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Inspiring the development of artificial intelligence for the benefit of all 

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Located in the heart of Quebec’s AI ecosystem, Mila is a community of more than 1,200 researchers specializing in machine learning and dedicated to scientific excellence and innovation.

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News

04 Jun 2025
Mila and Mastercard announce collaboration to improve AI fairness and transparency
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02 Jun 2025
Mila Welcomes Second Cohort of Indigenous Pathfinders in AI
Visual identity of the Indigenous Pathfinders in AI program.
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22 May 2025
Alfred partners with Mila to accelerate AI innovation in the food and beverage sector
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Faculty 

Founded in 1993 by Professor Yoshua Bengio, Mila today brings together over 140 professors affiliated with Université de Montréal, McGill University, Polytechnique Montréal and HEC Montréal. Mila also welcomes professors from Université Laval, Université de Sherbrooke, École de technologie supérieure (ÉTS) and Concordia University. 

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Latest Publications

Adaptation, Comparison and Practical Implementation of Fairness Schemes in Kidney Exchange Programs
William St-Arnaud
Margarida Carvalho
Golnoosh Farnadi
In Kidney Exchange Programs (KEPs), each participating patient is registered together with an incompatible donor. Donors without an incompat… (see more)ible patient can also register. Then, KEPs typically maximize overall patient benefit through donor exchanges. This aggregation of benefits calls into question potential individual patient disparities in terms of access to transplantation in KEPs. Considering solely this utilitarian objective may become an issue in the case where multiple exchange plans are optimal or near-optimal. In fact, current KEP policies are all-or-nothing, meaning that only one exchange plan is determined. Each patient is either selected or not as part of that unique solution. In this work, we seek instead to find a policy that contemplates the probability of patients of being in a solution. To guide the determination of our policy, we adapt popular fairness schemes to KEPs to balance the usual approach of maximizing the utilitarian objective. Different combinations of fairness and utilitarian objectives are modelled as conic programs with an exponential number of variables. We propose a column generation approach to solve them effectively in practice. Finally, we make an extensive comparison of the different schemes in terms of the balance of utility and fairness score, and validate the scalability of our methodology for benchmark instances from the literature.
2025-08-01
European Journal of Operational Research (published)
doi.org
arxiv.org
Clarifying a working definition for ‘precision communication’: a scoping review of medical literature on communication
Bao-Lam Pham
Brigitte N. Durieux
Amanda Bianco
Corinne Cécyre-Chartrand
Elena Guadagno
Amalia M. Issa
Dan Poenaru
2025-06-05
Personalized Medicine (published)
doi.org
Policy context and digital development: a comparative study of trajectories in 4 Canadian academic health centers over 30 years
Aude Motulsky
Susan Usher
Pascale Lehoux
Catherine Régis
Trish Reay
Paul Hebert
Lise Gauvin
Alain Biron
G Ross Baker
Marie-Pierre Moreault
Johanne Préval
Jean-Louis Denis
2025-06-05
Journal of the American Medical Informatics Association (published)
doi.org
Trophic Interactions Are Key to Understanding the Effects of Global Change on the Distribution and Functional Role of the Brown Bear
Pablo M. Lucas
Wilfried Thuiller
Lauren Talluto
Ester Polaina
Jörg Albrecht
Nuria Selva
Marta De Barba
Vincenzo Penteriani
Maya Guéguen
Niko Balkenhol
Trishna Dutta
Ancuta Fedorca
Shane C. Frank
Andreas Zedrosser
Ivan Afonso‐Jordana
Hüseyin Ambarlı
Fernando Ballesteros
Andriy‐Taras Bashta
Cemal Can Bilgin
Neda Bogdanović … (see 67 more)
Edgars Bojārs
Katarzyna Bojarska
Natalia Bragalanti
Henrik Brøseth
Mark W. Chynoweth
Duško Ćirović
Paolo Ciucci
Andrea Corradini
Daniele De Angelis
Miguel de Gabriel Hernando
Csaba Domokos
Aleksander Dutsov
Alper Ertürk
Stefano Filacorda
Lorenzo Frangini
Claudio Groff
Samuli Heikkinen
Bledi Hoxha
Djuro Huber
Otso Huitu
Georgeta Ionescu
Ovidiu Ionescu
Klemen Jerina
Ramon Jurj
Alexandros A. Karamanlidis
Jonas Kindberg
Ilpo Kojola
José Vicente López‐Bao
Peep Männil
Dime Melovski
Yorgos Mertzanis
Paolo Molinari
Anja Molinari‐Jobin
Andrea Mustoni
Javier Naves
Sergey Ogurtsov
Deniz Özüt
Santiago Palazón
Luca Pedrotti
Aleksandar Perović
Vladimir N. Piminov
Ioan‐Mihai Pop
Marius Popa
Maria Psaralexi
Pierre‐Yves Quenette
Georg Rauer
Slaven Reljic
Eloy Revilla
Urmas Saarma
Alexander P. Saveljev
Ali Onur Sayar
Çagan H. Şekercioğlu
Agnieszka Sergiel
George Sîrbu
Tomaž Skrbinšek
Michaela Skuban
Anil Soyumert
Aleksandar Stojanov
Egle Tammeleht
Konstantin Tirronen
Aleksandër Trajçe
Igor Trbojević
Tijana Trbojević
Filip Zięba
Diana Zlatanova
Tomasz Zwijacz‐Kozica
Laura J. Pollock
ABSTRACT Biotic interactions are expected to influence species' responses to global changes, but they are rarely considered across broad spa… (see more)tial extents. Abiotic factors are thought to operate at larger spatial scales, while biotic factors, such as species interactions, are considered more important at local scales within communities, in part because of the knowledge gap on species interactions at large spatial scales (i.e., the Eltonian shortfall). We assessed, at a continental scale, (i) the importance of biotic interactions, through food webs, on species distributions, and (ii) how biotic interactions under scenarios of climate and land‐use change may affect the distribution of the brown bear ( Ursus arctos ). We built a highly detailed, spatially dynamic, and empirically sampled food web based on the energy contribution of 276 brown bear food species from different taxa (plants, vertebrates, and invertebrates) and their ensemble habitat models at high resolution across Europe. Then, combining energy contribution and predicted habitat of food species, we modelled energy contribution across space and included these layers within Bayesian‐based models of the brown bear distribution in Europe. The inclusion of biotic interactions considerably improved our understanding of brown bear distribution at large (continental) scales compared with Bayesian models including only abiotic factors (climate and land use). Predicted future range shifts, which included changes in the distribution of food species, varied greatly when considering various scenarios of change in biotic factors, providing a warning that future indirect climate and land‐use change are likely to have strong but highly uncertain impacts on species biogeography. Our study confirmed that advancing our understanding of ecological networks of species interactions will improve future projections of biodiversity change, especially for modelling species distributions and their functional role under climate and land‐use change scenarios, which is key for effective conservation of biodiversity and ecosystem services.
2025-06-04
Global Change Biology (published)
doi.org
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AI for Humanity

Socially responsible and beneficial development of AI is a fundamental component of Mila’s mission. As a leader in the field, we wish to contribute to social dialogue and the development of applications that will benefit society.

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