Machine Learning for a better financial future. 💫
RBC Borealis’ AI Solutions team conducts research in artificial intelligence for financial services. We are a large team of researchers with backgrounds across artificial intelligence including computer vision, machine learning, and natural language processing, with PhDs in computer science, physics, computational finance, mathematics and more.
The research team undertakes fundamental and applied research, publishes papers, and works with large-scale datasets, deriving impactful machine learning models in collaboration with machine learning product owners and software engineers who help bring the research and prototypes to life.
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Scalable Temporal Domain Generalization via Prompting
Scalable Temporal Domain Generalization via Prompting
S. Hosseini, M. Zhai, H. Hajimirsadeghi, and F. Tung. Workshop at International Conference on Machine Learning (ICML), 2025
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Accurate Parameter-Efficient Test-Time Adaptation for Time Series Forecasting
Accurate Parameter-Efficient Test-Time Adaptation for Time Series Forecasting
H. R. Medeiros, H. Sharifi, G. Oliveira, and S. Irandoust. Workshop at International Conference on Machine Learning (ICML), 2025
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TabReason: A Reinforcement Learning-Enhanced LLM for Accurate and Explainable Tabular Data Prediction
TabReason: A Reinforcement Learning-Enhanced LLM for Accurate and Explainable Tabular Data Prediction
*T. Xu, *Z. Zhang, *X. Sun, *L. K. Zung, *H. Hajimirsadeghi, and G. Mori. Workshop at International Conference on Machine Learning (ICML), 2025
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Robustness of LLM-Initialized Bandits for Recommendation Under Noisy Priors
Robustness of LLM-Initialized Bandits for Recommendation Under Noisy Priors
A. Bailey, K. Wilson, Y. Cao, R. Aoki, and X. Zhu. Workshop at 31st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2025
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No Dtrain: Model-Agnostic Counterfactual Explanations Using Reinforcement Learning
No Dtrain: Model-Agnostic Counterfactual Explanations Using Reinforcement Learning
X. Sun, R. Aoki, and K. Wilson. Transactions on Machine Learning Research (TMLR), 2025
North Star
Research Areas
We focus on a set of challenging North Star research problems: Asynchronous Temporal Models, Non-Cooperative Learning in Competing Markets, and Machine Intelligence beyond Predictive ML.
Academic Partnerships
Our partnerships enable us to benefit from the latest in academia and transform that knowledge into real-world impact.
Let’s SOLVE it
New and diverse perspectives, awareness of challenges specific to local communities, and commitment to making a difference are needed today more than ever. Let’s SOLVE it is an RBC Borealis mentorship program for undergraduate students on a mission to solve real problem in their communities using AI. Let’s SOLVE it together.
Open Source Tools
AdverTorch
Advertorch is a Python toolbox for adversarial robustness research. The primary functionalities are implemented in PyTorch. AdverTorch contains modules for generating adversarial perturbations and defending against adversarial examples, as well as scripts for adversarial training.
GitHubLiteTracer
LiteTracer acts as a drop-in replacement for argparse, and it can generate unique identifiers for experiments in addition to what argparse already does. Along with a reverse lookup tool, LiteTracer can trace-back the state of a project that generated any result tagged by the identifier.
GitHubPrivate Synthetic Data Generation
This toolbox provides machine learning practitioners with the ability to generate private and synthetic data samples from real world data.It currently implements 5 state of the art generative models that can generate differentially private synthetic data.
GitHub
Fellowships
Supporting academic research sits at the core of RBC Borealis. Our Fellowship program supports graduate students’ research and career goals, helping advance the science of AI.
ML Research Internships
Research interns work with all our teams, collaborate with RBC on large-scale projects, and publish original research.
Careers
Research creates the models that underpin new products for RBC and its 17 million clients. We embrace diversity of perspectives, tenacity, and creative thinking to fundamentally advance what is possible in Machine Learning.
Join the teamCareers
Research creates the models that underpin new products for RBC and its 17 million clients. We embrace diversity of perspectives, tenacity, and creative thinking to fundamentally advance what is possible in Machine Learning.
Join the teamResponsible AI
Responsible AI is key to the future of AI technology, science, development, and adoption. Our RESPECT AI platform contributes knowledge, algorithms, programs, and tooling to help build technology that moves society forward.
Explore the hubResponsible AI
Responsible AI is key to the future of AI technology, science, development, and adoption. Our RESPECT AI platform contributes knowledge, algorithms, programs, and tooling to help build technology that moves society forward.
Explore the hub