About Me
I work at the intersection of building science, data, and climate action.
At Introba, I lead design analytics on complex decarbonization projects — bringing rigorous technical insight to real-world challenges in electrification, HVAC retrofits, and energy benchmarking.
As Co-Founder of Carbon Signal®, I’m building a platform that helps portfolio managers cut through uncertainty and move fast on carbon reduction. We combine simulation, data science, and intelligent defaults to prioritize what matters — and scale decarb strategies across entire building portfolios.
I hold a PhD in Mechanical Engineering (Polytechnique Montréal) and completed a Postdoc at MIT. My academic foundation taught me how to navigate complexity with discipline — and how to turn research into results. That mindset drives both my consulting and product work today.
Projects & OpenSource Tools
Democratization of urban building energy modeling.
I started this project with Yu Qian Ang and Zach Berzolla to accelerate the creation of Urban Building Energy Models (UBEMs). This project taught me how to develop and maintain a microservice on AWS.
The backbone of UBEM.io consists of 3 projects that I developed independently: pyumi, archetypal and umitemplatedb.
With UBEM.io, municipalities, consultants and researchers can upload a GIS footprint file with a height attribute, and download an UMI project file which can be opened in UMI for Rhino. After an energy simulation is run, the file can be uploaded to the Urban Model Visualizer to display a rich energy performance summary.
python scripting language to create, open and edit UMI projects.
This project was an opportunity to learn about Rhino 3DM files and the structure of Rhino 3D models. Using the recently open-sourced rhino3dm library, I was able to create UMI projects from scratch in a python environment without the use of the proprietary RhinoCommon API.
The package enables scripted workflows to open UMI projects and process the various module results (energy, mobility, district energy, etc.). It also enables the creation of new UMI projects from GIS files: import footprints, extrude geometries in 3D space and assign building template names based on a combination of feature attributes.
pyumi enables the Urban Model Generator as well as the Urban Model Visualizer.
Retrieve, construct, simulate, convert and analyze building energy models.
I started this project around the beginning of my PhD as a way of learning to code in Python, but also out of frustration with running Commercial Reference Building EnergyPlus models. Ep-Launch is clunky and it is a pain to upgrade old models to newer versions of EnergyPlus. Furthermore, I needed a way to efficiently read IDF models, run them and retrieve their results all in a Jupyter Notebook, the crown jewel of reproducible data analysis workflows.
I leveraged the excellent Eppy package to do the heavy lifting of parsing IDF models, but I rewrote the whole logic to handle file upgrades and simulation results. From this robust IDF model scripting language, I developed the model complexity reduction algorithms to create simplified 2-zone UMI models out of complex multi-zone IDF models. This in turn enabled the creation of building templates for the umi template database.
The structure of the archetype template database.
The umitemplatedb project was created out of a necessity to store and retrieve UMI Template Library Files online. The project defines the building template format, the backbone of UMI projects and handles the conversion of UMI Template Library Files to MongoDB documents and vice-versa.
Work Experience & Internships
Helping solve complex decarbonization challenges for large building portfolios.
I lead design analytics on complex decarbonization projects — electrification strategies, HVAC retrofits, and energy benchmarking for large building portfolios. I blend building science, data science, and coding to deliver rigorous, scalable solutions.
A platform to accelerate the path to low-carbon buildings.
I co-founded Carbon Signal® to help real estate teams figure out what actually matters when trying to cut carbon across hundreds of assets. We combine simulation, analytics, and smart defaults to turn messy decisions into clear next steps — and scale decarb strategies across entire building portfolios.
Developing tools at the SDL Lab reinforced my passion for creating robust analysis solutions that others can use.
As a Postdoctoral Fellow in the Sustainable Design Lab, I undertook research at the intersection of urban building energy modeling and district energy systems modeling to guide city planners, architects and engineers in designing and planning efficient buildings and urban systems.
Winning project: Demain Montréal. An ambitious Carbon Positive objective based on both a reduction of the embodied carbon of the building and a strong strategy to capture carbon during the operational phase.
I delivered a feasibility study for the implementation of an urban energy sharing network for the site of the De la Commune Service Yard. The study used an advanced topology optimization algorithm I developed during my PhD to explore various connectivity scenarios with an adjacent district energy plant. Also in the report, I outlined economic, legal, and technical opportunites and barriers for the project.
This report in addition to my help writing the “Energy Efficiency & Green Energy Production” chapter of the project’s proposal document helped our team secure the bid for the competition.
This internship was funded by the competitive Mitacs Acceleration scholarship.
At Pageau Morel, an MEP firm based in Montréal, Québec, I evaluated the potential of incorporating within the company workstream the use of novel building energy modelling tools such as Sefaira. I delivered a final report offering recommendations at the end of the internship.
Received a 2000$ scholarship for the program.
First hand ecological knowledge and engineering expertise bundled in a three-week program in the capital of energy efficiency building: Vienna.
Internship at the office of the developers of TRNSYS
During the internship, I learned to use TRNSYS, the simulation tool that would become a central part of my master’s thesis. My main task was to write technical documentation for future releases of TRNSYS.
Education
Ph.D. @ Polymtl
PhD Mechanical Engineering
2016 - 2020
Polytechnique Montréal is Canada's largest french-speaking engineering school.
Pursuing a PhD in mechanical engineering derives from my interest in the built environment and how early design decisions can impact the sustainability of a project. For my thesis, I applied principles of Integrated Design to the planning of heat-sharing networks.
B.Eng. @ Polymtl
Bachelor of Engineering | Civil Engineering
2010 - 2014
From structural systems to environmental science, my bachelor in civil engineering taught me a lot about the built environment.
A solid engineering foundation at Polytechnique Montréal taught me to efficiently solve complex problems.
Professional Affiliations
- ASHRAE — Member since 2014
- International Building Performance Simulation Association (IBPSA) — Member since 2015
- Bilingual: French (native) & English (native)
Awards & Scholarships
| Name | Organization | Value | Year |
|---|---|---|---|
| Postdoctoral Fellowship | Natural Sciences and Engineering Research Council of Canada | $45,000/yr | 2020-2021 |
| Hydro-Québec scholarship for excellence | Hydro-Québec | $25,000 | 2018 |
| FRQNT 3rd cycle scholarship | Fonds de recherche du Québec – Nature et technologies (FRQNT) | $20,000 | 2017-2018 |
| J.A. DeSève Foundation Prestige Scholarship | J.A. DeSève Foundation | $10,000 | 2017 |