Khadija Iddrisu at the Deep Learning Indaba Conference

Strengthen African AI: Khadija Iddrisu at the Deep Learning Indaba Conference 2023

Submitted on Friday, 22/09/2023

Khadija Iddrisu is a PhD candidate in the Insight SFI Research Centre for Data Analytics at DCU and we are extremely grateful to Khadija for sharing her personal experience and learnings from participating in the recent Deep Learning Indaba Conference 2023 that took place in Accra, Ghana in September.


The Deep Learning Indaba Conference is the largest Machine Learning/Artificial Intelligence Conference in Africa. In 2022, I had the privilege of being chosen as the representative for Ghana. This was the first Indaba I had ever attended, and it was an experience that proved to be profoundly distinctive and enlightening. One aspect that left a positive impression on me was the remarkable journeys undertaken by the keynote speakers, their narratives served as a source of inspiration, shedding light on the challenges of their career paths and this was a revelatory experience that broadened my perspective on the possibilities of AI in Africa.

Additionally, the Indaba afforded me the invaluable opportunity to immerse myself in the research endeavours of students hailing from diverse corners of the African continent. This exposure to a wide range of research projects constituted a significant point of learning and enrichment. I enthusiastically embraced the opportunity when I was invited by the Organizers to pitch for the next conference to be held in Ghana. I provided firsthand information on locations and what was to be expected and fortunately, our pitch was successful and the 2023 conference was held at the University of Ghana from the 3rd to 8th of September.

The 2023 conference admitted approximately 800 students, academics, and industry professionals representing 36 African countries. Under the guidance of my supervisors (Professors Suzanne Little and Noel O’Connor) and I presented a poster at the African Research Showcase Day held during the Conference. The content for the poster originated from the tasks I have been working on during the early stages of my PhD program and centered around the topic of “Driver Distraction Estimation with Event Cameras.” It aimed to introduce the concept of event-based vision within the field of computer vision, offering a clear distinction between traditional frame-based cameras and event-based cameras. Furthermore, we outlined some of the challenges associated with the utilization of event cameras, including the lack of adequate event-based datasets and the complexities involved in leveraging this data with deep learning architectures. In light of these challenges, we highlighted a method for generating synthetic event data using event simulators. Additionally, drawing from a paper that I am currently working on replicating, we demonstrated the inference of driver distraction through the detection of facial expressions and eye blinks.

The conference also included a series of workshops that proved highly advantageous for attendees, catering to both newcomers and seasoned researchers in the field of Machine Learning (ML). Notably, among these workshops were the Data Science for Health, Machine Learning for Biology, Trustworthy AI, and the Weakly Supervised Computer Vision Workshop. These workshops provided valuable opportunities for participants to engage in practical, hands-on learning experiences. During this year’s conference, I had the privilege of delivering a 3-minute spotlight presentation and showcasing a poster during the full-day workshop. This served as a remarkable platform to disseminate my research findings and engage with fellow participants, further enhancing the depth of my academic experience at the conference.

I also had the privilege of participating in a panel discussion focused on fostering diversity and inclusivity, with the aim of ensuring the sustainability of Machine Learning communities. During this panel session, I had the opportunity to discuss the initiatives of the Women in Machine Learning and Data Science Accra Chapter, an organization that I co-organize. As part of a dedicated team of four individuals, our primary objective is to orchestrate events that actively promote the participation of women and gender minorities in the fields of Machine Learning and Data Science. One particularly rewarding achievement for us has been the organization of a panel discussion addressing the opportunities and challenges encountered by under-represented groups, which took place at the commencement of the conference. This panel discussion was followed by a networking social event, supported by funding from OpenAI and the Tony Blair Institute for Global Change. It was an honor for me to represent our team on this panel, where I had the opportunity to share our journey and encourage other women to join our cause. Our work is aimed at creating a more inclusive and diverse ML community, and we believe that by sharing our experiences and successes, we can inspire others to become active participants in this important endeavor.


While attending the conference I also received an invitation from the Project Manager at Google Accra to visit their Google Office to attend a day dedicated to research activities, featuring enlightening talks and demonstrations presented by the AI/ML Team of the Accra Research Centre. The research event encompassed diverse areas of research interest, including but not limited to flood and disaster prediction, weather forecasting, and the exploration of public datasets accessible to the general public.

I was also invited to the launch event of the Google Research Women in EMEA program. This event boasted a lineup that included a fireside chat with Jeff Dean, a panel discussion delving into opportunities for women in the technology sector, and a session dedicated to lightning talks. I had the privilege of giving a lightning talk on my own research during this session. I derived substantial knowledge from the wide spectrum of research endeavors pursued by the Google Accra Research Centre team, and I established valuable connections within the research community. This visit also provided me with the opportunity to engage with research scientists at Google, from whom I gleaned invaluable insights into the nuances of navigating a successful research career. Prior to this engagement, I had also received an invitation to the Google DeepMind social event: “The Many Paths to a Career in AI.” This event featured a fireside chat with two early career researchers who now hold positions as Directors at Google DeepMind. They graciously shared their individual journeys to their current roles at Google DeepMind, providing an enriching perspective on the various avenues to building a career in artificial intelligence.

The Deep Learning Indaba Conference was an intense week of learning, research, exchange and ideation and I am glad for the opportunity to participate in sharing knowledge from a fairly new area of research during the poster presentation. I am also most grateful for the opportunity to learn from experts and beginners including keynote speakers and for the opportunity to engage in debates surrounding the state of AI in Africa and how we can use this knowledge to develop our nations and the world at large. As said by the late President of Ghana, Dr Kwame Nkrumah “We Face Forward” and as such I am looking forward to the great things and innovations that will arise from the knowledge and network gained from this conference. I would like to express my heartfelt gratitude and appreciation to Insight SFI Research Centre for Data Analytics and Xperi for generously funding my travel and allowing me time away from my PhD studies to attend this exceptional conference.