Upcoming Events

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Events Archive

We are all science storytellers

We are all science storytellers
Scientists and the journalists who write about them share a common goal: raising awareness of the science that shapes our lives. But we often take different tacks toward achieving that goal. At a time when society increasingly looks to science for answers, how are scientists and journalists working together to ensure that science stories are...
Speaker(s):
Ashley Smart

Q&A Panel on SML 201 and the SML Undergraduate Certificate

Q&A Panel on SML 201 and the SML Undergraduate Certificate

Ever wonder why Data Scientist is being referred to as the “sexiest job of the 21st century”*? Sitting on the fence about joining the CSML certificate program? Are you curious about how your fellow undergraduate students continued their path in Data Analytics after finishing the course SML 201?

Sushi with Sophomores!

Inherent Trade-Offs in Algorithmic Fairness

Inherent Trade-Offs in Algorithmic Fairness
Recent discussion in the public sphere about classification by algorithms has involved tension between competing notions of what it means for such a classification to be fair to different groups. We consider several of the key fairness conditions that lie at the heart of these debates, and discuss recent research establishing inherent trade-offs...
Location: Corwin Hall, Room 127
Speaker(s):
Jon Kleinberg
Departments of Computer Science and Information Science at Cornell University
Tags: Seminars

Physics-informed Machine Learning For Climate, Urban, And Environmental Sciences

Physics-informed Machine Learning For Climate, Urban, And Environmental Sciences
At the confluence of scientific simulation and modern machine learning there exists an opportunity to develop a “middle path” that leverages the strengths of both approaches to build machine-learning emulators of numerical simulation models. From the perspective of machine learning, incorporating simulation data may significantly reduce the need...
Location: Bowen Hall Auditorium Room 222
Speaker(s):
Adrian Albert
Research Scientist, Lawrence Berkeley National Laboratory
Tags: Seminars

Unsolved Data Problems

Unsolved Data Problems

Unsolved Data Problems will introduce faculty and students in the computer and data sciences to the untapped research possibilities inherent in humanities data.

Location: Computer Science Department, Room 105
Speaker(s):
Meredith Martin
Dan Trueman
Brian Kernighan
Jennifer L. Rexford
Marina Rustow

Cosmology with galaxy surveys: from precision to accuracy with data-driven models

Cosmology with galaxy surveys: from precision to accuracy with data-driven models
Immense surveys of the night sky are being conducted to test the origins and evolutions of the Universe as a whole, using distant galaxies and quasars (bright galaxies with active supermassive black holes at their center). This requires modeling the spatial and spectral statistics of those sources in detail using millions of noisy observations,...
Location: PCTS, 407 Jadwin
Speaker(s):
Boris Leistedt
Center of Cosmology and Particle Physics at New York University
Tags: Seminars

Fitting Convex Sets to Data

Fitting Convex Sets to Data
A number of problems in signal processing may be viewed conceptually as fitting a convex set to data.  In vision and learning, the task of identifying a collection of features or atoms that provide a concise description of a dataset has been widely studied under the title of dictionary learning or sparse coding.  In convex-geometric terms, this...
Location: Equad, B205
Speaker(s):
Venkat Chandrasekaran, Professor of Computing and Mathematical Sciences and Electrical Engineering
CalTech
Tags: Seminars

The Complexities of Astronomical Data

The Complexities of Astronomical Data
The analysis of astronomical data set reveals an astonishing diversity of astrophysical processes but also a dizzying array of observational complications. I will introduce several approaches to deal with complications like missing data, non-linear error propagation, and overlapping objects. I will concentrate on proximal optimization algorithms...
Location: Peyton Hall Auditorium, Room 145
Speaker(s):
Peter Melchior
Department of Astrophysical Sciences
Tags: Seminars

Astrophysical Inference with Complex, Stochastic Time Series

Astrophysical Inference with Complex, Stochastic Time Series
Astronomical time series—measurements of a celestial source’s brightness as a function of time—are key to probing the physical processes governing the behaviour of these sources on a large range of scales, from small asteroids in our solar system, to supermassive black holes at the centres of galaxies. Modern time domain surveys like the Zwicky...
Location: PCTS, Jadwin Hall Room 407
Speaker(s):
Daniela Huppenkothen
DIRAC Institute and eScience Institute, University of Washington
Tags: Seminars

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