English
Our philosophy
Our AI Lab is anchored by four core pillars
-
Research & development
We team up with world-class researchers and universities to push scientific discovery and shape the future of AI.
-
Sustainability
We create AI technologies to support energy optimization and the reduction of global carbon emissions.
-
Product creation
We turn breakthrough ideas and discoveries into ready-to-use products and applications – moving past the concept phase and into real-world impact.
-
Ethics & guardrails
We embed ethical and responsible AI principles and safeguards into how we design, develop and deploy our solutions.
Our team
A diverse ecosystem made up of the brightest minds in AI
BrainBox AI Trane Technologies AI Lab is home to a multidisciplinary team of over 100 technical experts - including software engineers, data scientists, AI researchers, machine learning developers and AI engineers. Comprised of some of the brightest minds in AI development and research, the team is primarily based in Montreal, Canada—one of the world’s leading AI hubs—with a reach and impact that extends across the globe.
Technology & academic members
Our areas of focus
Autonomous control
Development of technology using real-time data and advanced AI algorithms to enable the automated optimization of building assets using live equipment commands and control strategy assessments.
Highlighted Products
Published research papers
Hierarchical Multi-Agent Control Framework for Energy Efficiency and Carbon Emission Reduction in Multi-Zone Buildings
Occupancy Estimation Using Wifi Motion Detection via Supervised Machine Learning Algorithm
Sensing and Data Collection Methods for Occupant-Centric Building Control: A Critical Review of State of the Art
Agentic AI
Development of virtual agents designed to process and contextualize large volumes of internal and external data to deliver data visualization, reasoning, and informed human-in-the-loop automated actions using advanced LLM technology, with responsible AI guardrails and mechanisms to limit hallucination.
Highlighted Products
AI predictions
Advancement of deep learning models that can anticipate building needs with strong predictive performance, supporting improved real-time control strategies.
Highlighted Products
Published research papers
LSTM-Based Indoor Air Temperature Prediction Framework for HVAC Systems in Smart Buildings
Reinforcement Learning Approach for Predicting Occupant Preferences in Thermostat Set-Points
Data infrastructure
Ongoing optimization of high-performance tech stack with real-time data processing, continuous system checks, automatic model retraining and robust multi-layered protocols.
Highlighted Products
Published research papers
A Data-Driven Method to Test and Fine-Tune Occupant-Centric Building Control Prior to Implementation
Unified Architecture for Data-Driven Metadata Tagging of Building Automation Systems
Physics-informed neural networks
Combining traditional neural networks with fundamental physics principles to enhance physical interpretability and support improvements in prediction accuracy and training data needs.
Highlighted Products
Published research papers
Neural Differential Equations for Temperature Control in Buildings Under Demand Response Progress
Autoregressive Neural Networks with Exogenous Variables for Indoor Temperature Prediction in Buildings
Automated emissions reductions
Development of algorithms designed to support emissions reduction efforts, integrating real-time and forecasted emissions signals to derive consumption patterns and help prioritize cleaner energy sources.
Projects & Results
Published research papers
Responsible AI Principles
BrainBox AI Trane Technologies AI Lab believes responsible AI starts with trust, transparency and human oversight. Guided by responsible AI governance principles and ethical foundations, our approach to the development and deployment of intelligent building technology is grounded in responsible use, accountability and reliability.
