Posted April 5th, 2017
At regular Faculty Meets Faculty events, Tandon professors are given the opportunity to explain their research to colleagues, field questions, and enjoy an hour or so of camaraderie before returning to their labs and classrooms.
The latest event, held on March 29, featured Assistant Professor of Electrical and Computer Engineering Anna Choromanska, who discussed her focus on the branch of machine learning known as deep learning, which seeks to formulate algorithms and computational models that will enable computers to work and solve tasks that the human brain can tackle, but that computers, so far, cannot. She is interested, as she explained, in large-scale machine learning problems — those arising with increased access to massive data sets or large computational models — and massive classification problems (the process of classifying objects, such as images or multimedia collections, into one or a few of millions of categories very fast).
“The amount of digital data available is doubling every two years,” she said. “By 2020 the amount we create and copy each year could reach 44 zettabytes.” (The prefix zetta indicates multiplication by the seventh power of 1000, or 1021.)
Making entertaining asides about the bet between technologists Vladimir Vapnik and Larry Jackel (regarding the year in which we will gain a theoretical understanding of why big neural nets work well) and her own love of dance and music, Choromanska provided lively insight into the importance of Tandon’s Machine Learning Lab.
Having joined the faculty just in January, Choromanska was a welcome new face at the event, and the feeling seemed mutual: she devoted part of her talk to explaining what drew her to NYU and why she is happy to be here. “This is an exciting place to conduct research,” she asserted. “You just have to look at the long list of centers and labs, from C2SMART and CUSP to CATT and the CCS. And there is unparalleled opportunity to collaborate with industry partners like Google, Microsoft, Facebook, Yahoo, IBM Watson, NVIDIA, and AT&T.”