- \n
- National Science Foundation (NSF)<\/strong>\n
- \n
- Project title: Advancing Bayesian Thinking in STEM.<\/li>\n
- Role: Principal Investigator (PIs: Dogucu (UC Irvine) and Herring (Duke University)).<\/li>\n
- Period: Dec. 2022 – Nov. 2025.<\/li>\n
- Amount: $300,000.00<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
- \n
- Liberal Arts Collaborative for Digital Innovation (LACOL)<\/strong>\n
- \n
- Project title: Bayesian Statistics.<\/li>\n
- Role: Principal Investigator.<\/li>\n
- Period: Oct. 2018 – June 2022.<\/li>\n
- Amount: $27,500.00<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
- \n
- Liberal Arts Collaborative for Digital Innovation (LACOL)<\/strong>\n
- \n
- Project title: Bayesian Inference with Python.<\/li>\n
- Role: Principal Investigator.<\/li>\n
- Period: Jan. 2020 – June 2020.<\/li>\n
- Amount: $3,000.00<\/li>\n<\/ul>\n<\/li>\n<\/ul>\n
\nBook Projects:<\/strong><\/p>\n
\n\n\nAlbert, J. and Hu, J. <\/strong>(2019), \u201cProbability and Bayesian Modeling\u201d, Texts in Statistical Science, Chapman & Hall CRC Press. Text website<\/a>
![\"\"](\"http:\/\/pages.vassar.edu\/jihu\/files\/2019\/09\/ProbBayes-cover-201x300.jpg\")
<\/a><\/p>\n
\nTeaching and learning materials:<\/strong><\/p>\n
- \n
- A GitHub repo<\/a> on Vassar’s Bayesian Statistics course material (lectures, labs, homework, cases studies etc.)<\/li>\n
- I maintain a GitHub repo<\/a> on various resources for undergraduate Bayesian education – let me know if you have recommended material to be added to the repo!<\/li>\n<\/ul>\n
\nShort courses and workshops:<\/strong><\/p>\n
- \n
- “Bayes BATS”, an NSF-funded bootcamp for STEM educators to introduce Bayesian methods in their curriculum (co-presenter), July 2023 (link<\/a>)<\/li>\n
- \u201cBayesian Thinking: Fundamentals, Computation, and Hierarchical Modeling\u201d, ISI short course (co-presenter), January 2023<\/li>\n
- “Introducing Bayesian Statistical Analysis into Your Teaching”,\u00a0 eCOTS 2022 pre-conference workshop (co-presenter), May 2022 (link<\/a>)<\/li>\n
- “Introducing Bayesian Statistical Analysis into Your Teaching”,\u00a0 USCOTS 2021 pre-conference workshop (co-presenter), June 2021 (link<\/a>)<\/li>\n
- \u201cBayesian Thinking: Fundamentals, Computation, and Hierarchical Modeling\u201d, JSM workshop (co-presenter), November 2020 (link<\/a>)<\/li>\n
- “Introduction to Bayesian Inference in R”, Bureau of Labor Statistics short course, Washington D.C., October 2018<\/li>\n<\/ul>\n
\nPresentations and panel discussions:<\/strong><\/p>\n
- \n
- “Examples from Two Undergraduate Bayesian Courses”, Symposium on Data Science & Statistics (co-presenter), June 2021 (link<\/a>)<\/li>\n
- “Bayesian Methods and the Statistics and Data Science Curriculum”, CAUSE & JSDSE webinar series (panelist), February 2021 (slides and recordings<\/a>)<\/li>\n
- “Using CE Microdata in Undergraduate Statistics Courses”, 2019 Consumer Expenditure Surveys (CE) Microdata Users’ Workshop, Washington D.C., July 2019 (slide deck<\/a>)<\/li>\n
- “Teaching an Undergraduate Bayesian Statistics Course”, Statistical Science Department Seminar, Duke University, NC, December 2017<\/li>\n<\/ul>\n<\/div>\n
\nService:<\/strong><\/p>\n
\n\n\n- \n
- Organizer and Discussant, “Introducing Bayesian Methods in Statistics and Data Science Curriculum” (topic-contributed), JSM 2023<\/li>\n
- Section Chair,\u00a0Education Research and Practice Section, International Society for Bayesian Analysis (ISBA), 2023 – 2025<\/li>\n
- Organizer, “Recent developments in Bayesian education” (invited), ISBA 2022<\/li>\n
- Breakout Room Lead, “Teaching Bayesian Statistics”, Prepare to Teach 2021 (slide deck<\/a>)<\/li>\n
- Organizer & Chair, “Thinking beyond the p-value: advancing Bayesian education for the undergraduates” (invited), Joint Statistical Meetings 2020 (summary<\/a>)<\/li>\n
- Treasurer, Education Research and Practice Section, International Society for Bayesian Analysis (ISBA), 2017 – 2019<\/li>\n
- Organizer & Discussant, “Introducing Bayesian Statistics at Courses of Various Levels” (topic-contributed), Joint Statistical Meetings 2017<\/li>\n<\/ul>\n
\nPeer-reviewed publications:<\/strong><\/p>\n
- \n
- Kejzlar, V. and\u00a0Hu, J. <\/strong>(forthcoming), Introducing variational inference in statistics and data science curriculum, The American Statistician<\/em>. link to the published paper<\/a><\/li>\n
- Hu, J.\u00a0<\/strong>and Dogucu, M. (2022),\u00a0Content and computing outline of two undergraduate Bayesian courses: tools, examples, and recommendations,\u00a0Stat SDSS 2021 Special Issue,\u00a0<\/em>11(1), e452.\u00a0Open Access<\/a><\/li>\n
- Dogucu, M. and\u00a0Hu, J.<\/strong>\u00a0(2022),\u00a0The current state of undergraduate Bayesian education and recommendations for the future,\u00a0The American Statistician,\u00a0<\/i>76(4), 405-413.\u00a0Open Access<\/a><\/li>\n
- Albert, J. and\u00a0Hu, J.\u00a0<\/strong>(2020), Bayesian computing in the undergraduate statistics curriculum,\u00a0Journal of Statistics Education,\u00a0<\/em>28(3), 236-247.\u00a0Open Access<\/a><\/li>\n
- Johnson, A., Rundel, C.,\u00a0Hu, J.<\/strong>, Ross, K. and Rossman, A. (2020),\u00a0Teaching an undergraduate course in Bayesian statistics: a panel discussion,\u00a0Journal of Statistics Education,\u00a0<\/em>28(3), 251-261.\u00a0Open Access<\/a><\/li>\n
- Hu, J.\u00a0<\/strong>(2020), A Bayesian statistics course for undergraduates: Bayesian thinking, computing, and research,\u00a0Journal of Statistics Education,\u00a0<\/em>28(3), 229-235.\u00a0Open Access<\/a><\/li>\n<\/ul>\n<\/div>\n
\nWork in progress:<\/strong><\/p>\n
- \n
- <\/li>\n<\/ul>\n<\/div>\n<\/div>\n<\/div>\n<\/div>\n","protected":false},"excerpt":{"rendered":"
I am working on innovative approaches to introducing Bayesian statistics in the undergraduate statistics curriculum. Grants: National Science Foundation (NSF) Project title: Advancing Bayesian Thinking in STEM. Role: Principal Investigator (PIs: Dogucu (UC Irvine) and Herring (Duke University)). Period: Dec. 2022 – Nov. 2025. Amount: $300,000.00 Liberal Arts Collaborative for Digital Innovation (LACOL) Project title: … Continue reading Bayesian education<\/span>
- Hu, J.\u00a0<\/strong>and Dogucu, M. (2022),\u00a0Content and computing outline of two undergraduate Bayesian courses: tools, examples, and recommendations,\u00a0Stat SDSS 2021 Special Issue,\u00a0<\/em>11(1), e452.\u00a0Open Access<\/a><\/li>\n
- Organizer & Chair, “Thinking beyond the p-value: advancing Bayesian education for the undergraduates” (invited), Joint Statistical Meetings 2020 (summary<\/a>)<\/li>\n
- “Bayesian Methods and the Statistics and Data Science Curriculum”, CAUSE & JSDSE webinar series (panelist), February 2021 (slides and recordings<\/a>)<\/li>\n
- I maintain a GitHub repo<\/a> on various resources for undergraduate Bayesian education – let me know if you have recommended material to be added to the repo!<\/li>\n<\/ul>\n
- A GitHub repo<\/a> on Vassar’s Bayesian Statistics course material (lectures, labs, homework, cases studies etc.)<\/li>\n
- Liberal Arts Collaborative for Digital Innovation (LACOL)<\/strong>\n
- Liberal Arts Collaborative for Digital Innovation (LACOL)<\/strong>\n
![\"\"](\"http:\/\/pages.vassar.edu\/jihu\/files\/2019\/09\/ProbBayes-cover.jpg\")
<\/a><\/p>\n