Symposium on Model Accountability, Sustainability and Healthcare

SMASH 2025

November 4-5 2025

6666 Rue Saint-Urbain,
Montréal, QC H2S 3H1

Accepted Papers

Congratulations to all the accepted papers! You can see them and the spotlight papers on the accepted papers page.

About

The Symposium on Model Accountability, Sustainability and Healthcare (SMASH) is an interdisciplinary gathering focused on operationalizing AI safely and responsibly. The goal of this event is to identify challenges and propose technical, ethical and regulatory solutions to AI safety, data privacy, model interoperability and accountability. This symposium will explore these research topics through the lens of healthcare and sustainability.

The healthcare sector is rapidly embracing AI, and the insights gained are likely to inform future sustainability research. These disciplines operate within interconnected ecosystems of stakeholders, technologies, and datasets, sharing both the potential benefits and inherent risks.

Image showing people around a table discussing something

Important Dates

Jul 12, 2025: Submission opens
Aug 31, 2025: EXTENDED! Paper submission deadline
Sep 25, 2025: Announcement of decisions shared with Committee members
Oct 15, 2025: Camera-ready submissions deadline

Invite for Papers

We invite researchers to submit 4 page extended abstracts under the research areas defined below.

ML Safety, Privacy, Model Accountability and Alignment:

Safety, robustness and alignment of ML systems
ML systems and software traceability
Applications of privacy enhancing technologies (PETs): differential privacy, federated learning, etc.
ML performance and benchmarking methods
Mechanisms for ML provenance tracking and watermarking
Safety use cases for advanced AI systems

Interdisciplinary Submissions from Law and Social Sciences:

Acceptance of ML technologies by clinicians, patients, and administrators
ML risk assessments and disclosures
Ethical considerations when deploying ML systems
Regulation of ML technology

Contributions to SMASH that are of an applied nature are also welcome, such as case studies deploying ML with sensitive data.

Healthcare Applications:

Applications of AI in healthcare (administration, precision medicine, patient care, diagnostics)
Using patient data in ML research
Healthcare ML metrics, monitoring and benchmarking

Methods for ML Sustainability:

ML emissions accounting metrics
Case studies and applications of sustainability in ML
Sustainable computing and system design
Environmental accounting methods for ML

Sustainability, Healthcare and Safety, that's a bit of an odd mix - what's the deal?

You’re not wrong. But that's kind of the point! We’re firm believers that creating spaces that cut across academic boundaries yields compelling insights.

This event explores how AI in Sustainability and Healthcare are on parallel regulatory and operational trajectories and that they might benefit from a mutual exchange of ideas, governance and tooling.

Invited Speakers

Oana Balmau, McGill University
Goktug Bender, McGill University
Omar Benjelloun, Google DeepMind
Mark Casselman, Akinox
Ayse Coskun, Boston University
Audrey Durand, Université Laval, CIFAR
Vrushali Gaud, Google Sustainability
Christian Kästner, Carnegie Mellon University
Matt Kusner, McGill University
Maroussia Lévesque, Harvard University, CIGI
Doina Precup, Google DeepMind, Mila
Blake Richards, Mila, Montreal Neuro
Adriana Romero Soriano, Meta AI, CIFAR, Mila

We still have a few openings for invited speakers. If your work is broadly applicable, and you are willing to present in person, we invite you to submit a title for a talk and a brief description to the conference organizers: contact@smashcon.org.