My main research interests include projections of, and uncertainties in, future sea-level change and their impacts on coastal defense and adaptation decision-making; educational data analytics; and efforts to enhance and improve our understanding of how STEM students develop computational literacy. But, I also work on a diverse set of other topics. Check out the list of previous/ongoing student projects below.
Mike Foster, postdoctoral scholar What is the role of Computational Literacy in STEM undergraduate education, how does CL relate to the demands of the 21st century workforce? (Fall 2023-)
Trevor Lax, Ph.D. student researcher Improved statistical calibration approaches for characterizing uncertainty in future sea-level change (Spring 2024-)
Cameron Bundy, Ph.D. student researcher Education data analytics (Fall 2024-)
Carolina Estevez Loza, Ph.D. student researcher Using the Coastal Impacts and Adaptation Model for analyzing the impacts on adaptation decision-making, costs, and coastal damages from uncertainty in future sea levels (Spring 2023-)
Meghan Childs, Ph.D. student researcher Data-informed stochastic modeling for the spread of COVID-19 (Spring 2021-)
Math, Stats, and STEM Education Research
Jen Sundstrom, REU student researcher Educational data analytics to quantify the effects of class size on student grades (Summer 2024)
Alissa Mitelman, REU student researcher A framework to characterize student and faculty perceptions of computation in introductory probability and statistics (Summer 2024)
Rachel Suchman, REU student researchers Examining the impacts of students' social/study network connectivity on grades and graduation rates (Summer 2023)
Andrea Camacho-Betancourt and Kimberley Dorsey, REU student researchers Characterizing computational literacy by studying faculty perspectives and experiences using computation in their teaching and research (Summer 2023)
Mikayla MacIntyre and Kayleigh Patterson, B.S. student researchers Characterizing computational literacy by studying faculty perspectives and experiences using computation in their teaching and research (Summer 2022-Fall 2022)
Allison Dennis, REU student researcher Educational data analytics to examine the effects of in-group representation on students persistence and grades (Summer 2022)
Tiana Hose, B.S. student researcher using longitudinal data analysis to examine the impacts of Learning Assistants, class sizes, and other interventions on student retention, performance, and persistence (Fall 2021-Spring 2022)
Matthew Dunham, REU student researcher using Jupyter notebooks to characterize students' development of computational literacy in physics and mathematics (Summer 2021)
Mason Tedeschi, REU student researcher developing stochastic models to assess retention and persistence rates for underrepresented undergraduate student populations (Summer 2021)
Matthew Peeks, B.S. student researcher using fixed effects models to examine the effects of class size on student performance and teaching evaluation scores (Spring 2021)
Climate Science Research
Dwight Dinkins, M.S. student researcher Developing machine learning methods to characterize model sensitivity to interactions between parameters (Fall 2023-Spring 2024)
Selorm Dake, B.S. student researcher Use CO2 and Temperature models to predict committed sea level rise and potential risks that arise due to it in order to assess steps that can be taken to mitigate both (Spring 2023-Fall 2024)
Kelly Feke, B.S. student researcher Characterizing the impacts of model structural uncertainty on coastal adaptation costs and damages (Spring 2023-Spring 2024)
Prasanna Ponfilio Rodrigues, M.S. student researcher Using random forests to classify high-end/non-high-end uncertainty in future coastal damages and adaptation costs from sea-level rise (Spring 2023-Spring 2024)
Jaser Iniguez, M.S. student researcher using paleoclimate models and proxy data to characterize structural uncertainty and time-variation in the Earth-system sensitivity (Summer 2021-Spring 2022)
Grayson Olin, B.S./I.E. Research Fellowship evaluating the impacts of correlated sources of data on constraining future predictions of sea-level rise (Summer 2021)
Alana Hough, M.S. student researcher using decision trees and random forests to classify high/low-risk climate states and identify key parametric uncertainties related to sea-level rise hazards (2020-2021)
Ken Shultes, M.S. student researcher developing model calibration methods for uncertainty quantification/characterization for Earth-system sensitivity using long-term carbon cycle models and observational data (2020-2021)
Hannah Sheets, B.S./I.E. Research Fellowship characterizing how delayed action to protect coastal areas affects expected damages from sea-level rise and coastal storms (2020-2021)
Patrick Ribas, summer co-op student quantifying sensitivities, uncertainties and trade-offs in anaerobic food waste disgester and associated greenhouse gas emissions (2020)
H. Nihar Nandan, senior thesis investigating the impacts of uncertainty characterization/quantification in statistical calibration framework, on projections for future temperature and sea levels (2018-2019)
Travis Torline, Undergraduate Student Assistant reconciling multiple approaches to to constrain nonstationary projections of coastal storm surge flood risk (2019)
Mingxuan Zhang, independent study exploring the use of Markov chain Monte Carlo statistical calibration methods to constrain estimates of storm surge return levels (2018-2019)
Kyle Rosenberg, independent study designing a classifier for proposed Pokemon Go trades (2019)
Jon Oulton, independent study cluster analysis and builing a recommendation system for rock climbing routes (2019)
John Letey, independent study exploring the use of Markov chain Monte Carlo statistical calibration methods to fit distributions to data, including estimation of distributions for storm surge return levels (2018)
Alexandra Klufas, summer REU internship characterizing the effects of length of data record on calibrated estimates of storm surge model parameters and return levels (2017)
Rob Fuller, Master's thesis examining the value of expert assessment and probabilistic inversion in constraining projections of Antarctic ice sheet constributions to sea levels (2016-2017)