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Technology matters most where it speaks to the context in which it is
built. This year wasn’t just about smarter algorithms - it was about the
people asking better questions. Before we move forward, here’s a look at
the work that defined our year.
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Early this year a team from DSAIL and
the Institute of Geomatics, GIS &
Remote Sensing (IGGReS) collected data
in Kieni Forest in February focusing
on tree attributes and forest dynamics
with drone technology. This
collaboration captured high-resolution
images and tree data, essential for
advancing forest ecology,
conservation, and sustainable resource
management.
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The data collection offered a
thrilling opportunity to engage with
nature and contribute to scientific
research. Insights gained resulted in
the release of the
Miti360 dataset,
which is an integrated,
machine-learning ready dataset for
individual-tree and stand-level
reforestation monitoring that fuses
high-resolution drone orthophotos,
terrestrial stereo and single images,
precise ground measurements (tree
height, crown diameter, basal diameter
and GPS locations), species labels,
and multi-year weather time series for
nearby stations.
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The collection is designed to support
detection, segmentation, species
classification, and biophysical
parameter estimation (e.g., crown
diameter, height, biomass proxies),
and to enable linking short-term
growth dynamics to weather. Data is
provided in standard GIS and ML
formats (GeoTIFF, JPEG, JSON, SHP,
time-series API) for immediate
integration into research and
operational pipelines.
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Team work makes the dream work. This year we welcomed
new team members including Mary Kariuki, Leonard
Sanya, Samuel Mbugua, Emason Mutuma, Austin Kaburia
and Braxton Mandara. Their contributions have
strengthened our research efforts and with their
addition, DSAIL continues to grow driving forward ML
and AI research.
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This year’s publications featured our research,
insights and evidence that underpin our work. Have a
read:
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On 13th and 14th November we had remarkable Research
Days where we appreciated the ongoing research work at
DSAIL. On the first day our conversations revolved
around the various approaches we employ to solve real
world problems. To spice things up, we were thrilled
to welcome some fantastic guests! — Dr. Sekou L. Remy,
Antony M. Gitau and Ussen Kimanuka from Google
Research Africa, Clinton Oduor and Jackline Tum from
Amini AI, Gabriel Kiarie from NATURAL STATE and
Stephen Githinji from Institute of Design and
Innovation (IDI Africa).
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For the second day we took things a notch higher by
going for a game drive to appreciate the biodiversity
that is in our ecosystem. We visited the Aberdare
National Park in Nyeri where we had the opportunity to
view elephants, waterbucks, colobus monkeys among
other animals in their natural habitat. This made us
appreciate the role various animals play in the
robustness of the ecosystem.
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Machine Learning Foundations Course
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September marked the completion of an
intensive Machine Learning Foundations
course led by Prof. Neil Lawrence.
Over four weeks, participants from
DSAIL met three times per week to
build a strong understanding of
machine learning fundamentals,
advancing from theoretical concepts to
practical implementation and a final
mini-hackathon.
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Throughout the program, participants
demonstrated collaboration and
dedication, informally referring to
themselves as the “Machine Learning
Football Club (MLFC)” to reflect the
team spirit. The course fostered both
technical competence and a supportive
learning environment.
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With the training concluded,
participants are now prepared to apply
their skills in data science, machine
learning, and artificial intelligence
to address real-world challenges. We
extend our sincere congratulations to
all participants and express our
appreciation to the instructional team
for their commitment and guidance.
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All materials and winning projects are
available online. Please visit to
check out the season’s
highlights:
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View
the
Winning
Projects
here.
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Access
the
Lectures
here.
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Review
the
Practicals
here.
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Google PhD fellowships 2025
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Our Junior Research Fellow, Lorna Mugambi, was named a
recipient of the prestigious 2025 Global
Google PhD Fellowship
in Health Research!
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Lorna is a doctoral student in the Department of
Electrical and Electronic Engineering at Dedan Kimathi
University of Technology, supervised by Professor
Ciira wa Maina.
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Lorna's research, conducted in collaboration with
paediatric cardiologist Professor Liesl Zühlke,
focuses on addressing the burden of Rheumatic Heart
Disease (RHD) in Africa. Her work uses advanced AI
techniques, including Vision-Language Models (VLMs)
and Self-Supervised Learning (SSL), to develop
scalable, low-cost diagnostic tools for RHD.
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These fellowships recognize outstanding graduate
students who are conducting exceptional and innovative
research in computer science and related fields, with
a focus on influencing the future of technology.
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This program provides vital direct financial support
for Lorna’s PhD pursuits and connects her with a
dedicated Google Research Mentor, reinforcing Google’s
commitment to nurturing the academic community.
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We are incredibly proud of Lorna's achievement and
look forward to the continued success and impact of
her research.
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We had the opportunity to participate in a number of
events this year which allowed us to interact with
fellow researchers and share our work to wider
audiences. The events included:
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African-Next-Voices
Data Collection
Workshop
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DSAIL AI in Health
Workshop
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Open Hardware Summit
2025
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These events encouraged us to push new frontiers in
research and rejuvenated us on where to put our energy
in as far as research is concerned. 2026 can only get
better.
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You’ve made it this far. Check out
our major wins in our
2025 Wrapped.
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Thank you to Our Sponsors
Huge thanks to our sponsors for providing the
resources that steer our research work forward.
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Dedan Kimathi University of Technology - Nyeri, Kenya
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Subscribe to our newsletter
here
to stay updated on what we do.
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