invite all AIR·MS users to share how they use the platform to access multimodal clinical data and advance AI-driven biomedical research. Selected stories will be featured across our website, newsletter, and social channels – strengthening peer learning and community visibility.
As a small thank-you, the first 50 researchers who share their story will receive an AIR·MS Researcher Trophy: a limited-edition mug celebrating community contribution and innovation.
With a target of 1,000 AIR·MS users, we believe real stories from real researchers are the most powerful way to grow – together.
Mount Sinai User Requirement Workshop – HPI Bachelor students visiting Mount Sinai Health Systems in New York
“The eight of you need to go to New York.”
That was what Lothar Wieler said in a meeting about two months ago. We followed that advice – and we are definitely not complaining.
“The eight” turned out to be Charlotte Beurer, Markus Rünzel, Tobias Rademacher, Peer Schild, Simon Kossack, Jan Berndt, Daniel Cermann and Nele Rodenhagen. And so, in January, we suddenly found ourselves in New York City, where our Bachelor project moved from shared documents and video calls to hospital corridors and real conversations.
Under the supervision of Lothar Wieler, we are developing a tool that supports Infection Preventionists in gaining a clearer overview of infection chains of specific pathogens especially MRSA. The aim is to turn complex data into something that is actually useful in everyday hospital work – the helping not only to respond to ongoing outbreaks but also to recognize risks early and prevent them.
AIR·MS With New Dataset
Uncovering Treatment Resistance in Psychiatry with AIR·MS –Zeinab Soleimani, PhD Candidate, Hasso Plattner Institute
Zeinab Soleimani’s research focuses on one of psychiatry’s most pressing challenges: understanding treatment resistance across anxiety, depression, bipolar, and schizophrenia spectrum disorders. These conditions often show overlapping symptoms and highly individual disease trajectories, making personalized treatment decisions difficult.
Using AIR·MS, Zeinab analyzes Electronic Health Records (EHR) and clinical notes from the Mount Sinai Health System to identify patterns of treatment resistance – defined by symptom alleviation, side effects, and patient adherence. Her work combines…