Athanasios Kottas

Athanasios (Thanasis) Kottas is a Professor in the Department of Statistics at the University of California, Santa Cruz (UCSC), part of the Baskin School of Engineering. He holds a Ph.D. in Statistics from the University of Connecticut (2000) and a M.Sc./B.Sc. in Mathematics from the University of Ioannina, Greece. His research focuses on Bayesian nonparametric methods, mixture models, point processes, and their applications in biometrics, ecology, and environmental science. He has served as an editor for Bayesian Analysis and has authored numerous influential papers in top statistical journals.

Education:

• Ph.D. in Statistics, University of Connecticut, 2000
• M.Sc. in Statistics and Operations Research, University of Ioannina, 1996
• B.Sc. in Mathematics, University of Ioannina, 1994

Research Interests:

Kottas specializes in Bayesian nonparametric modeling, including mixture models, ordinal regression, and applications in environmental and ecological statistics. His work emphasizes flexible statistical frameworks for complex data structures, such as point processes, survival analysis, and spatial-temporal dynamics. Recent projects include developing methods for risk assessment in developmental toxicity and quantile regression.

Publications:

His 60+ publications span journals like Bayesian Analysis, Journal of the American Statistical Association, and Environmetrics, reflecting contributions to both methodology and interdisciplinary applications. Key themes include nonparametric density regression, spatio-temporal modeling, and Bayesian quantile analysis.

Awards & Honors:

• ISBA Savage Award (via student Maria DeYoreo, 2015)
• Honorable Mention for Savage Award (via student Matthew Taddy, 2009)
• Editor of Bayesian Analysis (2018–2024)

Students & Advising:

Kottas has mentored over 20 Ph.D. and M.Sc. students, many of whom have won prestigious awards. His advising emphasizes methodological innovation and interdisciplinary impact.

Labs & Collaborations:

He collaborates actively with researchers in ecology, environmental science, and astrophysics, leveraging Bayesian nonparametric tools to address real-world challenges.