Jana Shuaib’s MATH 696, Fall 2026: This project studies historical pandemics and COVID-19 using statistical and mathematical models to identify important variables for predicting and responding to future outbreaks, and it will continue into MATH 697 in Spring 2027.
Alex Fegghi’s MATH 899, Fall 2026: This research project investigates classification problems with applications to time-series data.
James Slaughter’s MATH 899 and MATH 895, Fall 2025–Fall 2026: James investigates historical and structural features of 199 countries from 1864 to 2024 using quantitative and classification methods to determine which features are most associated with a “socialist” government coming to power, and he may continue this work in Fall 2026 as a culminating experience.
Chad Kite’s MATH 899 and MATH 898 M.S. thesis, Fall 2024–Spring 2026: Chad completed his M.S. thesis over four semesters on evaluating and mapping demographic disparities in traffic stop data from multiple sources, developing Generalized Linear Models and comparing them with a novel geospatial smoothing algorithm to estimate traffic stops where data is unavailable; this work may lead to three research publications.
Pooja Chavanpatil’s MATH 892, Spring 2025–Fall 2025: Pooja’s culminating experience project investigated the relationship between frequent binge drinking and physical health outcomes across racial and ethnic groups in the United States using the 2023 BRFSS SMART data set, while controlling for demographic and socioeconomic variables such as age, gender, income, education, marital status, and insurance status.
Komal Bhimreddy’s MATH 892, Spring 2025: Komal’s culminating experience project investigated the relationship between frequent binge drinking and frequent mental distress among racial and ethnic groups in the United States using the 2023 BRFSS SMART data set, while controlling for demographic and socioeconomic variables such as age, gender, income, education, marital status, and insurance status.
Thanoj Muddana’s MATH 895, Spring 2025: Thanoj completed an internship project at Stanford University on an AI-enhanced clinical evidence tracking and alert system, developing a data-driven system to monitor new clinical research publications and update a centralized REDCap database for active cancer research queries.
Sean Colson’s MATH 696 and MATH 697, Fall 2024–Spring 2025: Sean worked with me on a funded project exploring data analysis of road fatalities by comparing multiple data sources, identifying anomalies and matches, and analyzing factors that explain those anomalies.
Levi Baguley’s MATH 899 and MATH 898 M.S. thesis, Spring 2024–Spring 2025: Levi worked on a research project using generalized additive models to study long-term weather trends, focusing on novel methods for analyzing curve attributes and developing computationally efficient estimation methods, including confidence intervals.
Alex Ness’s MATH 898 M.S. thesis, Spring 2024: Alex completed his M.S. thesis in Statistical Data Science under my supervision, working on Wide-Sense Stationary Vectors by developing theory, running simulations, and applying the research to signal processing, including sound tracks.
Thanoj Muddana’s MATH 899, Fall 2023–Spring 2024: Thanoj completed an independent study on Bayesian inference and participated in econometrics and/or finance data analysis, resulting in a manuscript that was accepted for publication.
Komal Bhimreddy’s MATH 899, Fall 2023–Spring 2024: Komal worked on my risk assessment research using gold returns data and made significant progress on Bayesian inference, resulting in a manuscript that was accepted for publication.
Tharun Kumar Byreddy’s MATH 895, Fall 2023: Tharun completed an internship project under my supervision in collaboration with industry partners who provided the data, focusing on the use of classification tools for high-dimensional data.
Shubhangi Sikaria’s Ph.D. thesis, Spring 2021–Fall 2021: Shubhangi completed her Ph.D. thesis at IIT, India, where I supported her research in computational and Bayesian applications alongside her supervisor, Prof. Sen from ISI Bangalore, at Dr. Sen’s request; her thesis focused on applications of Functional Data Analysis and resulted in a joint publication listed below.
Mentian Yin’s M.S. thesis, Fall 2013–Spring 2014: I advised Mentian’s M.S. thesis on Bayesian data analysis at Soochow University.
Jiangyang Wang’s graduate research project, Fall 2013–Spring 2015: Jiangyang worked on my research project on comparative study and sensitivity analysis of skewed spatial processes, which resulted in an applied research article published in Computational Statistics.
Miao Yang’s graduate research project, Fall 2013–Spring 2015: Miao Yang worked on my research projects on skewed spatial data analysis during his graduate program at Soochow University in Suzhou, China, and co-authored the aforementioned manuscript with Jiangyang; the project also contributed code to an open-source CRAN package.
Cai Li’s graduate project, Fall 2014: Cai Li completed her independent study on spatial data analysis at Soochow University in Suzhou, China.
Zimin Zhong’s Ph.D. thesis, Fall 2007–Spring 2008: At Prof. Eubank’s request, I co-supervised Zimin’s thesis work on Bayesian algorithms for applying curve registration to Functional Data Analysis while she was supervised by Prof. Eubank at ASU.
Jenifer Boshes’ M.S. thesis, Spring 2005–Fall 2005: I supervised Jenifer’s M.S. thesis on spatial data analysis of heterogeneous soil pollution data in the Phoenix metropolitan area, using land-use information and a spatial structure designed to model spatial heterogeneity.
Internship course, Business Statistics, Fall 2015–Spring 2019: I supervised approximately 10 students per year, about 40 students in total, in completing data analysis projects for internship training in the undergraduate Bachelor of Business program at North South University in Bangladesh.
Undergraduate research projects at ASU, Fall 2004–Fall 2007: I supervised undergraduate research projects by Katherine Dunning, Tatiana Moyer, Lydia Tolman, Kristen Fogg, Kristopher Aguilar, Raynette Bradie, and Wes Dyer.
MATH 760 curriculum development, Summer 2025–Spring 2026: I developed a graduate course on Multivariate Statistics for students in Statistical Data Science. The course combines textbook material, group problem-solving, homework assignments, and modern statistical methods for data analysis, along with project-based research on topics not covered in class.
MATH 690 curriculum development, Summer 2024–Fall 2024: I developed a project-based culminating experience for undergraduate students in the Statistics and Data Science program. The capstone project provides students with a culminating experience in applied modern statistical methods for data analysis.
Completed CEETL PLC, Spring 2024: I completed the semester-long New Faculty Professional Learning Community offered by CEETL and met with the Faculty Director every third Monday of each month. The program focused on discussing problems of practice with the goal of promoting equity through group discussion.
Completed CEETL Discussion Circle, Fall 2023: I completed a workshop on the growing availability of AI tools and the practices and questions surrounding their use in the classroom. The discussions expanded my understanding of new technological advances in education.