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.
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.
Junior Developer
Chris de Graaf
Chris is in his fifth and final year of computer science at the University of Manitoba, where he studies AI and theoretical CS. He’s been involved with a bit of everything, from software development to infrastructure to research. Outside of school and work, his interests include endurance sports and sustainable transport.
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
Senior Developer
Fernando Chorney
Fernando is a huge fan of trying to make things easier and more efficient for all peoples and systems. When he’s not messing with his Linux servers at home, Fernando likes to cook, make music, play games, or work on learning new skills.
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 Engineer
Glenn Moynihan
Glenn Moynihan is native of county Cork in Ireland but upped sticks to study Theoretical Physics at Trinity College Dublin where he received his Bachelors in 2013 and his PhD in 2018. His research focused on improving the accuracy and scope of linear-scaling density-functional theory applied to large-scale calculations of materials exhibiting strongly-correlated electrons.
Senior Researcher
James Requeima
James is a senior researcher at Invenia and a PhD student studying machine learning at the University of Cambridge in the Computational and Biological Learning Lab under the supervision of Dr. Richard Turner. His interests include Bayesian optimization, learning, approximate inference methods, and deep generative models. He previously completed a master’s in machine learning, speech and language technology at the University of Cambridge under the supervision of Dr. Zoubin Ghahramani and a master’s of mathematics from the McGill University under Daniel Wise. He is also a tenured member of the Department of Mathematics at Dawson College in Montréal
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.
Mahdi Jamei
Mahdi Jamei received the B.Sc. degree in Science and Technology in 2013, M.Sc. in Electrical and Computer Engineering from Florida International University (FIU), Miami, FL in 2014 and Ph.D. in Electrical and Computer Engineering from Arizona State University (ASU), Tempe, AZ in 2018. His research interests lie primarily in developing computational analytic tools for power system employing mathematical and signal processing techniques. He has been studying the security challenges of interdependent critical infrastructures mainly power, cyber and gas networks over the past few years.
Developer Intern
Matt Spelchak
Matthew is a huge Linux nerd that enjoys public speaking. He loves various types of music and has lately been obsessing over optimizing Arch Linux for gaming. Matthew is a co-op student at Invenia.
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.
Developer Intern
Nicholas Josephson
Nicholas is a computer science student entering his fourth year at the University of Manitoba. He has previously held positions as an Undergraduate Researcher and Software Developer before beginning his co-op term at Invenia. In his spare time, and he enjoys learning and exploring new technologies.
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 has recently finished 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

If you are interested in joining our team please visit our career page at www.joininvenia.com to apply.
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.