CSUN students take first place at Chapman University Datafest

Passing this along from an email I received from a colleague. Congratulations to our students and their faculty mentors!

Over the weekend a team of five students from CSU Northridge took first
place at the Chapman University “Datafest”. A “Datafest” is a regional,
intensive event where student teams from many Universities analyze a
large dataset and present their findings to a set of esteemed judges.
Annual “Datafests” were initiated at UCLA several years ago, and having
since been fully embraced by the American Statistical Association, are
now held at multiple universities across the nation. Typically a
company provides both actual (but anonymized) data to the Datafest
host/venue and also several, general, high-level, research questions of
interest. For more information on the Chapman University “Datafest”
competition, see:


The five CSUN students (the “Mean Squares”) who competed over the
weekend were:

Seyed Sajjadi (Computer Engineering, Team lead)
Matthew Jones (Computer Science)
Ian Postel (Computer Science)
Collin Miller (Computer Science)
Jamie Decker (Art)

Five victorious csun students hold up certificates and medals in a hotel conference room

Victorious CSUN students

It should be noted that not only did our students achieve success at the highest
level, they competed with strong teams from other universities such as
CSU Fullerton, UC Santa Barbara, UC Irvine, and USC.

For this particular “Datafest”, the students analyzed corporate-level
“big data” from the travel site “Expedia”. The dataset contained
approximately 10 million data points with information related to clicks,
searches, and bookings.

The judges were senior faculty and industry executives. The judges
indicated that the work done by the CSUN team was “incredible”. CSUN’s
team won “Best Insight” and “Best Overall”.

Our students’ 1), preparatory planning and vision; 2), ability to
navigate nuanced, technical questions and analytic, technology-based
queries; 3), skilled acumen with various statistical learning
methodologies and “data science” software tools; and 4), deep attention
to focused results are extraordinary and exemplary.