Talk Title: A pragmatists' guide to machine learning for Earth observation imagery
Abstract: Our planet is constantly changing as a result of ecological and socioeconomic interactions across a variety of spatial and temporal scales. A growing number of Earth observation datasets provide regularly repeated synoptic measurements that enable us to map and understand landscapes as the dynamic systems...
In person and Zoom, register here: https://forms.gle/d4cvu4wA3RLFDjeu5
Talk Title: Using AI to Advance Mobile Digital Health in Resource-Constrained Environments
Abstract: The emergence of ubiquitous mobile computing devices and Artificial Intelligence (AI) algorithms is transforming patient care, hereby making it more scalable and accessible. This is of particular importance in resource-constrained environments (RCEs) where access to healthcare technologies or expertise may be limited. The sensing modalities (e.g., camera/gyroscope) of mobile devices are capable of capturing and storing data that can then be...
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Talk Title: NASA Harvest Africa Program: Advancing the Use of Earth Observations and Machine Learning for Agriculture Monitoring for Food Security in Africa
Abstract: Global food security is predicated on identifying sustainable production...
On zoom, register here: https://mittalsouthasiainstitute.harvard.edu/event/ai-and-social-impact-in-south-asia/
The rise of artificial intelligence technology and the modernization of the South Asia region have occurred in parallel over the past few decades – now, they are growing increasingly interconnected, with wide-ranging impacts and consequences. Join us for this miniseries as we explore how AI technology becomes an integral part of South Asian society and consider the potential opportunities and concerns of its proliferation.
The first panel in this miniseries will explore the social impact of AI in the region. As AI is used to address social, environmental, and economic...
Diverse Swarms are Better Swarms! Swarms permeate our technological, biological, and sociological worlds. In swarms, individual members are limited to sensing or communicating with nearby peers, and no direct group-wide coordination is...
Zoom conference - Register at https://forms.gle/6761am3KA2QxeaxX7
“Using healthcare databases to learn what works when no randomized trials exist” Making clinical decisions among several courses of action requires knowledge about their causal effects. Randomized trials are the preferred method to quantify those causal effects. When randomized trials are not available, causal effects are often estimated from observational data. Therefore, causal inference from observational data can be...
Zoom conference - Register at https://forms.gle/6761am3KA2QxeaxX7
Designing Optimal Voting Rules
A central task in voting is to aggregate the ranked preferences of voters over a set of alternatives (candidates) to select a winning alternative. However, despite centuries of research, the natural question of which voting rule is “best” has remained elusive. A recent approach from computer science offers hope. By proposing a natural quantitative measure of the “efficiency” of a voting rule, called distortion, it allows us to define and seek the most efficient voting rule.