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[Last updated: 16-03-2025 at 15:02 pm]

About Me

I apply quantitative methods — including machine learning, biostatistics, and epidemiological modeling to study the emergence and spread of infectious diseases. I’m driven by curiosity about how data can help us understand/predict outbreaks and improve public health response.

Education

  • 2022 - MS in Artificial Intelligence and Data Analytics from the Institute of Digital Technologies at Loughborough University London.
  • 2019 - BS (Hons) in Computer Science from University of Jos, Nigeria.

Work Experience

I am currently a Research fellow at the West African Center for Emerging Infectious Diseases (WAC-EID) I am learning and contributing to research efforts in strengthening health systems and improving infectious disease control strategies in Nigeria (Particularly Lassa Fever, I'm investigating how viral evolution, rodent population dynamics, and environmental variability influence spillover and outbreak risk). The broader goal is to understand the dynamics of emerging infectious diseases and how to better prevent/respond to them.

Previously, I served as a Machine Learning Engineer at Greysoft Technologies, Nigeria, where I led the ML engineering/softwre engineering team to build AgroBays Agrofoods and 5Minutes I have also contributed to a number of research initiatives, including projects funded by EV, New Venture Fund through Data.org and Microsoft, the Embassy of France in Nigeria's Solidarity Fund for Innovative Projects, and the NIH-supported K43 project (K43TW011416) at JUTH.
Thanks a lot to the support of my advisors and my sponsors, I am able to conduct research and continue learning/building things that interest me.

Research Interests

I’m building a career at the intersection of biostatistics, epidemiology, and machine learning, with a focus on improving how we model, detect, and respond to infectious disease outbreaks. My work explores how Bayesian modeling, uncertainty quantification, and simulation-based inference can make epidemic forecasting more accurate, interpretable, and actionable for real-world decision-making. I care deeply about open and reproducible science and ensuring that the benefits of these methods/tools reach the people and places most at risk.

Recent News

  • [Jul. 2025] Our abstract was accepted for presentation at the ECOWAS Lassa Fever International Conference in Abidjan.
  • [Jul. 2025] Our paper was accepted at the BraTS 2025 Lighthouse Challenge, MICCAI'25 in Daejeon, South Korea
  • [Jun. 2025] I will attend the Data Science Africa 2025 (Summer School & Workshop) at the University of Ibadan, Nigeria.
  • [Apr. 2025] I hosted my first Spring ACX Everywhere Meetup in Jos. You can find more details and RSVP on the event page on LessWrong
  • [Mar. 2025] I’ll be joining UTMB Health, as a Research Fellow starting Fall'25.
  • [Dec. 2023] I participated in the 3rd Annual ML4H Symposium organized by the Association for Health Learning and Inference.
  • [Aug. 2023] I delivered a keynote on AI Governance and Safety in Nigeria at a Pie and AI Co-hosted by deeplearning.AI and Greysoft Technologies.
  • [Dec. 2022] I earned my MSc in AI and Data Analytics from Loughborough University London.
  • [Jul. 2020] I presented my undergraduate poster on cervical cancer at the 21st ACM Conference on Economics and Computation (EC 2020) in Budapest. link to poster
  • [Nov. 2018] I led Team Golden Halo to a 1st Runners-Up finish at the 2018 NASA Space Apps Challenge (Nigeria Online Round). See challenge.

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Profession Membership

I am a member of ACM Special Interest Group (SIGecom) on Economics and Computation , Effective Altruism Network (EA Nigeria & EA Global). I am also affiliated with Black in AI and Data Scientists Network formerly, Data Science Nigeria.

Misc

  1. A quote that has stayed with me all through life and work is "There is no passion to be found playing small - in settling for a life that is less than the one you are capable of living." by Nelson Mandela
  2. Here are few person that I am most inspired by (in no particular order): Scott Alexander, Tyler Cowen, Paul Graham, Naval Ravikant, and Gwern.

    I appreciate you taking the time to read this. Feel free to AMA or share feedback here

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