DSAIL-DeKUT

Ecosystem monitoring provides insights on ecosystem health. In this demo, we perform edge inferencing on bird sounds using locally developed technology at our lab. 🐦 Low-cost 🐦 Deployed on edge youtu.be/c_mkZYxLGPw?si…

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Your future starts here! Welcome to the Premier University of Technology, where innovation isn’t just taught, it’s lived. At DeKUT, we are committed to delivering quality education while nurturing holistic development of our students.

The HASH Project just opened the AI for Reproductive Health in Africa Innovation Challenge. Build AI tools for early pregnancy loss care or contraceptive decision-making. Win USD 1,350 + a trip to @dsa_Uganda 2026 in Kampala. Who should apply? Teams of 3–6 members, including: 🔹 At least 1 health professional 🔹 At least 1 data scientist/developer 🔹 At least 2 women 🔹 Residents or citizens of Sub-Saharan Africa Lusophone & Francophone applicants in Sub-Saharan Africa are especially encouraged to apply. Deadline: 3 May → bit.ly/4clmKEG Who in your network should be applying?

The DSA 2026 Workshop in Kampala will bring together researchers and practitioners working at the intersection of data science, machine learning, and AI. Join the conversation. Register for attendence: forms.gle/DBCgbqC8gnazo8… #DSAKampala2026

Access the dataset here👇 miti360.github.io

We could not afford to watch on the sidelines. We developed Miti360, a machine learning ready dataset to help researchers and conservationists monitor forests effectively. youtu.be/jfyqgnW68dA?si…

As AI takes shape in different sectors, Africa's forests face a critical threat: a massive data gap. Most ML models on forestry are trained on data from the global north, making them ill-suited to understand Africa's unique and complex forests. Here's what we did ... 🧵

From raw field data to a machine learning ready dataset, that's Miti360😎 youtu.be/jfyqgnW68dA?si…

Breaking into data science and AI can feel overwhelming. For many aspiring African data scientists, the path isn’t always clear. So where do you start; and how do you grow? The 2026 DSA Summer School & Workshop will be at @Makerere (July 20–24). What stage are you in? 👇🏾

Subscribe to our YT channel🔔 Dropping something cool soon!😎 @dekut-dsail?si=0NaSYc8aF5KQTbqD" target="_blank" rel="nofollow noopener">youtube.com/@dekut-dsail?s…

AI is rapidly shaping industries across Africa; But as adoption grows, an important question remains: What does responsible AI look like in the African context? Discuss in the comments👇 #DSAKampala2026 | #ResponsibleAI

AI is transforming healthcare across Africa, improving diagnosis and access. VentraScan, developed at @PEL_makerere, is helping enable faster TB detection. How do we scale this responsibly across communities? 👇🏾 More about Ventrascan: ventrascan.org #AIinHealthcare

Applications for the global Google PhD Fellowship Program are open! Fellowships directly support graduate students doing exceptional and innovative research in computer science and related fields as they pursue their PhD. Learn more and apply by April 30 at goo.gle/phdfellowship.

The NeurIPS 2026 submission site opening has been moved to April 15th. Note that all tracks (Main Submission, Evaluations & Datasets, and Position Papers) share the same dates. The final submission deadlines remain unchanged: • Paper Abstracts: May 4th (AOE) • Full Papers: May 6th (AOE)

It’s not a straight shot to the far side of the Moon! 🌕 Over approximately 10 days, the Artemis II astronauts will orbit Earth twice before looping around the far side of the Moon in a figure eight and returning home.

🌞🌕🧑‍🚀 Right now, the Orion capsule is passing behind the Moon, so the Sun is entirely eclipsed from their perspective. During this time, they will view a mostly darkened Moon and will use the opportunity to analyze the solar corona.

A simple way to think about AI agents: LLM = reasoning Tools = actions Memory = context Agents combine all three.

• Predict changes in tree biophysical parameters and stand volume in relation to prevailing weather conditions. Explore the dataset here 👉 miti360.github.io

With this dataset you can: • Identify and classify species of individual young trees, saplings, and seedlings from high-resolution drone images. • Estimate parameters like crown diameter and tree height from drone or terrestrial imagery to derive biomass estimates.