Chicago, IL 60611 United States
Overview
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DEADLINE: Applications will be accepted on a rolling basis. We will be evaluating/selecting and notifying candidates monthly while space remains.
Overview
Modern imaging now allows us to observe living systems across molecular, cellular, and tissue scales with unprecedented precision, yet our ability to extract mechanistic understanding to “learn the rules of life” from these data remains limited. Unlike molecular “omics” data, imaging captures continuous spatial and temporal information—shapes, motions, forces, concentrations and chemical potentials—that are inherently complex to represent, analyze, and interpret. The challenge lies in transforming this deluge of high-dimensional, dynamic spatiotemporal data into quantitative models, and linking these to other multi-modal data (e.g. proteomics, genomics, metabolomics), to reveal the governing principles of biological organization and dynamics across scales.
The goal of the program is to accelerate the development of image-based scientific machine learning for biological dynamics. Such approaches will enable “learning the laws” of biology directly from experimental images and movies, yielding new insight into how complex forms and behaviors emerge and evolve from the scales of sub-cellular structures to whole organs. Building shared benchmarks, interpretable methodologies, open tools, and cross-disciplinary collaborations will accelerate discovery and lay the foundation for a new era of AI-enabled scientific discovery for theory in biology across scales. We aim to (rapidly) bring together physicists, computer scientists, mathematicians and biologists to build on the current momentum in this evolving field.
Schedule/Activities
Scholars in Residence
We will select 16-18 scholars to be in residence at NITMB during the entirety of the 6-week program (February 1, 2027 to March 12, 2027). NITMB will pay for travel and lodging during the 6 weeks while at NITMB.
DEADLINE: Applications will be accepted on a rolling basis. We will be evaluating/selecting and notifying candidates monthly while space remains.
APPLY h̲e̲r̲e̲
Short Workshops
We invite proposals for small, focused workshops (1-3 days) to be held as part of the NITMB Scientific Focus Program on Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales. Submissions should clearly articulate the workshop’s focus, intended outcomes, and how it complements the scientific focus. Proposals should be submitted to p͟r͟o͟g͟r͟a͟m͟s͟@͟n͟i͟t͟m͟b͟.͟o͟r͟g͟.
Large Workshops
During the long program there will be three large workshops (4-5 days, 55-75 participants) associated with the goals of the program.
Workshop 1: “I͟m͟a͟g͟e͟-͟b͟a͟s͟e͟d͟ S͟c͟i͟e͟n͟t͟i͟f͟i͟c͟ M͟L͟ f͟o͟r͟ a͟d͟v͟a͟n͟c͟i͟n͟g͟ t͟h͟e͟o͟r͟y͟ i͟n͟ b͟i͟o͟l͟o͟g͟y͟” (February 1-5, 2027) Organizers: Aaron Dinner (University of Chicago), Ehssan Nazockdast (Allen Institute, Cell Science), Herve Turlier (Collège de France)
This workshop will focus on data-driven methods to employ imaging data in model discovery and building. This will include: force inference techniques, physics-constrained AI modeling approaches and data-driven model discovery. A͟p͟p͟l͟y͟ n͟o͟w͟.
Workshop 2: “I͟n͟f͟o͟r͟m͟a͟t͟i͟o͟n͟-͟t͟h͟e͟o͟r͟e͟t͟i͟c͟ m͟e͟t͟h͟o͟d͟s͟ f͟o͟r͟ l͟e͟a͟r͟n͟i͟n͟g͟ d͟y͟n͟a͟m͟i͟c͟s͟” (February 8-12, 2027) Organizers: Kristofer Bouchard (Lawrence Berkeley National Laboratory), Ilya Nemenman (Emory University). A͟p͟p͟l͟y͟ n͟o͟w͟.
Workshop 3: “L͟e͟a͟r͟n͟i͟n͟g͟ M͟u͟l͟t͟i͟v͟a͟r͟i͟a͟t͟e͟ S͟p͟a͟t͟i͟o͟‑͟T͟e͟m͟p͟o͟r͟a͟l͟ D͟y͟n͟a͟m͟i͟c͟a͟l͟ M͟o͟d͟e͟l͟s͟” (March 1-5, 2027) Organizers: Wenying Shou (University College London), Margaret Johnson (Johns Hopkins University), Yanlan Mao (University College London), Jianhua Xing (University of Pittsburgh). A͟p͟p͟l͟y͟ n͟o͟w͟.
Small, Focused Workshops
(~20 people, 1-3 days)
“E͟q͟u͟a͟t͟i͟o͟n͟ d͟i͟s͟c͟o͟v͟e͟r͟y͟ o͟f͟ t͟i͟s͟s͟u͟e͟ a͟n͟d͟ o͟r͟g͟a͟n͟ d͟y͟n͟a͟m͟i͟c͟s͟“ (February 22-24, 2027) Organizers: Andrei Klishin (University of Hawaiʻi at Mānoa), Luka Pocivavsek (University of Chicago), David Bortz, University of Colorado, Boulder.
Other Activities during Long Program
We will select and support other types of activities during the Long Program.
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Dedicated Hackathons & Training
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Opportunity for short term visitors who wish to participate in activities some of the activities
Other Activities outside the dates of the Long Program
There will be synergistic activities associated with upcoming NITMB workshops to build momentum throughout the year, and after the long program.
Tutorials/Discussions for Planned Workshops:
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C͟e͟l͟l͟s͟ S͟t͟a͟t͟e͟s͟ &͟ T͟r͟a͟n͟s͟i͟t͟i͟o͟n͟s͟(June 30-July 2, 2026)
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Pre Workshop Tutorials and Poster Session (June 29)
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Optimal Transport and Learning Dynamical Systems Equations by Elizabeth Jerison (12:15-1:45)
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AI Tools/Methodologies to Learn Cell State Transitions From Single Cell Data by Samantha Riesenfeld (2:00-3:30)
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Poster Session (4:00-5:00)
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B͟i͟o͟l͟o͟g͟i͟c͟a͟l͟ F͟u͟n͟c͟t͟i͟o͟n͟ a͟n͟d͟ S͟p͟a͟c͟e͟ &͟ T͟i͟m͟e͟:͟ F͟r͟o͟m͟ F͟o͟r͟c͟e͟s͟ &͟ C͟u͟e͟s͟ t͟o͟ E͟m͟e͟r͟g͟e͟n͟t͟ D͟e͟c͟i͟s͟i͟o͟n͟ M͟a͟k͟i͟n͟g͟ (Sept 14-18, 2026)
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R͟e͟p͟r͟e͟s͟e͟n͟t͟i͟n͟g͟ a͟n͟d͟ L͟e͟a͟r͟n͟i͟n͟g͟ M͟o͟r͟p͟h͟o͟l͟o͟g͟y͟ i͟n͟ B͟i͟o͟l͟o͟g͟y͟(Oct 19-23, 2026)
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Participants
Scholars-in-Residence
- Ben Cardoen – University of Birmingham
- Joel Dokmegang – SRH University of Applied Sciences Berlin
- Ahmed Elhady – Max Planck Institute of Animal Behavior / University of Konstanz
- Nabin Giri – Lawrence Berkeley National Laboratory
- Jacqueline Janssen – Laboratoire de Physique de l’École Normale Supérieure, ENS Paris
- Jinghui Liu – Max Planck Institute of Molecular Cell Biology and Genetics
- Georg Meisl – University of Cambridge
- Emna Ouni – Gustave Roussy Cancer Center
- Ivan Sudakow – The SETI Institute
- Hervé Turlier – CNRS- Centre national de la recherche scientifique
- Paul Villoutreix – CENTURI, INSERM, AMU
- Ray Zirui Zhang – Worcester Polytechnic Institute
Image-Based Scientific Machine Learning for Advancing Theory in Biology
February 1-5, 2027 | C͟l͟i͟c͟k͟ H͟e͟r͟e͟ f͟o͟r͟ W͟o͟r͟k͟s͟h͟o͟p͟ W͟e͟b͟p͟a͟g͟e͟
Organizers
- Aaron Dinner, University of Chicago
- Ehssan Nazockdast, Allen Institute
- Herve Turlier, French National Centre for Scientific Research
Participants
- Chase Broedersz – Vrije Universiteit Amsterdam
- Jonathan Colen – William and Mary
- Margaret Gardel – University of Chicago
- Ondrej Maxian – University of Notre Dame
- Mor Nitzan – Hebrew University
- Ivo Sbalzarini – University of Zurich
- Jin Wang – Stony Brook University
- Lingchong You – Duke University
Information-theoretic methods for learning dynamics
February 8-12, 2027 | C͟l͟i͟c͟k͟ H͟e͟r͟e͟ f͟o͟r͟ W͟o͟r͟k͟s͟h͟o͟p͟ W͟e͟b͟p͟a͟g͟e͟
Organizers
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Kristof Bouchard, Lawrence Berkeley National Laboratory
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Ilya Nemenman, Emory University
Participants
- Randall Balestriero – Brown University
- Margaret Gardel – University of Chicago
- William Gilpin – UT Austin
- Sidhartha Goyal – University of Toronto
- Ahmed El Hady – University of Konstanz / Max Planck Institute of Animal Behavior
- Elizabeth Jerison – University of Chicago
- Allon Klein – Harvard Medical School
- Nathan Kutz – Autodesk Research
- Andre Levchenko – Yale University
- Benjamin Machta – Yale University
- Mor Nitzan – Hebrew University
- David Schwab – CUNY Graduate Center
- Greg Stephens – Vrije Universiteit Amsterdam & OIST Graduate University
- Vincenzo Vitelli – University of Chicago
Learning Multivariate Spatio‑Temporal Dynamical Models
March 1-5, 2027 | C͟l͟i͟c͟k͟ H͟e͟r͟e͟ f͟o͟r͟ W͟o͟r͟k͟s͟h͟o͟p͟ W͟e͟b͟p͟a͟g͟e͟
Organizers
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Wenying Shou, University College London
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Margaret Johnson, Johns Hopkins University
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Yanlan Mao, University College London
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Jianhua Xing, University of Pittsburgh
Participants
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Alex Browning – University of Melbourne
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Rebecca Crossley – University of Oxford
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Carles Falco – University of Oxford
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Rikki Garner – The University of Texas at Austin
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Yi Jiang – Georgia State University
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Brian Munsky – Colorado State University
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Steve Presse – Arizona State University
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Hervé Turlier – CNRS
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Qiong Yang – University of Michigan