Timezone: »

Machine Learning for the Developing World (ML4D): Global Challenges
Paula Rodriguez Diaz · Konstantin Klemmer · Sally Simone Fobi · Oluwafemi Azeez · Niveditha Kalavakonda · Aya Salama · Tejumade Afonja

Tue Dec 14 06:00 AM -- 01:40 PM (PST) @
Event URL: https://ml4d.notion.site/ml4d/Machine-Learning-for-the-Developing-World-ML4D-2021-548251eab3df4517819c4742c2e5c853 »

While some nations are regaining normality after almost a year and a half since the COVID-19 pandemic struck as a global challenge –schools are reopening, face mask mandates are being dropped, economies are recovering, etc ... –, other nations, especially developing ones, are amid their most critical scenarios in terms of health, economy, and education. Although this ongoing pandemic has been a global challenge, it has had local consequences and necessities in developing regions that are not necessarily shared globally. This situation makes us question how global challenges such as access to vaccines, good internet connectivity, sanitation, water, as well as poverty, climate change, environmental degradation, amongst others, have had and will have local consequences in developing nations, and how machine learning approaches can assist in designing solutions that take into account these local characteristics.

Past iterations of the ML4D workshop have explored: the development of smart solutions for intractable problems, the challenges and risks that arise when deploying machine learning models in developing regions, and building machine learning models with improved resilience. This year, we call on our community to identify and understand the particular challenges and consequences that global issues may result in developing regions while proposing machine learning-based solutions for tackling them.

Additionally, as part of COVID-19's global and local consequences, we will dedicate part of the workshop to understand the challenges in machine learning research in developing regions since the pandemic started. We aim to support and incentivize ML4D research while considering current challenges by including new sections such as a guidance and mentorship session for project proposals and a round table session focused on understanding the constraints faced by researchers in our community.

Author Information

Paula Rodriguez Diaz (Harvard University (SEAS))
Konstantin Klemmer (University of Warwick, The Alan Turing Institute)
Sally Simone Fobi (Columbia University)
Oluwafemi Azeez (Borealis AI)
Niveditha Kalavakonda (University of Washington)
Aya Salama (Aigorithm Tech)
Tejumade Afonja (Saarland University)

Tejumade Afonja is a Graduate Student at Saarland University studying Computer Science. Previously, she worked as an AI Software Engineer at InstaDeep Nigeria. She holds a B.Tech in Mechanical Engineering from Ladoke Akintola University of Technology (2015). She’s currently a remote research intern at Vector Institute where she is conducting research in the areas of privacy, security, and machine learning. Tejumade is the co-founder of AI Saturdays Lagos, an AI community in Lagos, Nigeria focused on conducting research and teaching machine learning related subjects to Nigerian youths. Tejumade is one of the 2020 Google EMEA Women Techmakers Scholar. Tejumade was a co-organizer for ML4D 2019 NeurIPS workshop and she is serving as the lead organizer this year. She is affiliated with several other workshops like BIA, WIML, ICLR, Deep Learning Indaba, AI4D, and DSA where she occasionally serves as a volunteer or mentor.

More from the Same Authors