Jun S. Liu

{{short description|American mathematician and statistician}}

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| name = Jun Liu

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| birth_date = {{birth date and age |1965|04|26}}

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| fields = Statistical Machine Learning
Monte Carlo Methods
Bayesian statistics
Computational biology
High-dimensional statistics

| workplaces = Harvard University
Stanford University

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| education = Peking University (BS)
Rutgers University
University of Chicago (PhD)

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| thesis_title = Correlation Structure and Convergence Rate of the Gibbs Sampler

| thesis_url = https://www.worldcat.org/oclc/498906088

| thesis_year = 1986

| doctoral_advisor = Wing Hung Wong
Augustine Kong{{MathGenealogy}}

| academic_advisors =

| doctoral_students = {{plainlist|1=

• Yuguo Chen
• Xiaole Shirley Liu{{cite thesis|first=Xiaole Shirley|last=Liu|year=2002|title=Discovery of transcription factor binding sites using computational statistics|degree=PhD|publisher=Stanford University|oclc=84915802|id={{ProQuest|305549892}}}} {{closed access}}
• Chiara Sabatti

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| awards = NSF CAREER Award (1995)
COPSS' Award (2002)
Morningside Gold Medal (2010)
Pao-Lu Hsu [https://www.icsa.org/awards/pao-lu-hsu-award/ Award] (2016)
[https://www.niss.org/about/awards/jerome-sacks-award-outstanding-cross-disciplinary-research Jerome Sacks Award] (2017)
[https://bayesian.org/project/mitchell-prize/ Mitchell Prize] (2000)
IMS Medallion Lecture (2002)
Bernoulli Lecture (2004)
IMS Fellow (2004)
ASA Fellow (2005)
ISCB Fellow (2022)

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| website = {{URL|http://www.people.fas.harvard.edu/~junliu}}

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Jun S. Liu ({{zh|s=刘军|p=Liú Jūn}}; born 1965) is a Chinese-American statistician focusing on Bayesian statistical inference, statistical machine learning, and computational biology.{{DBLP}} He was assistant professor of statistics at Harvard University from 1991 to 1994. From 1994 to 2004, he was Assistant, Associate, and full Professor of Statistics (promoted while being on leave) at Stanford University. Since 2000, Liu has been Professor of Statistics in the Department of Statistics at Harvard University and held a courtesy appointment at Harvard T.H. Chan School of Public Health.

Liu has written [https://scholar.google.com/citations?user=-bHzVq8AAAAJ&hl=en many research papers] and a bookLiu, Jun S. Monte Carlo Strategies in Scientific Computing. New York: Springer, 2001. {{ISBN|978-0-387-95230-7}} about Markov chain Monte Carlo algorithms, including their applications in biology. He is also co-author of several early software on biological sequence motif discovery.:{{Google scholar id}} MACAW, Gibbs Motif Sampler, BioProspector, Motif regressor, MDScan, Tmod; on genetic data analysis: BLADE, HAPLOTYPER, PL-EM, BEAM; and more recently on, genome structure, gene expression and cell type analysis: HiCNorm, BACH, CLIME, RABIT, CLIC, TIMER, and PhyloAcc.