Hsuan-Tien Lin

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Hsuan-Tien Lin (Picture)
(Taken on Mar. 12, 2009, Room 314, NTU CSIE)
(New!) I am currently the Chief Data Science Consultant at Appier. Appier is a young company that specializes in making AI easier. We are eager to recruit more talented Data Scientists. If you are interested, please feel free to drop me an email.
Machine Learning Foundations Machine Learning Techniques
My two Mandarin-teaching MOOCs Machine Learning Foundations and Machine Learning Techniques have attracted more than 40K online students in total. Visit here for free Youtube video links, slides and more!
Learning from Data (Book)
My co-authored book Learning from Data: A Short Course is available for sale on Amazon, and is consistently one of the best sellers.

Short Bio

Prof. Hsuan-Tien Lin received a B.S. in Computer Science and Information Engineering from National Taiwan University in 2001, an M.S. and a Ph.D. in Computer Science from California Institute of Technology in 2005 and 2008, respectively. He joined the Department of Computer Science and Information Engineering at National Taiwan University as an assistant professor in 2008, and was promoted to an associate professor in 2012, and has been a professor since August 2017. He received the title of the Cyberlink/Perfect Endowed Chair Professor in 2022. Between 2016 and 2019, he worked as the Chief Data Scientist of Appier, a startup company that specializes in making AI easier in various domains, such as digital marketing and business intelligence. Currently, he keeps growing with Appier as its Chief Data Science Consultant.

From the university, Prof. Lin received the Distinguished Teaching Awards in 2011 and 2021, the Outstanding Mentoring Award in 2013, and five Outstanding Teaching Awards between 2016 and 2020. He co-authored the introductory machine learning textbook Learning from Data and offered two popular Mandarin-teaching MOOCs Machine Learning Foundations and Machine Learning Techniques based on the textbook. He served in the machine learning community as Progam Co-chair of NeurIPS 2020, Expo Co-chair of ICML 2021, Workshop Chair of NeurIPS 2022, Lead Workshop Chair of NeurIPS 2023, and Program Chair of ACML 2024. His research interests include mathematical foundations of machine learning, studies on new learning problems, and improvements on learning algorithms. He received the 2012 K.-T. Li Young Researcher Award from the ACM Taipei Chapter, the 2013 D.-Y. Wu Memorial Award from National Science Council of Taiwan, and the 2017 Creative Young Scholar Award from Foundation for the Advancement of Outstanding Scholarship in Taiwan. He co-led the teams that won the third place of KDDCup 2009 slow track, the champion of KDDCup 2010, the double-champion of the two tracks in KDDCup 2011, the champion of track 2 in KDDCup 2012, and the double-champion of the two tracks in KDDCup 2013. He served as the Secretary General of Taiwanese Association for Artificial Intelligence between 2013 and 2014.

Experience (complete curriculum vitae)



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