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It is time to talk about software engineering (SE) for artificial intelligence (AI). Industry is becoming increasingly dependent on AI software. Clearly, AI is useful for SE. But what about the other way around? How important is SE for AI? Many thought leaders in the AI industry are asking how to better develop and maintain AI software. This talk distills that discussion into the following five rules of SE for AI:
Tim Menzies (IEEE Fellow, Ph.D., UNSW, 1995) is a full Professor in CS at North Carolina State University where he teaches software engineering, automated software engineering, and foundations of software science. He is the directory of the RAISE lab (real world AI for SE). that explores SE, data mining, AI, search-based SE, and open access science.
He is the author of over 280 referred publications and editor of three recent books summarized the state of the art in software analytics. In his career, he has been a lead researcher on projects for NSF, NIJ, DoD, NASA, USDA (funding totalling over 12 million dollars) as well as joint research work with private companies. For 2002 to 2004, he was the software engineering research chair at NASA's software Independent Verification and Validation Facility.
Prof. Menzies is the co-founder of the PROMISE conference series devoted to reproducible experiments in software engineering (http://tiny.cc/seacrafts). He has served as associate editor of IEEE Transactions on Software Engineering, Communications of the ACM, ACM Transactions on Software Engineering Methodologies, Empirical Software Engineering, the Automated Software Engineering, Journal, Information Software Technology, IEEE Software, and the Software Quality Journal. In 2015, he served as co-chair for the ICSE'15 NIER track. He has served as co-general chair of ICSME'16 and co-PC-chair of SSBSE'17, and ASE'12. For more, see his vita (http://menzies.us/pdf/MenziesCV.pdf or his list of publications http://tiny.cc/timpubs) or his home page http://menzies.us.