Our research is focused on the development of algorithms for extracting useful information from large datasets. Our work spans areas such as theory of computation, data mining, machine learning with applications to the analysis of big data from social networks, biomedical data, urban traffic, industrial processes.
We focus on algorithms for: modern computing architectures; pattern mining and learning; temporal, dynamic, and evolving data; unsupervised learning (clustering, diversity).
The common themes of our work include scalability, fairness and privacy, networked data, and rigorous guarantees.
Digital technologies
Artificial IntelligenceBig data & analyticsHigh Performance Computing