I like to think of myself as a wearer of many professional hats. I am probably best described professionally by others as a computational decision scientist, researcher, an engineer and tech entrepreneur/founder.
I am lucky to have been trained by some of the world’s leading educational institutions - I obtained a PhD from Stanford - specializing in AI and sustainability and prior to that, dual masters degrees from MIT in Computer Science (AI) as well as in Technology Policy. I was also educated as an electrical engineer at the University of Ibadan in Nigeria.
Although I tend to keep a low profile, I finally decided to create this site as (i) a professional summary site like everyone seems to have these days, and perhaps more importantly, (ii) as an avenue to write my perspective and thoughts on a myriad of professional and social issues, with the hope that they may be of help to others navigating similar paths.
New Project
2024 –
Pastel (Co-founder, Data Scientist, CTO, CPO)
2021 – 2023
I co-founded Pastel to bring the power of technology to underserved businesses around the world. It is no secret that much of the world still falls behind in the use of technology to solve pain points in contrast to the United States. I think businesses even more than governments power the economies especially in Africa because when governments fail as is unfortunately common in the developing world, it is businesses, whether micro, small or enterprise in scale, on which the burden falls to keep the economy going. With Pastel, I was able to accomplish some really important things while also gaining some tremendous founder skills and lessons. They include:
Conceptualizing and leading the engineering and product development of an Enterprise AI SaaS platform, Sigma, for large banks, FinTechs in Africa. This flagship solution - one of a kind on the continent - was able to provide (1) real-time, AI-enabled, automated credit risk assessment & decisioning engine, (2) comprehensive, real-time AI transaction and customer risk monitoring and decisioning engine.
Leading the engineering and product development of multiple SaaS solutions leveraging AI to support critical small business operations such as invoicing, bookkeeping, payments and credit card-based financing. Cumulatively, the solutions have been used by 200,000+ small businesses/small business owners in over 40 countries.
Stanford (PhD)
2019 – 2023
Recently completed a PhD at Stanford in AI for Sustainability decision-making.
I could not have wished for a better opportunity to work on two things that I have spent over a decade obsessing on: Artificial Intelligence and Sustainability/Climate Change. Why study one when you can study both?
On the climate change side (the domain), I examined important decision-making questions related to large-scale decarbonization transportation (think EVs) and how organizations do their carbon accounting and emissions management strategy (think “net-zero” claims).
On the AI side (the methodological tools), my focus was on building advanced information extraction methods on alternative data sources (think geospatial computer vision on aerial imagery and LLMs for named entity recognition from text) and autonomous decision support systems (think classic ML and reinforcement learning).
The intersection of the above falls into computational decision-making under uncertainty so I spent a lot of time thinking about this interdisciplinary concept (think probability & statistics, economics, psychology, management and finance).
Super grateful to the Knight-Hennessy Scholars program who made that possible, not just via generous financial support, but also by providing a uniquely impactful leadership education and community.
MIT
2016–2018
University of Ibadan
I am motivated by a lot of pain points in the world and currently working on a very ambitious new project to address them. Watch out.
Spent two years here receiving some of the most transformative education of my life. Completed advanced research and coursework in machine learning, economics, technology policy, sustainable energy systems. Lots of traveling and experiential learning as part of the REM team (also described here).
S. M. Electrical Engineering and Computer Science.
S. M Technology and Policy.
Thesis: Network Partitioning Algorithms for Electricity Consumer Clustering.
Grateful for the MIT Tata Fellowship which funded my studies there.
My first training as an engineer. Started out as a traditional electrical engineering student, focusing embedded systems design (think microcontrollers, robots and electronic devices), being heavily involved with the IEEE and Engineers Without Borders. Then I became more focused on learning and applying computational intelligence ideas in the last couple years of undergrad. I joined the IEEE Computational Intelligence Society as an undergrad and began early forays into machine learning. Lots of edx and Coursera MOOCs. Mentorship on Evolutionary Algorithms by Chukwuka Monyei. Ultimately ended up undertaking my senior year thesis research project applying AI (in particular, what used to be then called “soft computing” techniques) to facilitate the transition towards sustainable and affordable residential energy systems in Nigeria.
B.Sc. Electrical and Electronic Engineering.
Thesis: Residential energy management with demand response functionalities in a smart grid environment.