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Finding Valdo with Deep Learning & Reaching UN's Sustainability Goals with DS

Meet Up
Finding Valdo
Monday, November 21, 2022, 6:30 pm – 8:30 pm

We can't wait to see you at CEU on Monday, 21 Nov!

  • Thomas Niedermayer is going to talk about how to find Valdo using Neural Networks.
  • Elisa Omidei is going to talk about how data science can help reach UN's Sustainable Development Goals.
  • After the talks, as always, comes the favorite part of many: grabbing a snack and getting to know each other!

🎤🎤 Open Mic
We are going to open up the stage after the talks for community announcements. If you'd like to announce something, open this slide deck, make sure you are signed in with a google account, and click "View Only" -> "Request Edit Access". Explain in the text box what you want to announce, and we'll give you edit access to the slide deck.
🎤🎤

Finding Waldo with permutational equivariance
Thomas Niedermayer, Data Science Student - LinkedIn

We will introduce the computer vision problem of the most recent Lumos datathon, showcase the winning submission, and explain the concept of permutational equivariance to improve the learning of neural networks for input data in the form of sets.

Leo and Thomas are TU Data Science students with a CS and math background, respectively. They are part of a student organization specializing in Data Science called Lumos.

Data science for the Sustainable Development Goals: Opportunities & Challenges
Elisa Omodei, Assistant Professor, Department of Network and Data Science, CEU - LinkedIn

In a rapidly changing world, facing an increasing number of socioeconomic, health and environmental crises, data science can help us quantify vulnerabilities and monitor progress toward achieving the UN Sustainable Development Goals. In this talk, I will provide a non-exhaustive overview of the main areas of applications where data-driven computational methods have shown their potential for social impact, and I will then deep-dive more specifically into my work on predicting food insecurity from conflict, weather, and economic data.

I am an Assistant Professor at the Department of Network and Data Science of the Central European University, in Vienna, Austria. Previously, I worked at the United Nations, first at UNICEF's Office of Innovation in New York and then at the UN World Food Programme in Rome. In my research, I explore how complexity and data science can help us address the needs of the most vulnerable populations and monitor and achieve the UN Sustainable Development Goals.

Please REGISTER your interest in attending through the registration link in the upper-right corner. 

 

Attention attendees with food allergies. Please be aware that the food and drinks provided may contain or come into contact with common allergens, such as dairy, eggs, wheat, soybeans, tree nuts, peanuts, fish, shellfish, or wheat.