I am a 4th year PhD student at Stanford's Institute for Computational and Mathematical Engineering (ICME). I am fortunate to be advised by Daniel Tartakovsky, and grateful to be supported by the Stanford Graduate Fellowship (SGF) and Stanford's Enhancing Diversity in Graduate Education (EDGE) Doctoral Fellowship programs.
My research interests lie at the intersection of mathematics, data, and modeling, which has led me to a focus on scientific machine learning (SciML). Specifically, I am working on developing new graph-based surrogate modeling methods for low-data regimes.
Earlier in my PhD, I collaborated with Jenny Suckale to model volcanic lava fountaining, and Susan Athey and Sanath Kumar Krishnamurthy to design improved algorithms for contextual bandits.
The high cost of data generation is a significant barrier to the development of efficient NN-based surrogate models for many physics-based problems. To address this, I developed a technique to train CNN-based surrogate models on a mixture of solutions to the d-dimensional problem and its (d-1)-dimensional approximation. Our paper was recently published in the Journal of Machine Learning for Modeling and Computing (JMLMC) and is also available on arXiv! If you're interested, you can also check out this talk I gave at MSML23.
I worked with Sanath Kumar Krishnamurthy and Susan Athey to develop the first algorithm that achieves costless model selection in contextual bandits by incorporating the bias-variance tradeoff. I presented our paper at AISTATS2024. The paper is available here, and you can also check out my poster.
I worked with Dr. Carter Price and a team of RAND researchers to evaluate modeling efforts for the COVID-19 pandemic. We developed a framework for what constitutes a suitable model for forecasting the relevant trends for COVID-19, assessing the effects of the pandemic, and informing policy responses.
In a related effort, we developed a model to explore the implications of a hurricane during the COVID-19 pandemic. We specifically explored how behavioral changes during a hurricane, such as evacuation or sheltering in a community facility, might exacerbate the spread of COVID-19, and how the risks can be effectively weighed in developing policy interventions.
A RAND team, led by Dr. Kandice Kapinos, was tasked with investigating the 10Plan, an alternative health care financing approach designed by Mark Cuban. As part of this analysis, I worked with RAND mathematicians to develop a dynamic longitudinal microsimulation to help us better understand how the plan would impact individuals, families, and federal government spending over a 15-year period.
The research brief is available here. Our paper describing the microsimulation model in detail has been accepted for publication at JASSS and is also available on arXiv.
For my masters' dissertation, I worked with Ricardo Ruiz-Baier at the University of Oxford to develop a novel class of 3D models for the electromechanics of cardiac tissue.
My dissertation is available in PDF format below.
The subsequent peer-reviewed journal publication is available here.
While at Harvard, I worked with Josh Benmergui and Steven C. Wofsy on observation system simulation experiments (OSSEs) for MethaneSat. Our goal was to demonstrate the ability of the proposed satellite to constrain methane emissions in comparison to existing observing systems. My senior thesis was cited by NASA's Carbon Monitoring System and is available in PDF format below.
Propp, A. M.*, Tartakovsky, D. Transfer Learning on Multi-Dimensional Data: A Novel Approach to Neural Network-Based Surrogate Modeling. Journal of Machine Learning for Modeling and Computing, 6(2):13–27 (2025). DOI: 10.1615/JMachLearnModelComput.2024057138.
Propp, A. M.*, Vardavas, R., Price, C. and Kapinos, K. The Longitudinal Health, Income, and Employment Model (LHIEM): A Discrete-Time Microsimulation Model for Policy Analysis. Journal of Artificial Societies and Social Simulation, 28 (2) 1. DOI: 10.18564/jasss.5591.
Krishnamurthy, S. K.*, Propp, A. M.*, Athey, S. Towards Costless Model Selection in Contextual Bandits: A Bias-Variance Perspective. Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:2476-2484 (2024). https://proceedings.mlr.press/v238/kumar-krishnamurthy24a/kumar-krishnamurthy24a.pdf
Propp, A. M.*, Gizzi, A., Levrero-Florencio, F. et al. An orthotropic electro-viscoelastic model for the heart with stress-assisted diffusion. Biomech Model Mechanobiol 19, 633–659 (2020). https://doi.org/10.1007/s10237-019-01237-y
Gauthier M, Kim JB, Curry CB, Aurand B, Gamboa EJ, Göde S, Goyon C, Hazi A, Kerr S, Pak A, Propp A, Ramakrishna B, Ruby J, Willi O, Williams GJ, Rödel C, Glenzer SH. High-intensity laser-accelerated ion beam produced from cryogenic micro-jet target. Rev Sci Instrum. 2016 Nov;87(11):11D827. doi: 10.1063/1.4961270. PMID: 27910336.
Chen SN, Gauthier M, Bazalova-Carter M, Bolanos S, Glenzer S, Riquier R, Revet G, Antici P, Morabito A, Propp A, Starodubtsev M, Fuchs J. Absolute dosimetric characterization of Gafchromic EBT3 and HDv2 films using commercial flat-bed scanners and evaluation of the scanner response function variability. Rev Sci Instrum. 2016 Jul;87(7):073301. doi: 10.1063/1.4954921. PMID: 27475550.
Learning Probabilistic Dirichlet-to-Neumann Maps on Graphs, with Jonas Actor, Elise Walker, Nat Trask, Houman Owhadi and Daniel Tartakovsky
Graph-based surrogate modeling for UQ on ice sheets, with Amanda Howard, Mauro Perego, Panos Stinis, Eric Cyr, Anthony Gruber, and Daniel Tartakovsky
The RAND Alcohol Policy Platform (RAPP) Model, with Carolyn Rutter, Raffaele Vardavas, Rosalie Liccardo Pacula, Dulani Woods, and Rosanna Smart
Propp, A. M. and Yoo, P. Y. (2021). Data management. In OECD (Ed.), OECD Global Teaching InSights: A video study of teaching - Technical report. Paris: OECD Publishing. https://www.oecd.org/education/school/GTI-TechReport-Chapter16.pdf
Yoo, P. Y., and Propp, A. M. (2020). Implementation of the pilot study. In OECD (Ed.), OECD Global Teaching InSights: A video study of teaching - Technical report. Paris: OECD Publishing. https://www.oecd.org/education/school/GTI-TechReport-Chapter13.pdf
Yoo, P. Y., and Propp, A. M. (2020). Implementation of the main study. In OECD (Ed.), OECD Global Teaching InSights: A video study of teaching - Technical report. Paris: OECD Publishing. https://www.oecd.org/education/school/GTI-TechReport-Chapter14.pdf
Kapinos, Kandice A., Carter C. Price, Drew M. Anderson, Adrienne M. Propp, Raffaele Vardavas, and Christopher M. Whaley, 10Plan, How Would It Affect Health Care Spending by Consumers and the Federal Government. Santa Monica, CA: RAND Corporation, 2021. https://www.rand.org/pubs/research_briefs/RB10127.html.
Kapinos, Kandice A., Carter C. Price, Drew M. Anderson, Adrienne M. Propp, Raffaele Vardavas, and Christopher M. Whaley, Analysis of the 10Plan: A Self-Pay System Designed to Minimize the Burden of Health Care Costs. Santa Monica, CA: RAND Corporation, 2021. https://www.rand.org/pubs/research_reports/RR4270.html.
Price, Carter C., Kelly Klima, Adrienne M. Propp, and Sean Colbert-Kelly, A Model of the Spread of the COVID-19 Pandemic During a Hurricane in Virginia. Santa Monica, CA: RAND Corporation, 2020. https://www.rand.org/pubs/research_reports/RRA323-2.html.
Price, Carter C. and Adrienne M. Propp, A Framework for Assessing Models of the COVID-19 Pandemic to Inform Policymaking in Virginia. Santa Monica, CA: RAND Corporation, 2020. https://www.rand.org/pubs/research_reports/RRA323-1.html.
U.S. alliance and partner networks: a network analysis of their health and strength.
Mallory, King.; Matthews, Luke J..; McNerney, Michael J.; Redden, Kaleb J.; Propp, Adrienne M.; Sacks, Benjamin J.; Toukan, Mark; Khan, Omair
DRR-A1066-1 (2021)
Site-specific counter-unmanned aircraft systems requirements analysis.
Toland, Brendan.; Adams, Christopher Scott.; DeWeese, Jacob; Dolan, Brian; Hargrove, Henry.; Propp, Adrienne M.; Consaul, Ryan; Westerman, Emma; Savitz, Scott
PR-4854-1-DHS (2020)
PR-A286-2 (2020)
Project management plan: Department of Homeland Security Headquarters Joint Requirements Council requirements analysis support.
Westerman, Emma; Rohn, Laurinda L.; Shelton, William L; Adams, Christopher S.; Ausink, John A.; Barnett, D. Sean; Chang, Joseph C.; Romita Grocholski, Krista; Hottes, Alliison K.; Jackson, John C.; Levedahl, Alexis; Ligor, Douglas C.; Propp, Adrienne M.; Putney, Angela; Romanosky, Sasha; Thompson, Julia A.; Yoder, Emily
PR-4913-DHS (2020)
Analysis of DHS capability requirements and gaps: 2019 annual report on HSOAC analysis for the Joint Requirements Council.
Rohn, Laurinda L.; Shelton, William L.; Levedahl, Alexis; Adams, Christopher S.; Propp, Adrienne M.; Bond, M. Scott
PR-4851-DHS (2020)
Assessment of Microsimulations for MyCare.
Price, Carter; Propp, Adrienne M.
PR-4264 (2019)
Army Media Distribution Division Operation Improvements.
Warren, Drake; Kang, Yun; Propp, Adrienne M.
PR-4420-A (2019)
Klieme, Eckhard & Mccaffrey, Daniel & Bell, Courtney. (2020). OECD Global Teaching InSights / TALIS Video Study policy report. https://doi.org/10.1787/20d6f36b-en.