What NYU CUSP is like, according to recent grad Aliya Merali - Technical.ly Brooklyn

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Sep. 8, 2014 11:42 am

What NYU CUSP is like, according to recent grad Aliya Merali

NYU's new data science program just graduated its first class. Here's what one grad learned — in the classroom and in working with NYPD 911 call centers.

Aliya Merali shortly after graduating from NYU CUSP.

(Photo courtesy of CUSP)

Aliya Merali had been working in a plasma physics lab at Princeton, but she told us, “I wanted to work on problems where I felt like I would immediately be able to impact the quality of life of people around me.”

That’s why she decided to join the first class at NYU’s Center for Urban Science and Progress, the still new program that’s projected to take over much of Downtown Brooklyn’s old MTA building over the next few years.

Merali spoke to us last week, not long after graduation. CUSP emphasizes a practical orientation to student work, so students finish the program in internships with city agencies. Merali and two other students opted to take internships with the NYPD, where they worked primarily on data that came from 911 call centers.

Merali and her colleagues have continued to work with the data since graduation. They think they might be able to produce an academic paper out of it, or create a machine-learning prototype the NYPD could try out. (None of their work has been used by the force yet.)

Merali focused on building her technical skills during the academic side of the CUSP program. She studied information visualization, statistics, ArcGIS. Basically everyone in the program also comes out with skills in Python, she added.

One of the first skills Merali learned at CUSP was cleaning a dataset. This was different from her experience in science, she said, where the datasets you use are usually ones from your own experiments. In this case, at NYPD, she was using data other people had generated before she’d even been around.

Merali also found that by talking to 911 operators, she developed a much more nuanced understanding of how different calls get coded. By talking to people that created the data, she said, she was able to do a better job of working with it.

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