Web Science and Digital Libraries Research Group

Today, I went to the 2020 ODU Undergraduate Research Symposium (URS). This year, the symposium is held in the Learning Commons, Perry Library, running from 8 am to 12:30 am, including both poster and oral sessions. According to the key organizer Eddie Hill, there are 45 posters. The total number of exhibitions is 125, including posters, oral, and art exhibits. I sat in two oral sessions and went through almost all posters. There are several works that drew my attention, especially the ones that apply machine learning (ML) and neural networks (NN) on cross-disciplinary research. I briefly describe them below.


1. Radio Frequency Signal Classification and detection of Drones based on Machine Learning
    by Michael Nilsen, mentored by Dr. Sachin Shetty, Electrical and Computer Engineering
    The goal of the research is to develop a classifier to distinguish between UAS (unmanned aircraft system) signals and non-UAS signals in multiple bands. For a particular band (e.g., 5m), the work u…

The Web Science and Digital Libraries (WS-DL) Research Group continued to grow in 2019! In this post we recap the highlights of calendar year 2019, including two Ph.D. graduates, seven incoming Ph.D. students, and a new assistant professor.  But don't wait another year to find out what we're up to now -- follow us now on Twitter (@WebSciDL) to keep up to date.

Students and faculty
We are the most proud of the fact that we graduated two Ph.D. students this year:
Lulwah Alkwaidefended her dissertation on 2019-04-04.  Shortly after her defense, Lulwah headed back home in Saudi Arabia to resume her position at the University of Hail, now as an assistant professor.  Mat Kellydefended his dissertation on 2019-05-07.  After selling his house in Portsmouth, Mat headed north to become an assistant professor at Drexel University and is recruiting his own Ph.D. students. Congratulations to @LulwahMA on a successful PhD defense! @WebSciDL@oducspic.twitter.com/54h8pm1dgo — Michele Weigle (@we…

Here’s a list of projects from the CS 620 Introduction to Data Science & Analytics course from Fall 2019. All the projects are implemented using Python and Google Colab. Google Colab (Colaboratory) is a free Jupyter notebook environment that requires no setup and runs entirely in the cloud. With Colaboratory you can write and execute code, save and share your analyses, and access powerful computing resources, all for free from your browser. All the projects are based on publicly available datasets, you’ll be able to find the links to the datasets, all the pre-processing, wrangling, analytics, machine learning and visualization steps using Python from these Colab Reports. If you need a quick summary, there’s a summary of the project at the very end of each Colab report.   Classifying White Wine Samples Dissolving the Myth surrounding Gender, Ethnic and Job discrimination in the city of Norfolk Innovations and Development around the World Crime Analysis Project Accidental Drug Related Dea…