About Dr Temitope Odedeyi
My research has evolved from high-frequency RF, microwave and photonic systems to intelligent sensing, IoT and AI for sustainable agriculture and resilient food systems.
I am a Royal Academy of Engineering Research Fellow in the Department of Electronic and Electrical Engineering at UCL. The instincts I built designing amplifiers above 200 GHz now go into low-cost sensors, field networks and crop models that work for farmers and processors in sub-Saharan Africa.
Then
Now
From ultra-wideband circuits to crop sensing, in seven steps.
Olabisi Onabanjo University, Nigeria, graduating in the top 2% of engineering undergraduates.
The Presidential Scholarship Scheme for Innovation and Development (PRESSID) funded my MSc and PhD at UCL. I finished the MSc in Telecommunication with Business with a Distinction, first in class.
At UCL I developed distributed amplifier architectures with world-record bandwidth, reaching beyond 200 GHz, and designed MMICs in InP and SiGe as a visiting researcher at Chalmers University of Technology in Sweden (pictured at the top of this page). A short visit to the University of Ljubljana added microwave filters for optoelectronic oscillators.
My team won the UCL and Rothamsted Research Agricultural Technology Hackathon with an idea for judging crop quality from its electrical properties. The £10k award paid for the first prototypes.
As lead author of a £100k UCL GCRF proposal, I became lead researcher on ASPIRE, designing an RF instrument to estimate starch in cassava roots. I took it to the International Institute of Tropical Agriculture (IITA) in Ibadan and led the first trials in West Africa.
As a postdoc on the EPSRC PhotoDAC project I built a high-speed 8-channel receiver for photonic digital-to-analogue conversion. Alongside it, ASPIRE won UCL Business proof-of-concept funding, we trained farmers to use the sensor, and I helped write the €5.25M Horizon Europe NESTLER proposal.
The Royal Academy of Engineering's Engineering for Development Research Fellowship (£625k) funds THRIVE: IoT field sensing, crop models and RF quality sensors working together across the cassava value chain, with partners in Nigeria, Ghana and Japan. Since then, grants from Huawei (ACCORD) and the Japan Prize Foundation have added AI-driven deployment of new crop varieties and cassava genetic diversity to the work.
Three questions that run through the grants, papers and students.
Can a cheap RF probe tell you what is inside a cassava root, or a bottle of olive oil?
RF reflectometry and impedance sensing to estimate starch and dry matter, corrected for temperature and sharpened with machine learning, now extended to food adulteration.
What is happening in the field, plant by plant, as the season unfolds?
IoT environmental stations, plant-level and leaf sensors, and drone and satellite observation feeding one data platform.
How much will this field yield, and what would raise it?
Crop growth and yield models that combine field sensing with downscaled climate data, plus tools to make cassava genetic diversity usable by breeders.
Research carried out with partners in six countries.
I welcome enquiries from prospective PhD students interested in RF sensing, IoT or machine learning for agriculture. Get in touch with a short outline of your interests. Full supervision details are in the PDF CV.
Six to start with. The full list is below and on Google Scholar.
The full academic CVAppointments, funding, supervision, teaching, service and complete publication list.
Download CV (PDF)