Columbia UniversityÀÇ Pierre Gentine±³¼ö´ÔÀ» ¼¿ï´ë·Î ÃÊûÇؼ 4¿ù 25(¸ñ)/26(±Ý) ¾çÀÏ¿¡ °ÉÃÄ Æ¯° µÎ°³¸¦ ÁøÇàÇÒ ¿¹Á¤ÀÌ¿À´Ï Çкλý ´ëÇпø»ý ºÐµéÀÇ ¸¹Àº Âü¿© ¹Ù¶ø´Ï´Ù.
1. Machine learning for climate science: from emulation to new discoveries
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2. How are plants stressed by water stress? The role of biogeochemistry and time scales
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Pierre Gentine ±³¼ö´Â »ýÅ°è ź¼Ò/¹° ¼øȯ ¿¬±¸¿¡ ´ëÇÑ ¿¬±¸¸¦ ¼±µµÇØ¿Ô°í(
https://scholar.google.com/citations?user=1KXRphAAAAAJ&hl=en), ÃÖ±Ù¿¡´Â Learning the Earth with Artificial Intelligence and Physics (LEAP), NSF Science and Technology Center (STC)ÀÇ µð·ºÅÍ·Î È°µ¿ÇÏ¸ç ±âÈÄ¿¬±¸¿Í ÀΰøÁö´ÉÀÇ °áÇÕÇÏ´Â ¿¬±¸¸¦ À̲ø°í ÀÖ½À´Ï´Ù. MIT¹Ú»ç°úÁ¤µ¿¾È ³·ù¿Í Áõ¹ß»ê ¿¬±¸¸¦ ±â¹ÝÀ¸·Î ¿ø°ÝŽ»ç(microwave, optical, and hyperspectral remote sensing), ½Ä¹°»ý¸®ÇÐ, ±¤ÇÕ¼º, È£Èí, Åä¾ç¼öºÐ µî ´ÙºÐ¾ß¿¡¼ ¿ì¼öÇÑ ¿¬±¸¸¦ ÇØ¿Â °úÇÐÀÚÀÔ´Ï´Ù.
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