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.

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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.
optimization
We apply existing and develop new optimization techniques to make optimal decisions given our pattern recognition and prediction algorithms.
pattern-recognition
We analyze and find patterns in supply and demand of electricity, renewable generation and electricity price which help us make optimal decisions.
prediction
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

INTELLIGENT SOLUTIONS
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.
COMPLEX DECISIONS
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.
All
Leadership
Research
Development
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 Hudson
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.
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.
Developer
Adrienne Pind
Adrienne started at Invenia as a co-op student, then joined full time after graduting with her Bachelor of Computer Science (Honours) from the University of Manitoba. In her spare time she can be found cycling, playing frisbee, or canoeing.
Researcher
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.
Developer
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.
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.
Research Intern
Chris de Graaf
Chris is a student at the University of Manitoba with interests in artificial intelligence, theoretical computer science, and pineapple on pizza. In his spare time, Chris can usually be found running, cycling, or programming on hobby projects.
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.
Advisor
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.
Head of Operations
Dustin Hildebrandt
Dustin has been with Invenia since 2010. He received his Bachelor's Degree in Computer Science (Honours) with specializations in Databases and Theoretical Computer Science from the University of Manitoba. He architects and develops Invenia's development workflow, data gathering, and financial systems. Dustin is an avid cyclist, ballroom dancer, board gamer, and a clarinetist who regularly performs with the University of Manitoba Concert Band.
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.
Researcher
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 worked on High-Throughput Materials Science methods before joining Invenia.
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.
Senior Developer
Gem Newman
Gem has been with Invenia since 2008. When not working on project management or system architecture, he can usually be found writing something in Python or Julia. Outside of Invenia, Gem serves as chair of the board of directors for national science advocacy group Bad Science Watch and is the executive producer of the science podcast Life, the Universe & Everything Else.
Director of Marketing
Imran Sha
Imran joined Invenia in June 2017, to help the company with marketing. He comes with over 15 years of experience in marketing and management consulting. Imran has  worked in start-up environments, as well as large corporates. His last role was a Director of Marketing at AsiaInfo, a 14,000 people, software company. Prior to this, Imran worked as Head of Market Insights at Convergys, MBA Intern at PricewaterhouseCoopers, and Assistant Manager at Deloitte. He holds an MBA from Lancaster University, and a BA in Psychology from Osmania University.
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.
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.
Developer Intern
Nibrasul Ohin
Ohin is in his 4th year at the University of Manitoba and currently doing his 2nd internship with Invenia as a Junior Developer with interests in writing scripts, doing personal projects and socializing in his spare time. He’s always up for the adrenaline rush and likes going on adventures. He tries to make every second count and make the most out of it.
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.
Developer
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.
Senior Infrastructure Architect
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.
Researcher
Wessel Bruinsma
Wessel completed his M.Phil. in Machine Learning, Speech, and Language Technology at the University of Cambridge. At Invenia, he 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.
Advisor
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.
All
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FIlePaths
A type based approach to working with filesystem paths in julia.
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Holidays
Julia library for handling holidays.
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Arbiter
A concurrent task-runner that automatically resolves dependency issues.
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BayesianOptimization
A julia package for bayesian optimization of black box functions.
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Playground
A julialang environment builder (like python's virtualenv).
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ResultTypes
A Result type for Julia—it's like Nullables for Exceptions.
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DeferredFutures
Julia Futures which are initialized when written to.
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Mocking
Allows Julia function calls to be temporarily overloaded for purpose of testing.
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matpy
Call Python from MATLAB.
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FTPClient.jl
Julia FTP client using LibCURL.jl
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