Previous Seminars

The IACS seminar series is a forum for thought leaders from academia, industry, and government to share their research on innovative computational and data science topics and methodologies. Past topics include smart city design, data science for social good, data privacy and security, socially assistive robotics, big data software, machine learning for small business lending, and AI technology development, and data-driven algorithmics.
2020 Feb 28

What Do Models of Natural Language "Understanding" Actually Understand? | Ellie Pavlick, Brown University

1:30pm to 2:30pm

Location: 

Harvard University, Maxwell Dworkin G115, 33 Oxford Street, Cambridge MA

IACS seminars are free and open to the public; no registration is required. Lunch will not be provided.

ABSTRACT: Natural language processing has become indisputably good over the past few years. We can perform retrieval and question answering with purported super-human accuracy, and can generate full documents of text that seem good enough to pass the Turing test. In light of these successes, it is tempting to attribute the empirical performance to a deeper "understanding" of language that the models have acquired. Measuring natural language...

Read more about What Do Models of Natural Language "Understanding" Actually Understand? | Ellie Pavlick, Brown University
2020 Mar 13

IACS Seminar | TBA

1:30pm to 2:30pm

Location: 

Harvard University, Maxwell Dworkin G115, 33 Oxford Street, Cambridge MA

IACS seminars are free and open to the public; no registration required. Lunch will not be provided.

ABSTRACT: Will be posted shortly.

BIO: Will be posted shortly

 

2020 Apr 17

Physics-Informed Machine Learning in Astronomy | Josh Bloom, Berkeley

1:30pm to 2:30pm

Location: 

Harvard University, Jefferson 250, 17 Oxford Street, Cambridge MA

IACS seminars are free and open to the public; no registration required.  Lunch will not be provided.

ABSTRACT: While “off-the-shelf” ML has become pervasively used throughout astronomy inference workflows, there is an exciting new space emerging where novel learning algorithms and computational approaches are demanded and developed to address specific domain questions. After describing such efforts—in the search for Planet 9 and new classes of variable sources—Dr. Bloom will turn his attention to new practical implementations and uses...

Read more about Physics-Informed Machine Learning in Astronomy | Josh Bloom, Berkeley
2020 Apr 24

Can Computers Create Art? | Aaron Hertzmann, Principal Scientist at Adobe, Inc.

1:30pm to 2:30pm

Location: 

Harvard University, Maxwell Dworkin G115, 33 Oxford Street, Cambridge MA

IACS Seminars are free and open to the public; no registration required.  Lunch will not be provided.

Abstract: In this talk, Dr. Hertzmann will discuss whether computers, using Artificial Intelligence (AI), can create art. His talk will cover the history of automation in art, examining the hype and reality of AI tools for art together with predictions about how they will be used. Dr. Hertzmann will also discuss different scenarios for how an algorithm could be considered the author of a piece of artwork, which,...

Read more about Can Computers Create Art? | Aaron Hertzmann, Principal Scientist at Adobe, Inc.