Proposed research program
What could
come next?
My proposed research program connects the ability to predict degradation, respond to damage, and sense change—grounded in rigorous measurement.
IPredictFrom reactions to reliability
I aim to connect materials-scale chemical and electrochemical degradation to structural performance through thermodynamics, multiphysics models, and physics-informed machine learning.
The direction: property-evolution models that carry measured uncertainty into predictions of component and system reliability.
IIRespondFrom healing concepts to scalable materials
I plan to develop self-responsive cementitious materials using multifunctional fibers, engineered activation mechanisms, and scalable extrusion processes.
The direction: reproducible delivery systems that bring autonomous crack sealing closer to structural applications.
IIISenseBefore the first visible crack
I propose combining optical chemical sensing with strain measurements to investigate changes in pore-solution chemistry and internal stress before visible damage develops.
The direction: early degradation diagnostics supported by calibration, reference measurements, and quantified uncertainty.
IVDiscoverBetter evidence. Better material design.
I aim to link reference-grade characterization with rapid, lower-cost measurements, creating traceable datasets for interpretable, physics-informed learning.
The direction: an experimental foundation that supports prediction, sensing, and the design of responsive materials.
Future directions / Proposed independent research program
A shared foundation
Measurement connects
the questions.
Reliable prediction, useful sensing, and reproducible materials design all depend on knowing what we measure—and how confidently we know it.
My proposed program uses characterization and quantified uncertainty to connect these directions, translating observations into models and models into better experiments.
See the work this builds on