We come from many backgrounds including machine learning, mathematics, physics, computer science, engineering and economics. We are all interested in problems that have a substantial impact on the world, specifically complex systems that involve economic and environmental efficiency.
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 where she studied Anthropology as a post-graduate. In her spare time, she also pursues research interests in machine learning and archaeology. In the past, she has excavated a 3,000-year-old settlement in Crete, Greece, and for her Master’s thesis, she applied machine learning to identify the ceramic manufacturing techniques of ancient potters.
Managing Director Invenia Labs/ Chief Science Officer / Co-Founder
Cozmin Ududec
Cozmin is a co-founder of Invenia and now also the Managing Director and Chief Science Officer 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 an assistant professor in computer science and statistics at the University of Toronto. He received his PhD in machine learning from Cambridge University. Before Invenia, he also worked at Google Research, the Max Planck Institute for Intelligent Systems, and the Harvard Intelligent Probabilistic Systems group.
Researcher
Abraham Alvarez-Bustos
Abraham Alvarez-Bustos was born in Mexico. He received a B.Sc. degree in Electrical Engineering from Instituto Politécnico Nacional (IPN) - ESIME, Mexico City, Mexico, in 2012. Then, a M.Sc. degree in Electrical Power Systems from the IPN - Sección de Estudios de Posgrado e Investigación (SEPI), Mexico City, Mexico, in 2015, where he got First Class Honours and an Honorific Mention. In 2016 he worked as a Transmission System Analyst in the National Control Centre of Energy (CENACE), Mexico. He obtained a Ph.D. degree at Durham University, Durham, UK in the area of Power Systems optimization and Control. His principal research interests lie in developing methods, models and software aimed at Power Systems Computational Analysis and Optimisation for Planning.
Alex has a PhD in Biophysics from Oxford University, where he worked on applying machine learning techniques to model biological data. Since then, he's worked on numerous applications of ML, including one for a startup in the energy sector and another for risk models in fintech. In his spare time, Alex can often be found playing board games or occasionally hacking around on personal ML projects.
Researcher
Andrew Rosemberg
Andrew received a BSc in control engineering from PUC-RIO and a BSc in general engineering from École Centrale de Marseille. He also holds a master's in Electrical Engineering with an emphasis on Operation Research, focusing on Power Systems and Energy markets. Some of his previous projects revolve around energy economic dispatch analysis and simulation, financial data classification and portfolio optimization. His main interests are optimization, decisions under uncertainty and machine learning.
Researcher
Anton Isopoussu
Most recently, Anton has been interested in unsupervised learning using ideas from optimal transport. Before getting into machine learning, he studied mathematics, physics and computer science in Helsinki and then went on to complete a PhD in algebraic geometry in Cambridge.
Arnaud graduated from the University of Edinburgh with an MSc in Artificial Intelligence in 2012. Since then, he's been working at various companies as a software engineer, notably in the music streaming industry and in the emerging space of autonomous vehicles. In his spare time, he enjoys travelling and tinkering with pet projects.
After achieving a Masters in Economics and Econometrics at the University of Sydney, Astrid completed her PhD in machine learning at the University of New South Wales. She has previously worked as a professional econometrician in the energy and financial sectors but now, as a researcher for Invenia, she finds ways of improving the computational efficiency of multi-task Gaussian process models for solar power forecasting. Her main research interests are scalable nonparametric methods for spatiotemporal modeling, structured prediction and grid integration of distributed generation.
Senior Researcher
Bella Wu
Bella achieved her PhD in engineering at 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.
Research Engineer
Ben Cottier
Ben completed an MSc Artificial Intelligence at The University of Edinburgh in 2020. He likes to take a closer look at machine learning research and build software to make it better. When he’s not working, you might find him hiking or pondering the future of AI.
Research Engineer
Branwen Snelling
Branwen did her PhD in Geophysics at Imperial College London, where she used an array of computational fluid dynamics models to research landslide-tsunami hazards. Along the way she explored uncertainty quantification and machine learning methods for natural hazard assessment. She is interested in building and using modelling tools to better understand the natural world and other complex systems.
People Operations Associate
Caolán Jennings
Caolán has been a Cambridge local since 2007. With an academic background in philosophy and law, he is always ready for a friendly chat. Outside of work you can normally find him enjoying a good book or playing music with friends.
Chief Financial Officer
Dan Allen
Dan is an experienced financial leader who has held senior positions in several tech businesses. His corporate finance experience spans from raising debt and equity funds to leading on several mergers and acquisitions deals, including exits. Commercially he has experience of building scalable operational and financial infrastructure in global tech businesses and has led operational and data teams. He has vast experience of being a member of strategic management teams, including holding both exec and non-exec board seats.
Alongside his work with Invenia as a Research Advisor, Doyne is also a 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.
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 he looked into High-Throughput Materials Science methods before joining Invenia.
Research Intern
Felix Opolka
Felix received his BSc in Computer Science from the Technical University of Munich and his MPhil in Computer Science from the University of Cambridge. Now he is working towards his PhD in Machine Learning at the Computer Lab of the University of Cambridge. He is interested in probabilistic modelling of network data, especially using Gaussian processes, and geometric machine learning.
Research Advisor
Francesco Caravelli
Francesco's research focuses on statistical physics as well as 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 Bachelor's 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.
Ian is a recent Master's graduate in data science from the University of Edinburgh where he has previously completed a Bachelor's degree in Physics. His main area of interest is how we can use data science and machine learning to help in the transition of the energy sector to a more renewable mix. His interests in machine learning are broad, with a particular interest in probabilistic modelling, Bayesian learning, and graph theory.
People Operations Associate
Jackie Diab
Jackie graduated in 2021 with a CIPD certified BSc in Business and Human Resource Management from Anglia Ruskin University. Before joining Invenia she has worked in various people management roles within the retail industry and has experience with HR administration, recruitment and delivering training. She’s passionate about fostering a healthy culture in the workplace, and is excited by the emergent field of people analytics.
James graduated with a BSc in Mathematics from Loughborough University. Before working at Invenia, he worked as a DevOps engineer for a startup developing artificial intelligence software for the legal profession.
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 optimisation, 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.
Research Intern
Jared Wentz
Jared is currently working towards an MSc in Computational Statistics and Machine Learning at University College London. Previously, he worked as a software engineer at JPMorgan and FanDuel, and holds a BS in Mathematics and Computer Science from Indiana University. Jared is working at Invenia as a research intern to complete his dissertation on bandit learning in electricity markets.
Talent Specialist
Jasmin Geddes-Rainbow
After gaining a degree in languages from the University of Cambridge, Jasmin spent a number of years working in business operations management at the University before choosing to specialize in Talent Acquisition. Outside of work, she can usually be found singing with her band, travelling, or in the gym.
People Operations Manager
João 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.
Data Scientist
Josh Chadney
Josh is a space and atmospheric physicist with a PhD in planetary aeronomy from Imperial College London, where he worked on building physical models of the upper atmosphere of extrasolar planets. He has since performed measurements of the northern lights from Svalbard, in the high Arctic, to infer the temperature of Earth’s upper atmosphere as a postdoctoral research fellow at the University of Southampton. More recently he has built systems to measure and monitor gas flaring and pollutant emissions produced by the energy industry for an environmental services start-up.
Senior Researcher
Joshua Knowles
Josh is an honorary professor at the Alliance Manchester Business School (University of Manchester), and an honorary fellow at the School of Computer Science, University of Birmingham. He is interested in developing robust algorithms for optimization, optimal control and decision making, particularly for problems involving multiple objectives, uncertainty, dynamical aspects (including interruptions), and human interaction. He is also interested in the ethical use of optimization and machine learning.
Letif received his PhD in computational chemistry from ELTE University, Hungary, where he worked on the methodological improvement of hybrid QM/MM approaches and free energy computations for complex systems. At the University of Cambridge and later at the University of Warwick, he developed an efficient sampling technique in combination with Gaussian process regression. In addition to this, he also 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.
Research Engineer
Lyndon White
Lyndon is passionate about building the tools to do research better. His current specific interests are around tooling for machine learning libraries, in particular automatic differentiation. Lyndon completed his PhD on Natural Language Processing via Machine Learning (Titled “On the surprising capacity of linear combinations of embeddings”) at the University of Western Australia in 2018. He has been programming Julia since 2014, and is currently a maintainer of, and contributor to, some unreasonable number of packages.
Facilities Coordinator
Magda Karavatou
Magda was born in Thessaloniki, Greece, and moved to Cambridge in 2019. She has previously studied Economic Science at the University of Macedonia and has received an IT skills certificate from the University of Cambridge.
Mahdi Jamei received a BSc degree in Science and Technology in 2013 and an MSc in Electrical and Computer Engineering from Florida International University in 2014. He then went on to achieve a Ph.D. in Electrical and Computer Engineering from Arizona State University in 2018. His research interests lie primarily in developing computational analytic tools for power systems employing mathematical and signal processing techniques. He has been studying the security challenges of interdependent critical infrastructures of power, cyber and gas networks over the past few years.
Data Scientist
Max Lensvelt
Max has worked in power markets and renewable energy within the UK, Europe, and the United States for almost a decade. His experience encompasses analytical roles in private equity, utilities, and industry. Most recently, he has worked as a Data Scientist for the developer of the UK's first virtual power plant. He also holds a BSc in Physics and an MSc in Data Science.
Meas was previously a postdoctoral researcher at the University of California, Santa Barbara. She received her PhD in environmental engineering from the University of Southern California. She also holds an MS in mechanical engineering from USC, and a BS in mechanical engineering from California State University, Los Angeles.
Research Engineer
Miha Zgubič
Miha, originally from Slovenia, is a theoretical physicist by training and holds an MSci degree from Imperial College London. After completing his Masters, he moved to the countryside to pursue a PhD at the University of Oxford where he analysed the data from the Large Hadron Collider at CERN searching for a rare decay of the Higgs boson. He likes python, boosted decision trees, and Federer's one-handed backhand.
Research Engineer
Nick Robinson
Nick recently completed a master's in AI at Edinburgh University, having previously studied analytic philosophy at Cambridge. In between, he worked at ASI building machine learning models for all sorts of different companies.
Researcher
Raphael Saavedra
Raphael received his MSc and BSc degrees in Electrical Engineering with an emphasis in Operations Research from the Pontifical Catholic University of Rio de Janeiro. He previously worked in projects with major electricity distribution companies with the goal of forecasting demands and optimizing contracts. He is also a Julia programmer and contributes to open- source projects. His main interests are optimization, time series models, and power system operation.
Talent Specialist
Robbie Smith
Robbie graduated from the University of Southampton with a Bachelor’s degree in Music, where he specialised in composition. Since then, he has worked in technical recruitment and a variety of administrative roles. Robbie loves learning about new technologies and computing. He also enjoys writing music and comedy in his spare time.
Chief Analytics Officer
Sam Hancock
Sam is a strategic analytical leader who has worked at companies ranging from 5-person startups to $100B+ multinationals. Most recently he guided Waymo’s Engineering Operations organization, the team that supports software development for Alphabet’s self-driving car project. At Invenia he is responsible for analytically connecting the company’s activities to its overarching objectives. Outside of work Sam is a semi-professional drummer, performing on the West End multiple times, and competes in triathlons.
Head of Architecture and Operations
Sascha McDonald
Sascha is a senior executive with a track record of developing and implementing strategies that drive revenue and service delivery within start-up and blue-chip businesses. His expertise includes designing enterprise architecture and delivering operational capability across people, processes and technology. In addition to this, he has masses of international experience in leading business development activity, contract negotiations to generate multi-million-pound revenue streams, and leading multiple teams within both matrix and direct management environments. His previous work has also included managing relationships at the CxO level with clients, suppliers, and strategic partners.
Sean received his PhD in computational physics from the University of Cambridge, where he worked on adaptive meshing methods in computational fluid mechanics. Since then, he has worked as a research scientist in R&D for the oil and gas industry, where his research interests included complex fluids, reduced-order models, and the application of statistical modelling to physical systems. He has also been involved in several academic collaborations and physics outreach projects.
Timothy was born in Malaysia and has recently graduated from the University of Manitoba with a bachelor’s of science degree in Computer Science. His work at Invenia started as part of his first internship as a junior developer, and he spent most of his time working with the data feeds team to build Invenia’s data gathering framework. In his spare time, he loves to explore new places.
Tom graduated from the University of Nottingham with a BSc in Mathematics. Outside of work, It's important for him to be active, this includes sports and the gym. He also enjoys going out with friends for food and trying new things.
Machine Learning Researcher
Tom Gillam
Tom has a broad interest in the application of statistical learning to real-world problems. He has a PhD in High Energy Physics from Cambridge, working with the ATLAS experiment at CERN. Prior to joining Invenia, Tom worked for a quantitative hedge fund, specializing in portfolio optimization, risk modelling, and strategy development. His research interests include Bayesian methods, optimization, and the incorporation of symmetries, causality, and other physical structure into models.
Researcher
Wessel Bruinsma
Wessel is currently a PhD student at the University of Cambridge. He holds an MPhil in Machine Learning and Machine Intelligence also from the University of Cambridge. At Invenia, Wessel researches machine learning and investigates applications thereof. His main research interests include probabilistic modelling, Bayesian nonparametrics, approximate inference, and signal processing.
Research Associate
Will Tebbutt
Will is currently a PhD student in the Machine Learning Group at the University of Cambridge. He is interested in probabilistic models for spatio-temporal phenomena, in particular Gaussian processes. He occasionally advises on specific machine learning problems at Invenia. When not working, he can be found playing the guitar, or listening to people play it well.
Machine Learning Researcher
Will Wilkinson
Will received his PhD in Computer Science from Queen Mary University of London in 2019, after which, he spent 2.5 years as a postdoctoral researcher in Machine Learning at Aalto University, Finland. His research interests lie at the intersection of machine learning and signal processing, with a focus on statistical inference for spatio and spectro-temporal data using Gaussian processes.
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 ten years. His current research interests include statistical machine learning, Bayesian nonparametrics, 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).
Poster
AABI_Poster
