On Dec. 6, 2009, Prof. Obradovic gave a keynote lecture at the 3rd International Workshop on Mining Multiple Information Sources, help in conjunction with IEEE International Conference on Data Mining in Miami, FL.
Topic of his lecure was “Spatio-Temporal Characterization of Aerosols through Active Use of Data from Multiple Sensors.”
Following is abstract of his presentation:
One of the main challenges of current climate research is providing Earth-wide characterization of Aerosol Optical Depth (AOD) which indicates the amount of depletion that a beam of radiation undergoes as it passes through the atmosphere. In this talk we will discuss issues related to a statistical approach aimed at better understanding of spatio-temporal distribution of AOD by taking advantage of measurements collected from multiple ground and satellite-based sensors. Challenges to be addressed in contest of global scale AOD estimation include (i) training a predictor for robust performance across multiple accuracy measures; (ii) AOD regression from mixed-distribution spatio-temporal data; (iii) uncertainty analysis of AOD estimation, (iv) active selection of sites for ground based observations, and (v) discovery of major sources of correctable errors in deterministic models.