We aim to create a community which empowers and encourages the growth and participation of women in the field of Computational Science Research.
This community is for minorities within the field of computational science research which includes but not limited to:
computer science, applied mathematics, computational mathematics/statistics, machine learning, data science/mining, robotics, AI and any other related field.
We are launching this community with a full day event with the theme:
You can’t be what you can’t see!
In this event we aim to inspire women researchers by allowing them close proximity to amazing women in the field and information to help them be well informed on the different options available in research (in Gauteng for the first year).
In particular, we will be:
Short Bio
Dr Jantjies is a technology specialist, researcher and advisor. She holds a PHD in computer science
and has held various strategic positions in the field. Dr Mmaki Jantjies is also an academic at the
University of the Western Cape and a member of the W20 digitization group which is a G20 working group
looking at the effect of technology on human personal in the digital era.
@MmakiJ
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Short Bio
Dr Jantjies is a technology specialist, researcher and advisor. She holds a PHD in computer science
and has held various strategic positions in the field. Dr Mmaki Jantjies is also an academic at the
University of the Western Cape and a member of the W20 digitization group which is a G20 working group
looking at the effect of technology on human personal in the digital era.
@MmakiJ
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Short Bio
Vukosi Marivate holds a PhD in Computer Science (Rutgers University) and MSc & BSc in Electrical Engineering (Wits University). He is based at the University of Pretoria as the ABSA Chair of Data Science. Vukosi 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(due to the abundance of text data and need to extract insights). As part of his vision for the ABSA Data Science chair, Vukosi is interested in Data Science for Social Impact, 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 an organiser of the Deep Learning Indaba, the largest Machine Learning/Artificial Intelligence workshop on the African continent, aiming to strengthen African Machine Learning. He is passionate about developing young talent, supervising MSc and PhD students and mentoring budding Data Scientists.
@vukosi
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Short Bio
Raesetje Sefala is a computer science master's student at Wits university in South Africa. Her research interests include applying machine learning to help solve problems experienced by countries in the developing world. Her master's work is about using satellite images and computer vision to study the effects and evolution of spatial apartheid in South Africa and she is a recipient of the Data Science for Social Good fellowship at the University of Chicago.
@bonjora
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Short Bio
Bio
@Lady_Riri94
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Short Bio
Jade Abbott is a Machine Learning engineer at Retro Rabbit. She's built software for every field from social upliftment to banking, working on projects throughout Africa and considers herself a polyglot. Her current project involves training and deploying deep learning system to perform a variety of NLP tasks for real life systems - from training the models, to scaling them in production. In her free time, she does ML research on Neural Machine Translation for African languages.
@alienelf
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Short Bio
I am a researcher at the Council for Scientific and Industrial Research (CSIR) under Mobile Autonomous Intelligence System division, working on projects related to Machine learning applications for computer vision. I completed a Master's in Big Data Science from the University of Pretoria (2017 - 2019) and BSc Hons in Mathematics from Sefako Makgatho Health Science University (2013-2016). My research interest is on black-box optimisation approaches for machine learning techniques, in order to understand how ML models make decisions.
@windy_seipati
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Short Bio
PhD Candidate in Computer Science. She is interested in e-services, cloud computing, Internet of Things and community development. She has published more than 9 double peer reviewed papers and lectured in various universities in South Africa.
@katli_01
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