- Provide support in data preparation and statistical analyses for use in IATTC stock assessments.
- Analyzing various types of univariate and multivariate fisheries data (e.g., catch and effort, morphometric, environmental, mark-recapture, genetics, electronic monitoring).
- Provide analytical support and statistical analyses to all IATTC research programs.
- Develop sampling designs for diverse data collection programs, including catch and effort, electronic monitoring, and mark-recapture.
- Ph.D. Statistics, University of Connecticut, Storrs, Connecticut, 2004
- M.Sc. in Statistics from Michigan State University, East Lansing, Michigan, 2001
- M.Stat. in Statistics from Indian Statistical Institute, Kolkata, India, 1998.
- B.Stat. in Statistics from Indian Statistical Institute, Kolkata, India, 1996.
Dr. Ananda Majumdar joined the Stock Assessment Program in 2021. Her research focuses on a variety of topics including improving stock assessment methods and meeting estimation challenges, analyzing various kinds of univariate and multivariate fisheries data, developing sampling designs for diverse data collection programs including catch and effort, electronic monitoring, and mark-recapture. Among her current tasks, Ananda is working on the reconstruction of tropical Tuna catch time series considering the biases caused by the impact of the COVID-19 pandemic on the species composition of the port sampling operations. As one of IATTC’s senior statisticians, Ananda will be working on a variety of projects using a variety of statistical techniques depending on the needs of the commission and the staff she will be collaborating with. As part of her Ph.D. research at University of Connecticut, Ananda developed flexible multivariate models for spatial data. In the past she has developed novel semiparametric multivariate models for spatial data. She has worked with hierarchical models, bivariate zero inflated models as well as spatio-temporal changepoints. A Bayesian statistician by training, prior to joining IATTC, she has worked with scientists in Ecology, Biology, Environmental Science, Earth Science, Statistics, Economics, Econometries, Finance and other areas. She was born in Bangladesh. Her undergraduate and graduate degrees are from Indian Statistical Institute and Michigan State University. She completed her Ph.D in Statistics with Professor Alan Gelfand from University of Connecticut and was a visiting researcher at Duke University. She served as Assistant Professor in Statistics at Arizona State. She also served as Statistics faculty at Southern Methodist University, Texas. She was invited and complied to serve in developing courses and research programs on Bayesian Analysis and Spatial Statistics at the Center of Advanced Statistics and Econometrics at Soochow University, China, as a Professor in Statistics. She served as a Professor in Statistics at North South University and Independent University, Bangladesh before she joined the program at IATTC.
- McHale, M., Hall. S. Majumdar, A., Grimm, N. B 2017. Carbon lost and carbon gained: a study of vegetation and carbon trade-offs among diverse land uses in Phoenix, Arizona. Ecological Applications
- Majumdar, A., Paul, D. 2016. Zero Expectile Processes and Bayesian Spatial Regression. Journal of Computational and Graphical Statistics
- Majumdar, A., Gries, C. and Walker, J. 2011. A non-stationary spatial generalized linear mixed model approach for studying plant diversity. Journal of Applied Statistics