As practising Data Science researchers and practitioners, the COVID-19 pandemic has highlighed both the need for data driven decision making and the reality of what it really takes to get to that point. It is not only about throwing data + model at a problem. It is about understanding the environment that one is in and then strategising on what might best work for that environment. In this talk I look back at some of the work we have done within responding to different challenges within both Data Science and Natural Language Processing. I place at the center people and how they are the important piece in our practice.

---

Youtube Live: Link

Vukosi Marivate holds a PhD in Computer Science (Rutgers University, as Fulbright Science and Technology Fellow) and MSc & BSc in Electrical Engineering (Wits University). Dr Marivate is based at the University of Pretoria as the UP ABSA Chair of Data Science. He works on developing Machine Learning/Artificial Intelligence methods to extract insights from data. A large part of his work over the last few years has been in the intersection of Machine Learning and Natural Language Processing (NLP). This has led to research outputs focused on how we can better improve low resource language tools, especially for African Languages. This has included creating new software libraries, new research approaches for robust NLP and encouraging the development of datasets for African languages. As part of his vision for the ABSA Data Science chair, Vukosi is interested in Data Science for Social Impact (https://dsfsi.github.io/), using local challenges as a springboard for research. In this area, Vukosi has worked on projects in science, energy, public safety and utilities. Vukosi is cofounder of the Deep Learning Indaba, the largest Machine Learning/Artificial Intelligence workshop on the African continent, aiming to strengthen African Machine Learning.