Accueil

Inspirer le développement de l'intelligence artificielle au bénéfice de tous·tes

Un professeur s'entretient avec ses étudiants dans un café/lounge.

Situé au cœur de l’écosystème québécois en intelligence artificielle (IA), Mila rassemble une communauté de plus de 1400 personnes spécialisées en apprentissage automatique et dédiées à l’excellence scientifique et l’innovation.

À propos

À la une

Nouvelles

18 Juin 2026
Retour sur le concours Science éclair 2026 : faits saillants et annonce des lauréats
Photo de groupe des participants à la 4e edition du concours science éclair de Mila
Lire la nouvelle
17 Juin 2026
G+D lance un centre dédié à l’IA à Montréal afin de promouvoir une IA sécurisée pour les infrastructures critiques
Group picture of GD and Mila
Lire la nouvelle
12 Juin 2026
Mila Techaide 2026 : la communauté tech se mobilise et amasse près de 118 000 $
Photo d'Hugo Larochelle sur scène en train de faire une présentation lors de Techaide
Lire la nouvelle
Voir plus de nouvelles

Corps professoral

Fondé en 1993 par le professeur Yoshua Bengio, Mila regroupe aujourd'hui plus de 140 professeur·e·s affilié·e·s à l'Université de Montréal, l'Université McGill, Polytechnique Montréal et HEC Montréal. L'institut accueille également des professeur·e·s de l'Université Laval, de l'Université de Sherbrooke, de l'École de technologie supérieure (ÉTS) et de l'Université Concordia.

Consultez l'annuaire en ligne

Photo de Yoshua Bengio

Publications récentes

Empowering 2D neural network for 3D medical image segmentation via neighborhood information fusion
Qiankun Li
Xiaolong Huang
Yani Zhang
Bo Fang
Duo Hong
Junxin Chen
2026-06-30
Pattern Recognition (publié)
doi.org
Wagg: Cost-aware Aggregation of Windowing Operators in Stream Processing
Pritish Mishra
Ruoyu Deng
Alexandre da Silva Veith
Oana Balmau
Eyal de Lara
2026-06-19
International Conference on Mobile Systems, Applications and Services (publié)
doi.org
The digital heartbeat: a qualitative descriptive study on women's views on preventing cardiovascular disease in primary care
Ilhem Chaima Bousbiat
Samira Abbasgholizadeh Rahimi
Roland Grad
Charo Rodriguez
BACKGROUND: This empirical study aims to explore women's perspectives on cardiovascular disease and the use of digital health interventions … (voir plus)(DHIs) for their primary prevention and to gather insights on essential features for developing artificial intelligent-enabled technologies. METHODS: Adopting a qualitative descriptive research design, we conducted 15 semi-structured, in-depth interviews via Zoom with women at higher risk for cardiovascular disease. Participants were women over 40 years old, residing in Quebec, with at least one cardiovascular disease risk factor, and proficient in English. Recruitment was from a McGill University-affiliated clinic. An inductive thematic analysis approach was used for data analysis. RESULTS: Five major themes were identified: (i) understanding cardiovascular disease in a variety of ways, (ii) barriers and challenges to preventing cardiovascular disease in women, (iii) women taking charge of their cardiovascular well-being, (iv) mixed perspectives regarding artificial intelligent-enabled technologies for cardiovascular disease prevention such as Xi-Care, and (v) range of suggestions for the format and design of a prospective artificial intelligent-enabled technologies. CONCLUSIONS: Despite the prevalence of cardiovascular disease, there is a significant knowledge gap among women regarding the chronic nature and manifestations of these diseases. Artificial intelligent-enabled technologies like Xi-Care, with the potential for customization and interactive engagement, could enhance the primary prevention of cardiovascular disease in women, providing valuable insights for the subsequent phases of the project leading to Xi-Care's development.
2026-06-18
Family Practice (publié)
doi.org
Engineered Nonheme Iron Enzymes Enable Asymmetric Hydrogenation of Alkenes
Yunfei He
Shuang-Yu Dai
Mei‐Yan Xu
Baixu Ma
Jian Tang
Lizhi Tao
Zhen Liu
Developing biocatalytic systems capable of reducing simple alkenes is highly desirable for synthetic chemistry and biosynthesis, yet existin… (voir plus)g enzymes remain largely restricted to their ability to convert polarized, electron-deficient substrates. Here, we present a nonheme iron metalloenzyme platform that enables hydrogenation of styrenes, conjugated nitriles and amides, and nonconjugated olefins through a putative iron–hydride mechanism. Starting from the Fe(II)/ α -ketoglutarate-dependent dioxygenase GOX, iterative rounds of directed evolution produced an engineered “alkene hydrogenase” (AHase-6) containing 16 mutations and promoting NaBH 4 -driven reduction across diverse C═C bond motifs. Kinetic analysis indicates that this enzymatic hydrogenation process proceeds via formation of an enzyme–substrate ternary complex through a sequential mechanism. Mechanistic studies further reveal that alkene insertion occurs with regioselectivity governed primarily by substrate electronics and sterics. These findings establish nonheme iron enzymes as an unrecognized scaffold for metal–hydride-based hydrogenation and highlight their potential as sustainable, tunable alternatives to traditional catalytic systems.
2026-06-12
Journal of the American Chemical Society (publié)
doi.org
Voir plus de publications
Mila Ventures

Mila Ventures

Notre branche de capital de risque cultive la prochaine génération d'entreprises, soutenues par l'écosystème de recherche en IA de classe mondiale de Mila. Nous investissons dans des fondateurs·rices visionnaires qui bâtissent à la frontière des technologies de pointe, de l'IA, des STIM et au-delà.

Nous croyons que l'avenir sera façonné par les entrepreneur·e·s scientifiques.

En savoir plus

Une personne regarde un ciel étoilé.