Discovery Park F285
Predictive analytics aims to extract information from existing data sets. Combining the derived information with previous experience, predictive analytics forecasts future outcomes and trends. Large-scale predictive analytics plays an essential role in enabling actions based on large amounts of data and is regarded as the corner stone of Data Science. At the first part of talk Dr. Huan overviews his own research in large-scale predictive analytics, covering topics such as learning with structured input and out put and learning with transparency and interpretability. At the second part of the talk, Dr. Huan briefly overview data science related programs at NSF.
Dr. Jun (Luke) Huan is a Program Director in the Information and Intelligent Systems Division at the National Science Foundation. At NSF he manages programs such as IIS core, Big Data, CAREER, and Partnerships for International Research and Education among others. Dr. Huan joins NSF from his home institute, the University of Kansas, where he is the Charles E. & Mary Jane Spahr Professor in the Department of Electrical Engineering and Computer Science.
Dr. Huan is an internationally recognized investigator in data science, AI, data mining and machine learning. He has published more than 120 peer-reviewed papers in leading conferences and journals and has graduated more than 20 graduate students including nine Ph.D.s . He was a recipient of the National Science Foundation Faculty Early Career Development Award in 2009. His group won the Best Student Paper Award (runner-up) at the ACM International Conference on Information and Knowledge Management in 2009. Dr. Huan's editorial memberships have included Springer Journal of Big Data, Elsevier Journal of Big Data Research, and the International Journal of Data Mining and Bioinformatics amon others. His significant service records include serving as an area chair for IEEE ICDM 16-17, a program co-chair for IEEE BIBM'15 and a workshop co-chair for ACM KDD'18.
