Prof. Lancelot F. JAMES
Chair Professor, Business Statistics lancelot@ust.hk




Academic qualification
PhD 1993 SUNY Buffalo, Statistics
B.A. 1989 SUNY Buffalo, Statistics

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ACADEMIC AND PROFESSIONAL EXPERIENCEChair Professor of ISOM, HKUST, 2018 - present
Director, MSc in Business Analytics, School of Business and Management, HKUST, July 2021 - present
Director, PhD and MPhil programs, School of Business and Management, HKUST, August 2017 - July 2019
Co-Director, Risk Management and Business Intelligence Program, Interdisciplinary Programs Office, HKUST,2015 - 2019
Professor of ISOM, HKUST, 2008 - 2018
Associate Professor of ISMT, HKUST, 2005 - 2008
Visiting Scholar of ISMT, HKUST, 2001 - 2005
Assistant Professor, Mathematical Sciences, Johns Hopkins University 1995 - 2001
Visiting Scholar, Institut National Recherche Agronomique (INRA) and Centre Recherche Economique et Statistique (CREST), Paris, France 1994 - 1995
Postdoctoral Fellow, National Institute of Health (NIH), Dept. Of Biostatistics, University of Rochester 1993 -1994

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SELECTED PUBLICATIONS James, L. F., "Bayesian Poisson Calculus for Latent Feature Modeling via Generalized Indian Buffet Process Priors
Bayesian Inference on Random Simple Graphs with Power Law Degree Distributions
Stochastic Volatility Models based on OU-Gamma Time Change: Theory and Estimation
Finite-dimensional BFRY Priors and Variational Bayesian Inference for Power Law Models
Exact simulation pricing with gamma processes and their extensions
Bayesian Analysis of Multi-state Event History Data: Beta-Dirichlet Prior
Quantile Clocks
The Sequence Memoizer
The Double CFTP Method
Bayesian Nonparametric Estimation and Consistency of Mixed Multinomial Logit Choice Models
Dirichlet Mean Identities and Laws of a Class of Subordinators
Lamperti-type Laws
Distributions of Functionals of the Two Parameter Poisson-dirichlet Process
Generalized Gamma Convolutions, Dirichlet Means, Thorin Measures, with Explicit Examples
Poisson Calculus for Spatial Neutral to the Right Processes
Bayesian Poisson Process Partition Calculus with an Application to Bayesian Levy Moving Averages
Generalized Weighted Chinese Restaurant Processes for Species Sampling Mixture Models
Gibbs Sampling Methods for Stick-breaking Priors
Consistent Estimation of Mixture Complexity
research-interests">RESEARCH INTERESTS Bayesian Non-parametric Statistics
Bayesian Machine Learning
Beta-Gamma-Stable Distribution Theory
Combinatorial Stochastic Processes
Computational Finance
Financial Econometrics
Random Measures

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PROFESSIONAL HONORSElected Fellow, Institute of Mathematical Statistics (IMS), 2008
Citation: For contributions to Bayesian nonparametric statistics, the development of Poisson partition calculus for Levy processes; and for dedicated service to IMS.
Elected Member, International Statistical Institute (ISI), 2006