I am a statistician and an Associate Professor in the 
Department of Mathematics and Statistics at Vassar College. I received my Ph.D. in statistics from Duke University Department of Statistical Science in 2015 (advisor: Jerry Reiter) and my BSc in Computing Mathematics, Department of Mathematics, City University of Hong Kong in 2011.
I was selected as the ASA/NSF/BLS Fellow at the Bureau of Labor Statistics in Washington D.C., 2018 – 2019, a faculty fellow of Data Analysis and Statistics Research Opportunities with NSF, National Center for Science and Engineering Statistics (NCSES), June to December 2020 and June to August 2021, and a fellow at OpenDP in summer 2021. Currently I am a non-resident fellow at Urban Institute.
I also provide statistical consulting service, mainly on data privacy and confidentiality. Currently I am a statistical consultant for the New York City Department of Health and Mental Hygiene on microdata privacy and confidentiality protection projects.
Click here for my CV.
News:
April 2025:
For family reasons, I am taking a leave from Vassar College and will be joining the Mathematics and Statistics Department at Binghamton University, starting Fall 2025.
I organized an invited session on “Recent Developments in Statistical Data Privacy Techniques and Applications” at the 2025 ICSA Applied Statistics Symposium in June 2025.
I am so honored to be selected for the 2024/25 Distinguished Alumni Award from College of Science, City University of Hong Kong.
Come and check it out: DataFest 2025 @ Vassar from April 11th to April 13th, 2025!!
FEBRUARY 2024:
I will be presenting my work with Matthew Williams and Terrance Savitsky on Mechanisms for Global Differential Privacy under Bayesian Data Synthesis at an invited session at the Statistical Society of Canada Annual Meeting 2024 in June 2024 and at the International Society for Bayesian Analysis 2024 (ISBA 2024) World Meeting in July 2024. I will be serving as the session chair of a topic-contributed session on Evaluating Statistical Disclosure Control Techniques based on the Risk and Utility of Privacy-Protected Data at the Joint Statistical Meetings 2024 in August 2024.
Mine Dogucu, Amy Herring and I are hosting our 2024 Bayes BATS bootcamp at Vassar in July 2024! We are so excited to welcome another cohort of STEM educators to immerse in a week-long training and exchange of Bayesian topics and the teaching of them. The ISBA BERaP (Bayesian Education Research and Practice) section is hosting a mixer at ISBA 2024 in Venice and we hope to see you there! Also at ISBA 2024, Harrison Quick and I will be giving a short course on Bayesian Methods for Statistical Data Privacy and we hope to see you there!
Join us for the Privacy and Public Policy Conference in September 2024 at Georgetown Massive Data Institute!!
My consulting work at the New York City Department of Health and Mental Hygiene (NYC DOHMH) is going to be presented by my NYC DOHMH colleagues at the Federal Computer Assisted Survey Information Collection (FedCASIC) Workshop in April 2024 and the American Association for Public Opinion Research (AAPOR) 2024 annual conference in May 2024.
Come and check it out: DataFest 2024 @ Vassar from April 5th to April 7th, 2024!!
MARCH 2022:
I will be presenting my work with Terrance Savitsky and Matthew Williams on Private Tabular Survey Data Products through Synthetic Microdata Generation at an invited session at the Joint Mathematical Meetings (virtual) in April 2022, at RAND’s Statistical Seminar in June 2022, at Fields Institute Workshop on Differential Privacy and Statistical Data Analysis in July 2022, and at an invited session at CMStatistics 2022 in December 2022. I will also present our newest work on Mechanisms for Global Differential Privacy under Bayesian Data Synthesis at a topic-contributed session at IMS Annual Meeting 2022 and an invited session at the Joint Statistical Meetings in August 2022.
I organized two invited sessions at ISBA 2022: Recent Advancements in Bayesian Methods for Statistical Data Privacy and Recent Developments in Bayesian Education. Can’t wait to be in Montreal for ISBA 2022!
I was one of the invited panelists at ASA Privacy Day Webinar in January 2022. Here is the session recording and here is the link to my slide deck on Incorporating Disclosure Risk in Designing Data Synthesis Models.
Kevin Ross and I will give an eCOTS workshop on Introducing Bayesian Statistical Analysis into Your Teaching, May 2022. Check it out here and many other great workshops!
Come and check it out: DataFest 2022 @ Vassar from April 1st to April 3rd, 2022!!
We are offering a co-taught, cross-campus Introduction to Data Science course, June 8 to August 5, 2022 for the fourth time! Registration opens soon so stay tuned. I am also sharing Vassar’s MATH 347 Bayesian Statistics again on the LACOL network for Spring 2022: check out the course recordings and teaching and learning materials at this GitHub repo.
FEB 2021:
I will be presenting my work with Terrance Savitsky and Matthew Williams on Risk-efficient Bayesian Data Synthesis for Privacy Protection at invited sessions at 2021 The Sixth International Conference on Establishment Statistics. Mine Dogucu and I are presenting our Bayesian teaching experience and resources at SDSS 2021 in June 2021.
Kevin Ross and I will give a USCOTS workshop on Introducing Bayesian Statistical Analysis into Your Teaching, June 2021. Check it out here and many other great workshops!
Come and check it out: DataFest 2021 @ Vassar from April 16th to April 18th, 2021!!
We are offering a co-taught, cross-campus Introduction to Critical Data Science course, June 6 to August 6, 2021 for the third time! Registration opens on March 22, 2021.
Colin Rundel, Kevin Ross and I are hosting a panel discussion on Bayesian Methods and the Statistics and Data Science Curriculum as part of the CAUSE and JSDSE series.
I am giving a talk on my work with Terrance Savitsky and Matthew Williams on Private Tabular Survey Data Products through Synthetic Microdata Generation at brown bag series at the National Center for Science and Engineering Statistics (NCSES).
JAN 2020:
Jim Albert and I will give a JSM short course on Bayesian Thinking: Fundamentals, Computation, and Hierarchical Modeling.
I will be presenting my work with Terrance Savitsky on Risk-efficient Bayesian Data Synthesis for Privacy Protection at invited sessions at the Joint Statistical Meetings 2020. Also at Westat, Smith College and UMass Amherst in Spring 2020.
We are offering a co-taught, cross-campus Introduction to Critical Data Science course, June 10 to August 7, 2020 again! Registration opens on March 1, 2020. I will be co-presenting aspects of the course at OLC Innovate in Chicago in April 2020.
Come and check it out: DataFest 2020 @ Vassar from April 17th to April 19th, 2020!!
I am sharing Vassar’s MATH 301 Data Confidentiality and MATH 399 Bayesian Inference with Python on the LACOL network for Spring 2020.
My Probability and Bayesian Modeling book with Jim Albert was published by CRC Press in the Texts in Statistical Science series!
MAY 2019:
I am sharing Vassar’s MATH 347 Bayesian Statistics again on the LACOL network for Fall 2019.
I am co-teaching a cross-campus Introduction to Critical Data Science course, June 3 to July 26, 2019, with colleagues from Swarthmore College, Washington and Lee University, and Williams College.
I am giving a workshop on Teaching a Shared/Hybrid/Online Course using Zoom at the Blended Learning in the Liberal Arts Conference on May 22nd, 2019!
Come and check it out: DataFest 2019 @ Vassar from April 12th to April 14th, 2019!!
I am giving seminars on recent collaborative work on Bayesian Pseudo Posterior Synthesis for Data Privacy Protection (seminar slides; manuscript) at the US Census Bureau and USDA National Agricultural Statistical Services in March 2019.