Highlights from the 3rd Data and Network Science Boot Camp

September 16, 2016

The focus of the third Network Science boot camp was to build a sense of camaraderie among the current cohort of IGERT trainees. The camp, held from September 6-16, just before the start of the Fall Quarter provided a foundation for working with networked data and had students working on small research projects from Day 1.

Morning seminars touched on subjects such as

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

The program concluded with these four project presentations:

Modeling Disease Propagation over Networks
Trainees: Isaac Mackey, Jacob Fisher, Taom Sakal
Mentor: Shadi Mohagheghi

Is it What You Publish, or Who You Publish With?
Trainees: Furkan Kocayusufoglu, Freddy Hopp, Xiaoming Duan
Mentor: Yi Ding

Bikeshare Projects: A Bayesian Network Approach
Trainees: Pedro Cisneros, Rachel Redberg, Devin Cornell
Mentor: Minh Hoang

Ship Routing to Avoid Whale Strikes with Least Cost Routes
Trainees: David Grimsman, Christina Awadalla
Mentor: Ben Best

We wish to thank the following people for their help with mentoring:

  • Dr. Ben Best, PhD Duke
  • Yi Ding, PhD student, Computer Science
  • Dr. Luca Foschini, PhD UC Santa Barbara
  • Minh Hoang, PhD student, Computer Science
  • Alex Jones, PhD student, Computer Science
  • Arlei Lopes da Silva, PhD student, Computer Science
  • Wenjun Mei, PhD student, Mechanical Engineering
  • Shadi Mohagheghi, PhD student, Electrical and Computer Engineering

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.