Prof. Bonifati will present her latest results on enhancing the quality of querying and inference processes on healthcare data. She and her team operate on real-life data of patients from a French hospital and provide the domain experts with useful data management and learning techniques that can help them with their diagnoses and analyses. In the lecture, she will mainly focus on two techniques. The first technique allows us to add inconsistency annotations to structured data and queries, while the second technique allows us to identify similarities among long time series corresponding to patients’ signals. In both cases, their research aims at providing the caregivers with a better understanding of their clinical data thanks to the improved outcomes of the performed analytics.
Dr. Raymond Ng is internationally renowned for his data mining research. He was program chair of a ACM International Conference on Knowledge Discovery from Large Databases (SIGKDD), the top data mining conference in the world, and program chair of 2009 Data Engineering Conference. His joint paper with Ruben Zamar entitled “Robust Space Transformation for Distance Based Operations” won the SIGKDD best paper award. His paper with his student Yuhan Cai entitled “Indexing Spatio-temporal Trajectories using Chebyshev Polynomials” won the ACM SIGMOD best paper award. He is an Associate Editor for two of the top database and data mining journals in the world: IEEE Transactions on Knowledge and Data Engineering, and the Very Large Data Bases Journal. Dr. Ng collaborates with a broad range of medical researchers.