Session: AI for Disaster response
When disaster strikes, humanitarian organizations and local communities need to coordinate efforts to bring quick help to affected populations. Two AI in Disaster response case studies will be presented in aiding affected people and frontline relief workers. First is the use of AI to predict the affected population so that humanitarian aid can be expedited and more effective. This solution has the potential to help multiple groups of people dealing with emergencies and can expand to other disaster types. The second use case is devising safe paths to identify the best routes to travel to safety in the aftermath of an earthquake. And allowing rescuers to distribute emergency aid more effectively and identify those still in danger and isolated from escape routes.
- how can you use AI for social impact.
- Combination of Analytics, Machine Learning Models, Natural Lanuage Processing, Streamlit Deployment.
- Designing for human aid, consideration of Relief agencies and the Casualties
As a PO I lead global team of Data Scientists, to build data-driven real-world solutions making a social impact. Creating A.I. solutions for Climate Change, Drug Repurposing, Reducing energy, the effect of the digital divide, PTSD, Material Consumption, and more.
Nishrin has 15+ years of experience Research, Product development and Data Science experience. A believer in using technology for social upliftment and creating positive reinforcement in people's lives. She gives her time to volunteering/mentoring/teaching in her local School community and Data Science organizations WW Code, Women in Big Data, and Women in AI.
She has a Master of Science in Physics, PGP in Machine Learning from University of Texas at Austin and did Ph. D research in Astrophysics.