Events

The Genetic Algorithm (GA) is a popular global search algorithm that enjoyed great success applications in many fields. It’s very flexible and effective. However, GA is hindered by performance challenges: difficult-to-reach optimal solutions for complex problems and slow convergence speed for difficult problems.

Searching for exoplanets requires extensive data mining and cross-checking to confirm discoveries.  It also requires proper assembly of search catalogs, along with visualization tools that can be used to sort through large numbers of potential planets. I will demonstrate several such tools developed for the exoplanet program at Vanderbilt, many of which can be easily repurposed for a wide range of astronomical and other scientific projects.

The automatic prediction of protein three-dimensional structures from an amino acid sequence has become one of the most important and researched fields in bioinformatics. As models are not experimental structures determined with known accuracy but rather with prediction, it is vital to determine estimates of a model's quality.  We attempt to solve this problem using machine learning techniques and information from both the sequence and structure of the protein.

In this dissertation, we study data collection and its achievable network capacity in large-scale Wireless Sensor Networks (WSNs). Firstly, we investigate the data collection issue in dual-radio multi-channel WSNs under the protocol interference model. We propose a multi-path scheduling algorithm for snapshot data collection in single-radio multi-channel WSNs and derive its network capacity, which is proven to have a tighter bound compared with the existing best result. We subsequently propose a novel continuous data collection algorithm for dual-radio multi-channel WSNs.

In the field of neuroscience, it is important to share knowledge of identified neurons among neuroscientists. This project presents a cloud-based collaborative platform for neuroscientists to browse and edit information about identified neurons online. NeuronViz is an ongoing effort that builds on the NeuronBank project, which was started several years ago by a group of faculty members and students from Computer Science and the Neuroscience Institute.