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Applied Machine Learning Research

Empowering organizations through applied AI solutions

From Lab to Industry

The separation between business applications and academic AI research can sometimes make it difficult for organizations to identify and adopt the right technologies to tackle specific problems.

To bridge this gap, Mila’s Applied Machine Learning Research Team works with organizations on high-impact and challenging machine learning projects. The team's unique collaborative approach aims at designing and implementing cutting-edge solutions that benefit organizations by enriching their machine learning capabilities. Whether your project requires natural language processing, computer vision, or other forms of expertise, our team's diverse skill set can help you achieve your goals.

Contact us Meet the team

Collaborating With Us

Whether your organization needs help for hands-on development or requires expert advice, we offer our services with avenues favorable to industrial and intellectual property concerns and exciting funding opportunities.

Applied Research Projects Advisory services for SMEs

Applied Research Projects

From the earliest stages of AI projects, our specialists aim to establish proofs of concept to help organizations capture the full value of machine learning. Our teams strive to fully understand the problem being solved and how a machine learning model will be used in production. The success of our approach is due in large part to a solid understanding of the datasets we are entrusted with and rigorous experimental protocols set up according to project objectives.

A Distinctive Approach to Applied AI


Thorough analysis of the data and rigorous experimental protocols

Intellectual Property

Industry friendly intellectual property agreements

Value and Results

Committed to delivering value and rigorous results

Custom Approach

Custom approach to complex projects

Collaborative Process

Collaborative approach geared for knowledge transfer


Industry-level code and clear documentation

Recent Projects

Caisse de dépôt et placement du Québec

CDPQ collaborates with Mila to explore machine learning-based investment strategies.

CDPQ collaborates with Mila to explore machine learning-based investment strategies

We collaborated with CDPQ on a research project to explore machine learning-based investment strategies for predicting allocations of a portfolio of stocks, based solely on the past prices of those assets. Those strategies, referred to as momentum-based, showed interesting results in the recent literature and we wanted to verify the irapplicability to the investing context of CDPQ. In extension of this line of research, we tested the approach to a universe composed of S&P500 stocks rather than futures contracts and introduced transaction costs explicitly. To account for the characteristics of financial data, we applied a walk-forward training process to re-estimate the parameters, modified the objective function to ones actually used by practitioners, namely the Sharpe and Information ratios, and tested ensemble approaches. We proposed ideas based on continual learning to try to overcome the observed limitations of those models.


Leveraging reinforcement learning to optimize telemedicine for patient care at Dialogue.

Leveraging reinforcement learning to optimize telemedicine for patient care at Dialogue

Dialogue provides a virtual healthcare platform that aims to assign a patient to the right practitioner thanks to a chatbot whose goal is to collect all relevant information about a patient’s symptoms and antecedents. The system used by Dialogue is rule-based, and is therefore difficult to extend to include new pathologies or new medical knowledge. It also asks a lot of questions and doesn’t always collect all relevant information. Mila built a new model, based on reinforcement learning, that collects much more relevant information while asking a smaller number of questions. The training of this model includes a reward shaping function whose goal is to mimic the reasoning of a senior physician.

American Family Insurance

Using deep learning models to accelerate the completion and verification of claims at American Family Insurance.

Using deep learning models to accelerate the completion and verification of claims at American Family Insurance

American Family Insurance is interested in using deep learning models to assist its insurance professionals by accelerating the completion and the verification of claims for its automotive insurance line of products. Those models need to handle multimodal inputs such as text, categorical data, and images. The models will be designed to predict or verify the values of attributes describing individual vehicles involved in an accident, as well as overall claim-level attributes describing properties of the accident.

Optina Diagnostics

Optina Diagnostics partners with Mila to accelerate the early detection of Alzheimer’s disease.

Optina Diagnostics partners with Mila to accelerate the early detection of Alzheimer’s disease

Optina Diagnostics is developing the Retinal Deep Phenotyping™ platform for detecting the cerebral amyloid status and other key biomarkers for Alzheimer’s disease (AD). Given that the retina, lining of the eye, is an extension of the brain, it can provide insights into neurological pathologies. The goal of the project is to use Optina Diagnostics’ retinal hyperspectral images to detect phenotypes associated with cerebral amyloid status via direct observation of the retina. This approach is less invasive and less costly than brain amyloid positron emission tomography (A-PET) scans.

Retinal scans thus offer the possibility to improve the availability of tests which could lead to earlier AD diagnosis, and therefore improve the quality of life of impacted patients. We are using the results of a clinical study of a few hundred patients for whom both brain A-PET scans and Optina Diagnostics’ retinal hyperspectral images are available. Physicians analyzed the A-PET scans to categorize the cerebral amyloid beta status of the patients.

With this project, Mila has to work with a relatively small number of patients compared to typical deep learning datasets, as the reference standard, A-PET scans, are both expensive and inaccessible. But the large size of retinal hyperspectral cubes (in terms of spatial and spectral resolution) open vast possibilities for our research team.

We are collaborating with Optina Diagnostics’ machine learning team to accelerate the development of deep learning models and ensure that they continue to increase the accuracy and precision of their cerebral amyloid status test.

Hydro Québec’s Research Center

Hydro Québec’s research center and Mila collaborate to accurately predict solar irradiance in order to better understand the implications for electrical production.

Hydro Québec’s research center and Mila collaborate to accurately predict solar irradiance in order to better understand the implications for electrical production.

We are working with researchers at CRHQ to accurately predict the global horizontal irradiance (GHI) in Quebec and the north-eastern US from zero to six hours ahead, using images from a geostationary environmental satellite. The GHI is the total amount of shortwave solar radiation received by a horizontal surface (W/m2). Better predicting the GHI will primarily improve our understanding of the potential for electrical production using solar energy and provide additional tools to manage the electrical grid. One of the main challenges in this project is the scarcity of ground truth GHI signals, as the number of pyranometers in the territory of interest is extremely small.

Advisory services for SMEs

Our applied research experts offer advisory services to innovative Canadian small and medium -sized enterprises (SMEs) working on hands-on machine learning projects. We are committed to helping your business achieve its goals by tailoring our expertise toward your specific needs. Our team can:

  • Assist with the problem formalization;
  • Help define a robust experimental protocol;
  • Brainstorm ideas on how to choose the best models;
  • Provide guidance on model implementation.

We deliver our services to Canadian SMEs with funding support from the National Research Council of Canada Industrial Research Assistance Program (NRC IRAP).

If you are interested in accessing these services and are an existing NRC IRAP client, please contact your NRC IRAP industrial technology advisor. If you are not an existing client, please visit the NRC IRAP website for eligibility criteria and contact information.

Discover some of the companies we have helped
“Our collaboration with Mila has been a game changer for our AI strategy. Their team of experts brought invaluable insights and expertise, revolutionizing our AI techniques, models, and data annotation methodology. They streamlined our data annotation methods, making our datasets more efficient and our AI models significantly more accurate.

Communication with Hadrien and his team was always clear, and they consistently met deadlines. Their deep AI expertise pushed the boundaries of what we thought possible, setting us up for success in a competitive landscape.

In summary, Mila has elevated our AI capabilities, and we're thrilled with the results. We look forward to continuing our partnership and achieving even greater milestones together. Thank you, Mila, Hadrien and his team, for your invaluable contributions.”
Aldo Vargas
Software Director, Nexus Robotics
“As an early stage deep tech company, it is often hard to find the resources necessary to build your full vision. Good talent, especially in the deep learning space, is very hard to find and often out of reach for startups. The interactive visits provided by Mila’s applied research team are the perfect solution to this problem. At LUCID, we have not only benefited from a number of significant product improvements from this program, our team was also able to learn from world-class talent, upgrading our core competencies. This program is one-of-a-kind, and a real driver for innovation that levels the playing field for bright-minded entrepreneurs who are early in their journey.”
Aaron Labbé
CTO and Co-Founder, Lucid
“The support offered by Mila as part of the interactive visit was a key factor in successfully deploying our first deep learning-based product. Thanks to the advice provided by Mila’s members, we were able to quickly launch real artificial intelligence activities at Tootelo. Mila helped us select the necessary equipment, libraries required for analysis and training, and assisted us more than once when we encountered pitfalls. I think I can say beyond any doubt that without Mila’s contribution, we would never have been able to set up our service for predicting waiting times in medical clinics.”
Étienne de Villers
Business Intelligence Lead, Tootelo
“T-Base Communications Inc. was introduced to Mila by the National Research Council. We engaged Mila for support in our efforts to improve automated processes for the transformation of input documents into alternate formats for individuals who are blind or have low vision. Mila provided exceptional support and guidance, helping T-Base to identify deep learning models best suited for automated document transformation. Mila experts provided invaluable insight and research assistance, and the advice from these experts proved critical to improving our knowledge of deep learning solutions applicable to our document transformation requirements – helping to deliver the platform solution to address the market need for creating accessible documents.”
Sinisa Cvetkovic
Director of Software Innovation, T-Base Communications
“A wonderful collaboration with the Mila experts who allowed our teams to get to the next level in terms of AI production in real situations.”
Alain Lavoie
CEO, LexRock AI
“We already had some in-house expertise in AI. The collaboration with the experts of the applied research group allowed us to give a concrete boost to our current project. We were able to identify development paths and validate them in an exceptionally short time. We acquired expertise that would otherwise have taken us much longer to obtain. This interaction with Mila had a significant impact on our timeline.”
André Beaudin
Ing., Eng., Team Manager, Innovation, D-BOX Technologies Inc.
“Mila’s experts played an instrumental role in helping us advance our team’s machine learning capabilities and building internal expertise. Collaborating with Mila allowed us to build, test, optimize and deploy Roxi, the only AI algorithm for concrete performance prediction, analysis, and optimization. The algorithm is currently used by practitioners, on a daily basis, to analyze millions of cubic yards of concrete in thousands of projects worldwide.”
Andrew Fahim
M.Sc.E, Senior Manager, Research and Development, Giatec Scientific Inc.
“Mila was instrumental in identifying and integrating deep learning models of the “transformers” type that were more efficient than the models we were previously using. At the time, these models had just appeared in the literature and had not yet been popularized.”
Marc-André Morissette
VP of Technology, Lexum
“Our collaboration with Mila’s experts was essential to the development of our solution. More than just an application of their expertise, their approach based on knowledge transfer allowed us to really take ownership of the solution we developed together.”
Antoine Gagné
CTO, Whale Seeker, Inc.
“The opportunity to work with researchers from Mila’s Applied Machine Learning Research Team during an interactive visit over several months enabled Humanware to build a stronger infrastructure for its indoor object detection work. With a great openness and creativity, the approach of the Mila contributors involved effective mentoring. This interactive visit led to an original model architecture that we are currently working on, creating a highly beneficial experience for the Humanware team.”
François Boutrouille
Emerging Technology Leader, Humanware
“ The team's collective expertise in computer vision at Mila played a pivotal role in elevating our floor plan symbol detection project. Their innovative problem-solving abilities and dedication to maintaining high standards went beyond our expectations. Professional, communicative, and highly skilled, the team stands out as the go-to experts for delivering impactful solutions in computer vision. I wholeheartedly recommend their involvement in any project within this field. ”
Marzieh Zare
Data Science and Machine Learning Lead, Dreeven
“ The interactive sessions offered and led by Mila supported our team in improving the accuracy of our prediction models. We are deeply grateful to have benefited from this wonderful collaboration to deepen our knowledge and explore new avenues that have accelerated the pace of development of our product. ”
Katherine Cadieux-Auger
Hydraulics Team Leader, Assistant Manager, JFSA QC
« The collaboration with Mila institute has benefited our team, providing cutting-edge expertise that has directly contributed to refining our strategies and improving our artificial intelligence models. Mila's involvement in our technical decision-making process has facilitated in-depth exploration of different development avenues, enabling us to adopt innovative and effective solutions.»
Stéphane Turbide
COO, Maket

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