AI Innovation Institute

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.

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.

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.