NYU Data Science newsletter – October 16, 2015

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I was thinking about the role of analytics and where the profession might develop over the next few years. At the moment, there’s a focus on predictive models and developing analysis into prescriptive models. However, I think analytics can go a step further into what I call anticipatory modeling. It’s early in my thinking process but let me explain the difference.

Predictive modeling is based on the idea that data can be used to predict future behavior. The prediction is based on statistical models which can range from a simple linear equation to more complex models like a neural networks. Predictive modeling focuses on “predicting data we don’t have”. So in social media data, sentiment analysis for a customer could be used to predict whether they are likely to leave or not. It predicts what might happen.

As datasets grow larger, Big Data experts are facing the increasing problem of getting their data ready before it can actually be processed. A recent report found that business intelligence professionals spend anywhere from 50% to 90% of their time preparing data before they can even put it through analytics apps.

Xplenty, which sells a Big Data transformation platform, surveyed more than 200 BI professionals from across the U.S. on several areas of the ETL (Extract, Transform and Load) process. Almost all – 97% – said ETL was vital to business processes.

According to a 2014 U.N. report, 54% of the world’s population resides in urban areas, with further urbanization projected to push that share up to 66% by the year 2050. This projected surge in population has encouraged local and national leaders throughout the world to rally around “smart cities” — a collection of digital and information technology initiatives designed to make urban areas more livable, agile, and sustainable.

Astronomers have spotted a strange mess of objects whirling around a distant star. Scientists who search for extraterrestrial civilizations are scrambling to get a closer look.

The automated classification of music is an important outstanding problem in computer science. Now a straightforward way of analyzing music’s information content could help.

The world’s most dangerous malaria parasite shuffles its genes in a clever attempt to avoid the immune system. A new approach has begun to reveal how the process works.

Microsoft engineers and City of Bellevue planners have a sci-fi inspired strategy for curbing bike and pedestrian injuries on city streets: By using video analytics, they want to predict and prevent crashes before they happen.

“This is like ‘Minority Report,’ ” said Bellevue senior transportation planner Franz Loewenherz, referring to the 2002 film in which Tom Cruise preemptively stops crime. “We’re trying to get out in front of the collisions. We can take a corrective measure before someone gets hurt.”

We invite researchers to submit their recent work on scalable non-parametric methods, including, for example, Gaussian processes, Dirichlet processes, Indian buffet processes, and support vector machines. Full details appear below, in the workshop overview. Submissions will take place in the form of 2-4 page abstracts (unlimited references), in the NIPS style (available here). Author names do not need to be anonymized. Accepted papers will be presented as posters or contributed talks.

Deadline for Paper Submission Extended: 20 October 2015

Professor Panos Ipeirotis, associate professor of Information, Operations and Management Sciences, was recently awarded the 2015 CRT Foundation – Lagrange Prize in recognition of his research in the field of Complexity Science. Established in 2008 by the CRT Foundation and coordinated by the ISI Foundation, the Lagrange Prize is given for outstanding scientific contributions in the field of complexity and complex systems across all the scientific disciplines.