On June 24, Ph.D. student Wanwan Xu successfully defended her thesis entitled “Topics on Statistical Data Fusion with Public Health Applications”. The defense took place online via WebEx and was attended by many students and faculty members. Wanwan’s committee consists of Drs. Robert Aseltine, Kun Chen, Yuwen Gu, and Jun Yan. Thank you all for your support!
After graduation, Wanwan will be a Post-Doc at the Department of Biostatistics at Yale University.
Congratulations, Dr. Xu!
On June 23, Ph.D. student Yan Li successfully defended his thesis entitled “Amalgamation-Based Statistical Learning for Compositional Data”. The defense took place online via WebEx and was attended by many students and faculty members. Yan is co-advised by Drs. Kun Chen and Jun Yan, and his committee consists of Drs. Robert Aseltine, Kun Chen, Elizabeth Schifano, and Jun Yan. Thank you all for your support.
After graduation, Yan will be a Post-Doc at the Department of Biostatistics at the University of Michigan.
Congratulations, Dr. Li!
Our big data research is featured on UConn Today:
The Study of Big Data: How CLAS Researchers Use Data Science
Chen has been elected as Program Chair-Elect 2022 for the ASA Statistical Computing Section.
On April 14, Ph.D. student Zhe Sun successfully defended her thesis entitled “On Statistical Modeling of Longitudinal Compositional Data with Applications in a Preterm Infant Study”. The defense took place online via WebEx and was attended by more than thirty students and faculty members. Zhe’s committee consists of Drs. Kun Chen, Ming-Hui Chen, and Zhiyi Chi. Thank you all for your support.
Congratulations, Dr. Sun!
Dr. Chongliang Luo will join Washington University in St. Louis as an Assistant Professor in fall 2021. Congratulations!
Chongliang is currently a postdoctoral fellow at the Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania. He graduated from UConn with a Ph.D. in Statistics in 2017. His research interests focus on statistical methodology on data integration, including multi-view data integration, statistical methods on meta-analysis and privacy-preserving distributed statistical learning.
Applications are invited for a postdoctoral associate position under the mentorship of Dr. Kun Chen (https://kun-chen.uconn.edu). This position is open immediately until filled, with an anticipated start date in Spring 2021. The initial appointment is for one year with an expected appointment length of 2-3 years upon satisfactory performance and funding availability.
This position involves primarily NIH-funded statistical and machine learning research in the following directions:
Statistical theory and methodology for data integration and data fusion.
Statistical theory and methodology for transfer learning.
Statistical and machine learning methods for building risk prediction models for rare events, in particular, suicide and mental health related outcomes, with large-scale EHR and medical claims data.
Please apply at https://jobs.hr.uconn.edu/cw/en-us/job/494932/postdoctoral-research-associate.
Our work on suicide identification and prevention is reported on UConn Today:
UConn Researchers Leveraging CT Health Data to Develop Suicide Risk Algorithms
GA and Post-doc positions are available in Chen’s research group. If interested please contact Chen at kun.chen@uconn.edu.
Our project on developing suicide risk algorithms for diverse clinical settings using data fusion (R01-MH124740) is awarded by NIH. This is a four-year multi-PI R01 grant starting from September 2020, led by Dr. Robert Aseltine from UCHC, Dr. Kun Chen from UConn, and Dr. Fei Wang from Cornell Medicine. We propose to use data from a large multistate health information exchange, integrated with hospital data from the State of Connecticut, to develop and test suicide risk algorithms using principles associated with statistical data fusion and transfer learning.
Please inquire Dr. Kun Chen at kun.chen@uconn.edu for possible Post-Doc and graduate assistantship opportunities.