Professor and Chair, Duke University Department of Computer Science, Trinity College of Arts & Sciences; Professor, Duke University Department of Biostatistics and Bioinformatics, School of Medicine; Professor of Electrical and Computer Engineering, Pratt School of Engineering.
Fellow, The Royal Society of Canada (FRSC), The Canadian Academy of Engineering (CAE), ACM, and IEEE.
Research Areas: data science, big data, data mining, database systems, and enterprise data strategies.
Ph.D. Student Recruiting
I am recruiting multiple Ph.D. students at Duke University. Ambitious students with solid background and strong interest in data science, data mining, databases, data engineering, computational statistics, and their applications in healthcare, economics, climate changes, green energy, and social good are sincerely welcome to apply. I am particularly eager to look for Ph.D. students passionate about the following directions.
- Data markets and applications
- End-to-end outlier and statistical paradox detection and analysis
- Efficient and scalable statistical analysis in spatial and temporal applications
- Causality, interpretation, and sound and embodied data mining
- Female students and students of under-represented groups in computer science and engineering are especially encouraged to apply.
If interested, please submit your formal application to the Department of Computer Science, the Department of Electrical and Computer Engineering, or the Department of Biostatistics and Bioinformatics at Duke University and list me as a potential advisor. You are welcome to send me a brief introduction by email <firstname.lastname@example.org>. I will try my best to reply to those demonstrating great potential matches.
Evidence of research aptitude, such as publications, working papers, project reports/descriptions, and well-written thoughts about your research interests may substantially strengthen your application. Moreover, priority will be given to students with excellent undergraduate training and proven research experience in computer science, computer engineering, and statistics.