【學(xué)術(shù)講座】熊輝:Big Data Analytics in Business Environments

作者:教學(xué)辦公室發(fā)布時(shí)間:2018-07-19瀏覽次數(shù):1121

報(bào)告時(shí)間20187309:30-11:30

報(bào)告地點(diǎn):信息樓X321

報(bào)告人簡(jiǎn)介

熊輝教授是Rutgers, the State University of New Jersey正教授 (終身教授)RBS院長(zhǎng)講席教授,中國(guó)科學(xué)技術(shù)大學(xué)大師講席教授、百度商業(yè)智能實(shí)驗(yàn)室主任, 本科于1995年畢業(yè)于中國(guó)科學(xué)技術(shù)大學(xué),博士于2005年畢業(yè)于美國(guó)明尼蘇達(dá)大學(xué)。獲得的部分榮耀包括ACM杰出科學(xué)家、中國(guó)國(guó)家基金委海外杰青B類(lèi)(海外及港澳學(xué)者合作研究基金)、 IBM 創(chuàng)新獎(jiǎng)、2017 IEEE ICDM Outstanding Service Award ICDM-2011最佳研究論文獎(jiǎng)、美國(guó)羅格斯-新澤西州立大學(xué)最高學(xué)術(shù)獎(jiǎng)—the Rutgers University Board of Trustees Research Fellowship for Scholarly Excellence (2009)。 主要學(xué)術(shù)成果包括:1本專(zhuān)著;3本編著,其中Encyclopedia of GISSpringer)被評(píng)為最受歡迎前十名的Springer華人作者的計(jì)算機(jī)著作; 學(xué)術(shù)論文200余篇,其中有70余篇發(fā)表在包括 IEEE Transactions on Knowledge and Data EngineeringVLDB JournalIEEE Transactions on Fuzzy SystemsMachine LearningIEEE Transactions on Systems, Man, and Cybernetics - Part BIEEE Transactions on Mobile Computing在內(nèi)的頂級(jí)權(quán)威刊物上,有40篇發(fā)表在數(shù)據(jù)挖掘的頂級(jí)學(xué)術(shù)會(huì)議 ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD)上。熊輝教授還曾在清華大學(xué)經(jīng)濟(jì)管理學(xué)院、長(zhǎng)江商學(xué)院、中國(guó)科學(xué)技術(shù)大學(xué)管理學(xué)院、南京大學(xué)商學(xué)院、美國(guó)BSE企業(yè)家商學(xué)院、湖南大學(xué)工商管理學(xué)院、大連理工大學(xué)管理學(xué)院、廈門(mén)大學(xué)和大連高級(jí)經(jīng)理學(xué)院講授商務(wù)智能EMBA以及MBA課程,同時(shí)還被中國(guó)國(guó)家龍星計(jì)劃作為海外名師邀請(qǐng)為數(shù)據(jù)挖掘?qū)iT(mén)授課老師,受到廣泛好評(píng)。此外,熊輝教授還擔(dān)任中國(guó)證券業(yè)協(xié)會(huì)互聯(lián)網(wǎng)證券專(zhuān)業(yè)委員會(huì)、中國(guó)計(jì)算機(jī)學(xué)會(huì)大數(shù)據(jù)專(zhuān)家委員會(huì)委員和中國(guó)房地產(chǎn)評(píng)估協(xié)會(huì)顧問(wèn)。

熊輝教授目前擔(dān)任Encyclopedia of GIS (Springer)的共同主編,并擔(dān)任Encyclopedia of GIS (Springer)的共同主編,以及IEEE Transactions on Data and Knowledge Engineering (TKDE)IEEE Transactions on Big Data (TBD)ACM Transactions on Knowledge Discovery from Data (TKDD) ACM Transactions on Management Information Systems (TMIS)的副主編。擔(dān)任ACM KDD-2012企業(yè)及政府主題的共同程序主席、IEEE-ICDM 2013的共同程序主席、IEEE-ICDM 2015的共同大會(huì)主席及ACM KDD 2018的研究專(zhuān)題程序委員會(huì)主席。

熊輝教授的研究工作被ForbesXinhua News Agency, the EconomistHarvard Business Reviewand the Wall Street Journal等媒體廣泛報(bào)道。其中,經(jīng)濟(jì)學(xué)人雜志(the Economist)在2016年專(zhuān)文重點(diǎn)介紹了熊教授利用大數(shù)據(jù)技術(shù)預(yù)防犯罪的研究工作 (Economist Article Title: Cutpurse capers),同時(shí)哈佛商業(yè)評(píng)論在2016年也以專(zhuān)文重點(diǎn)介紹他的關(guān)于人力大數(shù)據(jù)分析的前沿工作。

報(bào)告摘要:

Recent years have witnessed the big data movement throughout all the business sectors. As a result, awareness of the importance of data mining for business is becoming wide spread.  However, the big data are usually immense, fine-grained, diversified, dynamic, and sufficiently information-rich in nature, and thus demand a radical change in the philosophy of data analytics. In this talk, we introduce a set of scenarios for understanding and mining of business data in various business sectors. In particular, we will discuss the technical and domain challenges of big data analytics in business environments. The theme to be covered will include (1) the data mining problem formulation in different business applications, such as marketing, real estate, and mobile intelligence; (2) the challenging issues of data pre-processing and post-processing in business analytics; (3) how the underlying computational models can be adapted for managing the uncertainties in relation to big data process in a huge nebulous business environment. Finally, we will also show some promising research directions.



通訊員:;初審:;終審人:張志遠(yuǎn)

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