Imperial College London

Sabbatical Reflections


Staff and students at the African Institute for Mathematical Sciences (AIMS) in Rwanda

Dr Marc Deisenroth, from Imperial’s Machine Learning Initiative, reflects on the four months he spent in Rwanda on sabbatical.

A decision faces every academic who decides to takes a sabbatical: what is the most effective way to spend my long sought-after time? Often a tension emerges: should I spend my time on high-impact career-progressing work, like a long-planned book, or in an international lab with a different research focus, to learn new things, or should I work toward more community development and social impact?

I am a lecturer at Imperial College London, and as part of my sabbatical, I decided to spend four months at the African Institute for Mathematical Sciences (AIMS) in Rwanda, where I taught a course on Foundations of Machine Learning.

Deciding where to go

AIMS is a pan-African institution with centres in South Africa, Cameroon, Senegal, Ghana, Tanzania and Rwanda. It provides a full-time learning environment where students and lecturers stay on campus, and does not charge tuition fees. In fact every student receives a full scholarship, which allows students from all backgrounds to study a masters in mathematical sciences. Students come from across the African continent to study together and to grow a pan-African community of mathematicians.

Beautiful sunset in RwandaI first came across AIMS a few years ago, when I supervised some students’ dissertations at AIMS Senegal, the students’ performance really impressed me. In September 2017, I taught a short course at the Deep Learning Indaba in South Africa, where I experienced a full week of great enthusiasm and excitement about machine learning; that week in Johannesburg left a lasting impression on me, and with a sabbatical coming up in 2018, I decided to spend a few months at an AIMS institution.

Masters in Machine Intelligence

Set up in 2016, AIMS Rwanda now offers two masters courses in Mathematical Sciences and Machine Intelligence. Lecturers teaching the courses come from across the globe, and the small class sizes makes interaction between lecturers and students direct, personal and engaging.

I contacted Prince Osei, the Director of Quantum Leap Africa (a centre of excellence at AIMS Rwanda that catalyses high impact research in data science and smart systems engineering), and we immediately agreed on a syllabus outline and high-level objectives of the course. In August 2018 I began a new chapter in Kigali.

The African Masters in Machine Intelligence (AMMI), launched in October 2018, aims to train a generation of globally connected African machine learning developers and practitioners. The first AMMI cohort comprises 31 students (42% women) from 11 different countries.

Staff and students on the African Masters in Machine Intelligence courseThe degree covers modern machine learning, from the mathematical foundations (linear algebra, calculus, statistics and probability theory) and basic machine learning algorithms, to more advanced topics. These include Gaussian processes, approximate inference, kernel methods, graphical models, advanced optimization and reinforcement learning. However, besides these theoretical topics, the degree has an equal focus on applied topics, such as deep learning, natural language and image processing. Mentors, who are international experts in machine learning, provide guidance and support to the students, helping them to become part of the international machine learning community. AMMI students also give back to their own local communities: each is expected to mentor an undergraduate or high-school student in their respective home country.

Teaching Experience

During my time at AIMS I taught a course on Foundations of Machine Learning, as part of the AMMI degree covering mathematical foundations of machine learning and their application to basic machine learning algorithms, such as linear regression or principal component analysis. The objective of this course was to uncover intrinsic mathematical principles often hidden in machine learning algorithms, to show students how and why these algorithms work and what their underlying assumptions are. The students had strong mathematical backgrounds and were really engaged in class; some of our discussions had a lasting impact on my way of thinking and explaining.

Next Steps

Next year the AMMI degree will be offered to a total of 100 students, and PhD and Research Fellow positions in machine learning will be offered at AIMS Rwanda in 2019.

AMMI is part of a growing machine learning and AI community in Kigali. Other include CMU Africa, University of Rwanda, incubators and start-ups such as K-Lab, and many other activities, such as the regular AI Saturdays and DevFest-2018. A joint application will bring together different local groups for a one-day IndabaX workshop in 2019.

I hope to build on my connection to AMMI by establishing collaborations between AIMS Rwanda and Imperial, via joint project and PhD supervisions, and joint MSc courses. A symmetric exchange of researchers and teachers will benefit both sides.

Getting involved

There are opportunities for interested academics to tutor, lecture, and remotely supervise projects. If you are interested, please contact the corresponding AIMS branch. Travel, accommodation and food are covered, and the Royal Statistical Society has very close ties with AIMS.


I am very grateful to the Royal Statistical Society for their support during this journey. I also thank Imperial for freeing me from my normal teaching and administrative duties during my sabbatical. Finally, I want to express my deepest gratitude to AIMS, Quantum Leap Africa and all students at AIMS for making my stay an unforgettable and unique experience.


Marc Deisenroth

Marc Deisenroth
Department of Computing