Tell us about your background.
My background is in Data Science and Machine Learning. I graduated with a BSc. Applied Statistics with Computing. I am now pursuing an MSc. in Data Science at the African Center of Excellence in Data Science at the University of Rwanda. My thesis research is focused on transfer learning for classification of bean plant leaf diseases in precision agriculture. I am advised by Dr. Weiwei Pan, Data Science Graduate Program Advisor at Harvard University and Dr. Melanie Fernandez Pradier, Senior Researcher at Microsoft Research.
What are you currently working on?
At MARI, I am currently working on Big Data analytics and Natural Language Processing research – Language Modeling and Automatic Speech Recognition for African languages. I am currently interested in Machine Learning, Natural Language Processing, and Computer Vision and their applications to improve productivity in three broad areas: the Future of Work, Health, and Society. Prior to joining MARI, I was a Research Intern at Harvard University.
I am also a member of Masakhane, a grassroot NLP community for Africa by Africans, working on NLP – Machine Translation for African languages. I have collaborated with the team and worked on two projects: Participatory Translations of Oshiwambo: Towards Sustainable Culture Preservation with Language Technology | OpenReview and [2205.02022] A Few Thousand Translations Go a Long Way! Leveraging Pre-trained Models for African News Translation (arxiv.org)
How did you get interested in data science?
I love making sense out of data. I was interested in how to advance my skills to help me use data to solve real-life problems. With my skills in Statistics and Mathematics, I jumped into Data Science and now, I can leverage tools like ML, NLP, and AI to design impactful solutions to challenging real-life problems using data.
How did you first discover WiDS?
I discovered WiDS when I joined MARI. My director at MARI, Dr. Jacki O’Neill who is a phenomenal woman in tech and strongly supports women in tech, introduced me to WiDS and motivated me to represent MARI in promoting WiDS in Kenya and Africa. I love youth empowerment especially mentoring girls and so I was excited to take part in promoting women in data science in Kenya and Africa.
Have you been involved with WiDS since that first experience? If so, in what way?
I and my fellow WiDS co-ambassadors – Sonal Henson, Philomena Mbura, Teresia Muiruri and Carol Muchemi hosted the WiDS Kenya Datathon and WiDS Kenya Conference for the first time this year.
Tell us about the WiDS Datathon workshops in Kenya.
The WiDS Kenya ambassadors held a datathon workshop series for the first time on three Saturdays in January 2022. About 30 participants registered for the datathon competition. In the first workshop on January 15, we onboarded participants into the WiDS Datathon challenge: Using Data Science to Mitigate the Effects of Climate Change. In the second workshop on January 22, we had a training by Manal Jalloul, an instructor from the NVIDIA Deep Learning Institute on the Fundamentals of accelerated Data Science. Finally on January 29, we had our last workshop which was a talk by Wei Xiao, Director of Developer Relations, Cross Geo from NVIDIA on AI for Climate Change.
“It was a pleasure to host the WiDS Kenya Datathon for the first time in 2022. I personally learned a lot in terms of team/community building. I am grateful to NVIDIA for facilitating our workshops and most importantly, to WiDS Stanford for giving us a platform to inspire, support and educate our participants in applying data science to impactful real-life problems through hands-on practical experience.” – Millicent Ochieng, Data and Applied Scientist, Microsoft Africa Research Institute.
How has WiDS made an impact on your life and/or work?
I am super excited to be part of WiDS as an ambassador. WiDS has given me opportunity to build a community of talented women in data science in my region – Kenya. It is a platform where women can support one another as they keep thriving in the field of data science. Seeing fellow women succeeding in this field is my true success as a WiDS ambassador. This has been an interesting journey with immense support from being a part of both the WiDS Datathon and Conference organizing teams.
What comes next for you? And what are your hopes for women in the data science in the future?
I hope to build a strong community of female data scientists in my region, where these talented women can share knowledge and support one another. I plan to reach out to more women by hosting both WiDS Kenya Datathon Workshop and Conference every year to keep inspiring and educating data scientists in my Kenya.