Browsing IDEaS Seminars by Issue Date
Now showing items 1-9 of 9
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Assembly of Big Genomic Data
(Georgia Institute of Technology, 2017-09-15)As genome sequencing technologies continue to facilitate the generation of large datasets, developing scalable algorithms has come to the forefront as a crucial step in analyzing these datasets. In this talk, I will ... -
Second Order Machine Learning
(Georgia Institute of Technology, 2017-09-22)A major challenge for large-scale machine learning, and one that will only increase in importance as we develop models that are more and more domain-informed, involves going beyond high-variance first-order optimization ... -
The Science of Stories: Measuring and Exploring the Ecology of Human Stories with Lexical Instruments
(2019-11-06)I will survey our efforts at the Computational Story Lab to measure and study a wide array of social and cultural phenomena using “lexical meters” — online, interactive instruments that use social media and other texts to ... -
Building Trustworthy AI for Environmental Science
(2020-09-25)As climate change affects weather patterns and sea levels rise, the world’s need for accurate, usable predictions of weather and ocean and their impacts has never been greater. At the same time, the quantity and quality ... -
Understanding Human Functioning & Enhancing Human Potential through Computational Methods
(2020-10-08)It is generally accepted that computational methods can complement traditional approaches to understanding human functioning, including thoughts, feelings, behaviors, and social interactions. I suggest that their utility ... -
Curating a COVID-19 data repository and forecasting county-level death counts in the United States
(2020-10-23)As the COVID-19 outbreak evolves, accurate forecasting continues to play an extremely important role in informing policy decisions. In this paper, we present our continuous curation of a large data repository containing ... -
Collision Course: Artificial Intelligence meets Fundamental Interactions
(2020-10-30)Modern machine learning has had an outsized impact on many scientific fields, and fundamental physics is no exception. What is special about fundamental physics, though, is the vast amount of theoretical, experimental, and ... -
Challenges and Opportunities at the Nexus of Synthetic Biology, Machine Learning, and Automation
(2020-11-13)Inspired by the exponential growth of the microelectronic industry, my lab has been attempting to build a biofoundry that integrates biology, automation and artificial intelligence (AI)/machine learning for rapid prototyping ... -
Logical Neural Networks: Towards Unifying Statistical and Symbolic AI
(2021-01-15)Recently there has been renewed interest in the long-standing goal of somehow unifying the capabilities of both statistical AI (learning and prediction) and symbolic AI (knowledge representation and reasoning). We introduce ...