Data Science for Development and Poverty Mapping: Opportunities & Challenges

Agenda:

6:00pm - 6:30pm:- Pizza, Drink and Socialize.

6:30pm - 7:20pm:- Presentation, Question & Answer.

7:20pm - 8:00pm:- Discussions, Project Ideas for Community and Networking.

Abstract:

Due to the proliferation of digital data in developing economies, there is a paradigm shift from using traditional methods to using data-intensive methods for solving some of humanity's grand challenges. We will talk about how researchers are leveraging on the data science revolution to solve problems in low resource countries - from using satellite imagery and deep learning to predict poverty to using mobile money data to create disruptive financial technologies. We'll end the talk with conceptual machine learning theories and real world applications.

Speaker Bio:

Wale Akinfaderin (https://www.linkedin.com/in/waleakinfaderin/) is a Physics PhD Candidate at Florida State University. He spent the summer of 2016 building veracity model with machine learning and natural language processing for international development at IBM Research.