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27 Mar 2024: Wan Yin Lim PhD student   Current situation Member of Chinese Annual Conference (CAC), Methodist Church of Malaysia   Subject Peacebuilding in Malaysia: An Interdisciplinary Examination of Chinese Methodist Peace Theology and Peace Studies &#xa0

3 Apr 2024: 1. C U R R I C U L U M V I T A E. Wah Sung Vincent Mak（麥華嵩）. Address: Cambridge Judge Business School University of Cambridge Trumpington Street Cambridge CB2 1AG United Kingdom Tel: 44 (0)1223 764295 Email: v.mak@jbs.cam.ac.uk Faculty webpage: www.jbs.cam.ac.uk/people/vincent-mak/. PROFESSIONAL EXPERIENCE.  Professor of Marketing & Decision Sciences, Cambridge Judge Business School, University of Cambridge (since 2019; with tenure).  Reader (Associate Professor) in Marketing & Decision Sciences, Cambridge Judge Business School, University of Cambridge (2016-2019; with tenure).  University Lecturer (Assistant Professor) in Marketing & Decision Sciences, Cambridge Judge Business School, University of Cambridge (2014-2016; with tenure).  University Lecturer (Assistant Professor) in Marketing, Cambridge Judge Business School, University of Cambridge (2009-2014).  Visiting Assistant Professor, Department of Marketing, The Hong Kong University of Science and Technology (2008-2009). EDUCATION.  The Hong Kong University of Science and Technology.  2008 PhD in Marketing.  Visiting Scholar, The Fuqua School of Business, Duke University (January-May 2008).  University of Cambridge, Cambridge, UK

14 May 2024: Small Data, Big Time—A retrospect of the first weeks of COVID-19. Qingyuan Zhao. [To be read before The Royal Statistical Society at the Society’s 2021 annual conference held inManchester on Wednesday, September 8th, 2021, the President, Professor Sylvia Richardson, in theChair]. Abstract. This article reviews some early investigations and research studies in the first weeks of the coron-avirus disease 2019 (COVID-19) pandemic from a statistician’s perspective. These investigations werebased on very small datasets but were momentous in the initial global reactions to the pandemic. Thearticle discusses the initial evidence of high infectiousness of COVID-19 and why that conclusion wasnot reached faster than in reality. Further reanalyses of some published COVID-19 studies show thatthe epidemic growth was dramatically underestimated by compartmental models, and the lack of fitcould have been clearly identified by simple data visualization. Finally, some lessons for statisticiansare discussed.Keywords: Infectious disease modeling; Selection bias; COVID-19; Model diagnostics. 1 Introduction. Starting from a regional disease outbreak in Wuhan, China, the coronavirus disease 2019 (COVID-19)rapidly grew into a once-in-a-lifetime