We Make Electrical Grids More Efficient

Machine learning and comprehensive datasets enables unprecedented understanding of complex problems and optimal solutions, resulting in a better outcome for all.
At Invenia, we understand this.

Proven Energy Intelligence System

Invenia’s EIS helps manage and optimize power grid operations. It solves complex problems quickly by using high volume and high frequency data linked to AI based decision-making models.


Energy Intelligence System

Invenia's EIS is a cloud-based machine learning platform that uses big, high frequency data to solve complex problems in real time. We use this technology to manage and optimize power grid operations.
We apply existing and develop new optimization techniques to make optimal decisions given our pattern recognition and prediction algorithms.
We analyze and find patterns in supply and demand of electricity, renewable generation and electricity price which help us make optimal decisions.
Electricity price, wind power or electricity consumption: We study the past, learn from it through automated algorithms and we predict the future.

What We Do

Invenia EIS system links forecasting, pattern recognition, and optimization to a model of the decision-making process customized to the user’s needs. The result is a decision recommendation, one that is the best answer to the problem that the user is trying to solve at any given time. The process involves understanding the problem from generation to transmission and delivery, adding massive efficiency along the way.
Electric grids face the challenges of intermittent wind and solar power, huge volumes of smart grid data, and demand response. These factors have added significant complexity and increased the pace required for operational decision-making.
The Energy Intelligence System
Invenia's EIS is a cloud-based machine learning platform that uses big, high frequency data to solve complex problems in real time. We use this technology to manage and optimize grid operations.

Our Team

We are a team of scientists, researchers and developers that come from machine learning, engineering, computer science, economics, theoretical physics, mathematics and management.
Chief Executive Officer / Co-Founder
Matt Hudson
Matt co-founded Invenia, and has been CEO from the start. He started Invenia while at Microsoft, after majoring in political science and economics with additional studies in computer science and engineering. He has developed a deep knowledge of the electrical grid, complex networks, and machine learning.
Chief Technology Officer / Co-Founder
Christian Steinruecken
Christian completed his PhD under the supervision of Prof Sir David MacKay at the University of Cambridge (UK), and is a specialist in machine learning. He has led engineering projects in artificial intelligence, data compression and probabilistic programming. Christian believes that building intelligent technology is our best hope for making the world a better place.
Chief People Operations Officer / Co-Founder
Oksana Koval
Oksana is a co-founder of Invenia and is currently the Chief People Operations Officer, overseeing operations in Canada and the UK. She attended the University of Manitoba and Red River College, where she studied Business Administration, and Anthropology as a post-graduate. In her spare time, she also pursues research interests in Machine Learning and Archaeology.
Managing Director Invenia Labs / Co-Founder
Cozmin Ududec
Cozmin is a co-founder of Invenia, and is currently Managing Director of Invenia Labs in Cambridge. He received his PhD in the foundations of quantum theory from the University of Waterloo, and is still puzzling over the quantum world in his spare time. Here are some of the papers Coz published: 1. Higher-order interference and single-system postulates characterizing quantum theory 2. Information-theoretic equilibration: the appearance of irreversibility under complex quantum dynamics 3. The structure of reversible computation determines the self-duality of quantum theory
Scientific Advisor / Co-founder
David Duvenaud
David is a co-founder of Invenia, and assistant professor in computer science and statistics at the University of Toronto. He received his Ph.D. in machine learning from Cambridge University. He has also worked at Google Research, the Max Planck Institute for Intelligent Systems, and the Harvard Intelligent Probabilistic Systems group.
Alex Robson
Alex has a PhD in Biophysics from Oxford University, where he worked on applying machine learning techniques to model biological data. Since then he has worked on different applications of ML, one for a startup in the energy sector and most recently risk models in fintech. In his spare time, he can be found playing board games, and occasionally hacking around on personal ML projects.
Scientific Developer
Aron Hofer
Aron finished his Computer Science degree at the University of Manitoba specializing in Machine Learning. Aron has been with Invenia since 2009, where he is responsible for the efficient application of the organization's Machine Learning algorithms.
Senior Researcher
Bella Wu
Bella got her PhD in engineering from the University of Cambridge, where she developed advanced signal processing techniques, including many based on Bayesian inference, for magnetic resonance applications. Before joining Invenia, Bella worked at a startup on building energy models that provide forecast and analysis for use in hedging, trading and investments. She is interested in combining mathematical modelling and machine learning with fundamental theories in fields such as engineering and economics to gain unique insights into complicated systems that have a significant social impact.
Brendan Curran-Johnson
Brendan is a developer and a documentarian at Invenia. Whether writing docs or infrastructure code. His goal is to make it easier for others to be able to do their work.
Cameron Ditchfield
Cameron originally joined Invenia as a co-op student from the University of Manitoba. An enthusiastic reader, Cameron enjoys a wide range of topics. From the sagas to The Guns of August, he likes to spend his free time with a good book.
Senior Researcher
Chris Davis
Chris was formerly an Assistant Professor in Energy Informatics and Modelling at the University of Groningen. He received his PhD at Delft University of Technology, and his work covers topics related to Energy, Sustainability, Linked Data, Machine Learning, Data Visualization and Agent Based Modelling. Here are a few papers published by Chris: 1. Secondary Resources in the Bio-Based Economy: A Computer Assisted Survey of Value Pathways in Academic Literature 2. Electric vehicle charging in China’s power system: Energy, economic and environmental trade-offs and policy implications 3. The state of the states: Data-driven analysis of the US Clean Power Plan For the rest of Chris' published work, please refer to his Google Scholar profile.
Developer Intern
Cole Peters
Cole Peters and is a 4th year Computer Science Student at the University of Manitoba. He is currently a Co-op at Invenia, planning to graduate in April 2019. He was born and raised in  Winnipeg. Some of his favourite pastimes include swimming, fishing, nature walks, and watching sports, specifically the Winnipeg Jets and Blue Bombers.
Head of Development
Curtis Vogt
Curtis works on managing, architecting, and developing the next generation of Invenia's EIS. He also is a contributor and advocate for the Julia programming language.
Doyne Farmer
Doyne works with Invenia as a research advisor. Professor in the Mathematical Institute at the University of Oxford, and an External Professor at the Santa Fe Institute. His current research is in economics, including agent-based modeling, financial instability and technological progress. He was a founder of Prediction Company, a quantitative automated trading firm that was sold to the United Bank of Switzerland in 2006. His past research includes complex systems, dynamical systems theory, time series analysis and theoretical biology.
Senior Developer
Eric Davies
Eric received their Bachelor's Degree in Computer Science (Honours) with specialization in Artificial Intelligence from the University of Manitoba. Eric architects and develops improvements to Invenia's data processing and machine learning pipeline while pushing for a faster, more capable EIS. Eric also contributes to the Julia community and helps lead the charge for new technologies at Invenia.
Eric Perim Martins
Eric received his PhD in Physics from the University of Campinas, where he worked on Nanotechnology problems using Computational Physical-Chemistry techniques. He then moved to Duke University where he worked on High-Throughput Materials Science methods before joining Invenia. Here are a few papers published by Eric: 1. Spectral descriptors for bulk metallic glasses based on the thermodynamics of competing crystalline phases 2. Inorganic Graphenylene: A Porous Two-Dimensional Material With Tunable Band Gap 3. Mechanical properties and fracture dynamics of silicene membranes 4. On the unzipping of multiwalled carbon nanotubes
Research Advisor
Francesco Caravelli
Francesco's research focuses on statistical physics and complex systems, in particular complex networks, memristive circuits, econophysics and agent-based modelling. He is a theoretical physicist, interested in quantum and classical systems and the application of techniques of statistical physics and complexity to other disciplines such as economics, engineering and finance. He has been a Senior Researcher at Invenia Labs in Cambridge and a researcher at the London Institute for Mathematical Sciences, before moving as an Oppenheimer Fellow to Los Alamos National Laboratory.
Research Intern
Gabriel Arpino
Gabriel is currently in his 4th year of the Engineering Science program at the University of Toronto. He has previously worked in the field of multi-robot systems at Carnegie Mellon University and Technion - Israel Institute of Technology. He loves jazz, and things that are hard to understand in general. Here are a few papers published by Gabriel: 1. Using Information Invariants to Compare Swarm Algorithms and General Multi-Robot Algorithms 2. Full Stack Swarm Architecture (Page 118 onwards)
Senior Researcher
James Requeima
James completed his Masters degree in Mathematics at the University of McGill. At Invenia, he works on our machine learning and risk management programs. He is currently working on finishing his masters in Machine Learning, Speech and Language Technologies in the department of Engineering at the University of Cambridge.
People Operations Manager
Joao Moraes
After completing a law degree Joao went into business through a variety of roles, ultimately completing an MBA at the University of Cambridge. His previous background includes managing all aspects of a restaurant chain, brand strategy consultancy, and leadership development.
People Relations Manager
Kajal Bansal
Born and raised in Winnipeg, Kajal has moved around quite a bit having had the opportunity to live in Singapore, Ottawa and Toronto before eventually permanently settling back in Winnipeg. As a designated CPA, Kajal has worked in accounting, loan portfolio management, business development and recruitment. She will also be working toward her Human Resource Management Certification over the next 12 months.
Letif Mones
I received my PhD in computational chemistry from ELTE University, Hungary, where I was working on the methodological improvement of hybrid QM/MM approaches and free energy computations for complex systems. At University of Cambridge and later at University of Warwick I developed an efficient sampling technique in combination with Gaussian process regression, introduced a protocol for constructing high dimensional quantum surfaces of organic molecules using machine learning and developed universal preconditioners to enhance the performance of optimisation techniques.
Senior Researcher
Lorenzo Sindoni
Lorenzo obtained a PhD in Theoretical Physics from SISSA (Trieste, Italy) for the last 6 years has been a researcher at the Max Planck Institute for Gravitational Physics in Potsdam-Golm (Germany), working on statistical approaches to quantum gravity. His main interests are emergent phenomena in many body physics, gravitational physics and complex systems on random graphs.
Senior Data Scientist
Mike de Denus
While working on his Master's degree, Mike developed a robotics system for maintaining formation movement with varying numbers of robots without the use of a centralized controller. His teams have won awards at numerous international robotics competitions. At Invenia, he focuses on the analysis and exploration of nodal and spot electricity markets.
Nicole Epp
Nicole graduated from the University of Manitoba with a Computer Science degree specializing in Theoretical Computer Science, Networks and Security, and Web-Based Systems. She also completed a minor in Chemistry. Nicole worked at Invenia for two co-op student work terms before joining full time in 2018.
Scientific Developer
Nick Thiessen
After completing BSc in computer science, Nick came to Invenia to work on building and maintaining machine learning systems and simulations. During his spare time, he can be found either developing, playing, or discussing games of all sorts.
Senior Developer
Rory Finnegan
Rory Finnegan joined Invenia as a Computer Science Co-op and Linux enthusiast with a background in Bioinformatics and Human Computer Interactions. Rory is currently completing a graduate degree in Computational Neuroscience.
Sam Morrison
Sam "no, the other Sam" is currently finishing her Bachelor of Computer Science (Honours) degree at the University of Manitoba. When not at work or studying, she can be found tending plants, watching science fiction shows, and attempting to learn useless skills.
Sam Massinon
Sam is a recent graduate from the University of Manitoba with a Bachelor of Computer Science. He started at Invenia as a co-op during the summer of 2015 and started working full time beginning in December of that year. He has been involved in a number of projects ranging from development to researching.
Director of Finance
Steve Marr
Steve is a CPA, CA who has worked at Deloitte, Great-West Life and most recently, as the Corporate Controller for the International Institute for Sustainable Development. He strives for continuous improvement and enjoys problem-solving collaboratively.
Head of Architecture and Operations
Sascha McDonald
Sascha is a senior executive with a track record of developing and implementing strategies to drive revenues and service delivery within start-up and blue-chip businesses. He comes with extensive international experience, key expertise includes: designing enterprise architecture, delivering operational capability across people, processes and technology; leading business development activity and contract negotiations to generate £multi-million revenue streams; leading multiple teams within both matrix and direct management environments; and managing relationships at CxO level with clients, suppliers and strategic partners.
Developer Intern
Timothy Levins
I’m from Malaysia and I’m currently in the 3rd year of my CS degree at the University of Manitoba. This is my first internship as a junior developer and I am working with the data feeds team building Invenia’s data gathering framework. I drum a little in my spare time, work on mobile apps on the side, and I am always down to explore new places.
Corporate Concierge
Wendy Maguire
After traveling the world as a flight attendant for 10 of years Wendy joined Invenia's team. She is from Kenora, Ontario, and she is in love with Lake of the Woods and all related water activities.  CrossFit is her current choice for fitness, but she has always been physically
active and enjoy cooking nutritionally. She volunteers at CrossFit competitions, Winnipeg Triathlon Club, her son’s school and Winnipeg Fire Department.
Wessel Bruinsma
Wessel is currently a PhD student at the University of Cambridge. He holds an MPhil in Machine Learning, Speech, and Language Technology also from the University of Cambridge. At Invenia, Wessel conducts research in the field of machine learning and investigates applications thereof. Research interests include probabilistic modelling, Bayesian nonparametrics, approximate inference, and signal processing.
Research Associate
Will Tebbutt
Will is currently a PhD student at the University of Cambridge, and occasionally advises on specific Machine Learning related matters at Invenia Labs. When not working he can be found playing the guitar, or listening to people play it well.
Zoubin Ghahramani
Zoubin works with Invenia as an advisor. He is also a professor of Information Engineering at the University of Cambridge, where he leads the Machine Learning Group consisting of about 30 researchers, and the Cambridge Liaison Director of the Alan Turing Institute, the UK's national institute for Data Science. His academic career includes concurrent appointments as one of the founding members of the Gatsby Computational Neuroscience Unit in London, and as a faculty member of CMU's Machine Learning Department for over 10 years. His current research interests include statistical machine learning, Bayesian non-parametrics, scalable inference, probabilistic programming, and building an automatic statistician. He has published over 250 papers, receiving over 30,000 citations (an h-index of 74).

Join Us

We are interested in meeting the best and brightest to help us solve our most challenging problems. If you are interested in joining our team or want to collaborate on a research project, send us an email at team@invenia.ca.
About Us

Invenia is a fast-growing technology startup headquartered in Winnipeg, Canada. We foster an innovative and collaborative culture, one that is the foundation of our success.

Our teams are composed of highly skilled individuals who love what they do, and are excited to use their talents to build a better tomorrow. We apply machine learning to solve some of the world’s most complex problems. We find meaning in what we do with our ability to reduce CO2 emissions and save lives by reducing pollution. It’s what drives us to work hard, and challenge our limits every day.

We are the first in the world to bring AI into the power grid, and have already made an enormous impact in North America. Invenia has been recognized nationally by the Canadian Youth Business Foundation as the Best Innovative Business, as well as the best overall business at the Foundation’s’ Chairman’s Awards.

Working at Invenia

Invenia’s team is the key to our success. We go to great lengths to take care of our people. We focus on providing a delightful workplace, enabling flexible schedules as well as locations, and fostering a social environment where everyone feels included.

Working at Invenia is an opportunity to collaborate with and learn from talented individuals at the top of their fields, to master new skills and grow professionally, intellectually and academically, all while helping to make the world a better place.

Current Opportunities

We are always looking for ambitious, hardworking, bright individuals in research, development, operations and infrastructure. We are also currently interested in individuals who have a background in grid scale power engineering, and physical electricity markets.

How to Apply

If you are interested in applying to work at Invenia, please send a resume, cover letter, and university transcript (for recent grads) to team@invenia.ca.

Open Source

Our projects using Julia, Python and MATLAB languages.
A type based approach to working with filesystem paths in julia.
Julia library for handling holidays.
A concurrent task-runner that automatically resolves dependency issues.
A julia package for bayesian optimization of black box functions.
A julialang environment builder (like python's virtualenv).
A Result type for Julia—it's like Nullables for Exceptions.
Julia Futures which are initialized when written to.
Allows Julia function calls to be temporarily overloaded for purpose of testing.
Call Python from MATLAB.
Julia FTP client using LibCURL.jl
This is us, drop by sometime.