IUMA Seminar Series – two seminars by Dr. Bormin Huang

El próximo viernes 13 de Septiembre tendrán lugar dos seminarios incluidos en el IUMA Seminar Series denominados "The Phantoms of the Quantization" and "Ultraspectral Sounder and Hyperspectral Imager Data Compression" impartidos por el Dr. Bormin Huang (Space Science and Engineering Center, University of Wisconsin-Madison). La hora de comienzo será a las 12:00 horas en el salón de actos del Edificio de Electrónica y Telecomunicación.

 Breve biografía del ponente (en inglés):

Dr. Bormin Huang is a Fellow of SPIE – The International Society of Optics and Photonics. He received his MSE in aerospace engineering from the University of Michigan, Ann Arbor in 1992, and his PhD in the area of satellite remote sensing from the University of Wisconsin-Madison in 1998. He is currently a research scientist and principal investigator at the Space Science and Engineering Center, the University of Wisconsin-Madison. Dr. Huang serves as an Associate Editor for the IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS) and SPIE’s Journal of Applied Remote Sensing (JARS). He has been a founding chair of three annual international meetings held in USA, Europe and Asia, respectively: SPIE Conference on Satellite Data Compression, Communication and Processing, SPIE Europe Conference on High Performance Computing in Remote Sensing, and IEEE International Workshop on Parallel and Distributed Computing in Remote Sensing, part of the IEEE International Conference on Parallel and Distributed Systems. Dr. Huang also served as a Chair of the Conference on Imaging Spectrometer Technologies and Applications, part of 2013 International Symposium on Photoelectronic Detection and Imaging (ISPDI 2013). Dr. Huang has authored and coauthored near 200 publications, including the book "Satellite Data Compression" published by Springer in 2011. Dr. Huang has broad interests and experiences in remote sensing science and technology, including satellite data compression, high-performance computing in geoscience and remote sensing, remote sensing image processing, forward modeling and inverse problems.