Location

CS 230

Mission

Study of the principles and applications of logic-based methods in databases, verification of concurrent systems, data mining, and Web information systems.

Details

Members of the Lab are engaged in three major projects: 

  • FLORA - a declarative object-oriented language for programming knowledge intensive applications.
  • The LMC (Logic Programming-Based Model Checking)
  • XSB - A high-performance logic programming and deductive database system.

Location

236 Computer Science

Mission

We focus on network design that will achieve the maximum potential of networked sensors, to revolutionize the way we observe, interact with and influence the physical world. The major technical challenges of sensor networks include scalable network self-organization, as well as efficient processing of the massive amount of spatially and temporally distributed data, under the constraint of limited computation and communication resources.

Details

Specific Projects: 
Network localization: We develop efficient localization algorithm in which sensors collaborate with each other to locate themselves and self-organize into a connected network.
Topology discovery: We work on distributed algorithms that discover and maintain high-order topological features (e.g., holes not covered by sensors) or the geometric shape of the sensor field.
Mobility: We work on heterogeneous sensor networks that integrate mobile nodes (robots, people holding cell phones) with static monitoring sensor nodes and foster novel applications.

Coordinator

Location

CEWIT 243

Mission

Big Data makes for big and interesting problems! Our lab focuses on analyzing large-scale text streams such as news, blogs, and social media to identify cultural trends around the world's people, places, and things.

Details

Our research covers a range of topics in natural language processing. A current focus is using Deep Learning techniques to build concise representations of the meanings of words in all significant languages, and use these powerful features to recognize entities and measure sentiment and other properties of texts. Another focus involves analyzing Wikipedia to identify the fame and significance of historical figures as reported in our book Who's Bigger? and associated website. Our Lydia technology has been licensed by General Sentiment, a social media analysis startup.

Coordinator

Location

CS 1309

Mission

The study of the design and analysis of algorithms.

Details

Theoretical and experimental analysis of string, graph, and combinatorial algorithms, including 

  • applications in computational biology and combinatorial computing,
  • randomized algorithms, with applications to scheduling, and
  • computational geometry and approximation algorithms, particularly with applications to computer graphics and manufacturing.

Coordinator