IACS Seminars


This year's IACS's seminar series will focus on a wide range of topics from machine learning and data visualization to the perils of data science.

Seminars are generally held every other Friday during the academic year, and are free and open to the public. Lunch is served at 12:30pm on a first-come, first served basis, with the seminar beginning promptly at 1pm. Unless otherwise indicated, all seminars will be held in Maxwell Dworkin G115.



September 23, 2016

Machine Learning for Materials Discovery: Low-LTC Compounds, GrainBoundaries and Superlattices

Speaker: Koji Tsuda, Professor, Department of Computational Biology and Medical Sciences Graduate School of Frontier Sciences, The University of Tokyo

Material discovery driven by machine learning is a reality. I report successful case studies in discovery of low LTC compounds from database, grain boundary optimization and automated design of Si-Ge superlattices.

October 7, 2016

Computational lensless imaging: Using optics for computation and computation for optics in miniature sensors and imagers

Speaker: David G. Stork, Rambus Labs

The central insight underlying the field of computational sensing and imaging is that the joint design of optics and signal processing to yield a final digital image or estimate of some property of the scene can relax the traditional constraints on optical elements need to make an optical image that "looks good."  In our lensless imagers, binary diffraction gratings with special mathematical properties yield blurry, blob-like optical images that nevertheless contain sufficient information that a digital image of the scene can be computed.

November 4, 2016

Topic: Social, Collaborative, and Artistic Aspects of Information Visualization

Speakers: Fernanda Viegas & Martin Wattenberg, Google

Data is ubiquitous in our lives. It describes our neighborhoods, our cities, weather patterns, it helps track illnesses and contextualize social patterns. In an increasingly data-rich society, there’s a critical need for tools to help people understand and reason about complex information. Our research seeks to make data visualization accessible to everyone: from lay users to data experts. We will present work that exposes kids to complex data, explores the artistic expressiveness of data, uncovers the underworld of cyber crime and augments our knowledge of scientific fields such as machine learning. This approach to visualization as an inclusive communication medium points the way to a future where every citizen can more fully participate in a data-driven society.

November 18, 2016

Controlling Dynamic Robot Behavior with Optimization

Speaker: Scott Kuindersma, Harvard University

Despite the existence of incredible robot hardware, the limitations of our best planning and control algorithms have prevented us from unleashing these machines to tackle critical exploration, automation, and disaster response challenges. This talk will summarize our recent research on designing optimization algorithms that improve our ability to plan and stabilize dynamic motions involving contact in large-scale robots, including the Atlas humanoid robot at the DRC.

December 2, 2016

The Perils of Data Science

Speaker: Alfred Z. Spector, Two Sigma Investments