2nd Annual Data and Network Science Boot Camp

September 18, 2015

The Network Science IGERT program held its second annual boot camp September 8-18 in the Cooper Lab on the UCSB campus. The event drew the interest from many students from the campus, from diverse departments/units such as Computer Science, Electrical and Computer Engineering, Mechanical Engineering, Molecular Biology, and Linguistics. The goal of the boot camp is to train participants on big data and network science. Specific topics included

  • Computer Basics
  • Data Visualization
  • Linear Algebra
  • Graph Algorithms
  • Dynamical Systems
  • Statistics
  • Machine Learning

The program started with a faculty panel discussing the need for interdisciplinary research at the graduate level, and the value of training in data and network science. The program continued with daily training sessions in the morning and the afternoon, many of which were hands-on labs. There were also three lunch-time presentations by UCSB faculty meant to facilitate collaboration among the boot camp participants, many of whom were new to UCSB. The program concluded with a graduate student panel.

Dr. Luca Foschini, who received his PhD in 2012, led the boot camp and played a major role in its design. Instructors included the following:

  • Haraldur Tómas Hallgrímsson, Computer Science graduate student
  • John O’Donovan, PhD, Computer Science researcher
  • Victor Amelkin, Computer Science graduate student
  • Nirman Kumar, PhD, Computer Science postdoc
  • Hari Sivakumar, Electrical Engineering graduate student
  • Arya Pourzanjani, Computer Science graduate student
  • Bo Zong, PhD, Computer Science graduate

The boot camp is just one programmatic activity of the Network Science IGERT, an NSF-funded, interdisciplinary graduate training program. The IGERT prepares students to engineer and control large networks, measure and predict the dynamics of networks, design algorithms to operate at scales of millions and billions of entities, make such networks robust, and develop new scientific hypotheses and principles about networks. There is growing demand for such a trained interdisciplinary workforce from multiple domains of science, commerce, and national security.