Tyler N. Tallman
Environmental Science · Purdue University West Lafayette
Publications
121
Citations
1,506
Est. group size
~9
Recurring co-author estimate
Active years
17
Publishing since 2010
Tyler N. Tallman's research focuses on developing 'self-sensing' materials and structures—especially carbon fiber composites embedded with conductive nanomaterials—that can detect their own damage by measuring changes in electrical properties. A major methodological focus is electrical impedance tomography (EIT), a technique for imaging internal damage from surface electrical measurements, which he combines with mathematical and machine-learning tools (like physics-informed neural networks) to solve the difficult 'inverse problem' of reconstructing damage images from data. This work is aimed at structural health monitoring applications, such as detecting cracks or damage in aerospace and engineered composite structures.
Publication output rose sharply from 2017 to a peak around 2020-2021, then gradually declined and leveled off to a more moderate but steady pace in recent years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Radial strain-induced resistivity variations in fiber-reinforced nanocomposites: A concentric cylindrical analytical model
Journal of Intelligent Material Systems and Structures · 2026
- Physics Informed Neural Networks for Electrical Impedance Tomography
Neural Networks · 2025
- The Effect of Different Regularization Approaches on Damage Imaging via Electrical Impedance Tomography
Journal of Nondestructive Evaluation · 2025
- Detection of Damage in the Presence of Multi-Modal Loading from EIT Data Using a Source Separation Algorithm
2025
- AI-based methods for damage detection and localization via EIT measurements
2025
- Improving the self-sensing inverse problem displacement field recovery via sensor data fusion
2025
- Damage Detection in a Complex Truss Structure via EIT With Mixed Regularization
2025
- A Direct Solution to the Self-Sensing Inverse Problem Via the Primal-Dual Interior Point Method
2025
- Full-field mechanics imaging by direct inversion of electrical data
Proceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2025
- Introduction: frontiers of applied inverse problems in science and engineering
Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · 2025
- Detection of indentation damage in carbon fiber/epoxy composites via EIT during the application of bending loads
NDT & E International · 2024
- Synergistic carbon nanotube + carbon-coated iron nanoparticle polymer composites: Electrical, magnetic, and mechanical properties
Composites Part A Applied Science and Manufacturing · 2024
- Synergistic Carbon Nanotube + Carbon-Coated Iron Nanoparticle Polymer Composites: Electrical, Magnetic, and Mechanical Properties
SSRN Electronic Journal · 2024
- Student Paper: The Current State of Pedagogy on Nondestructive Methods in Engineering Education
2021 ASEE Virtual Annual Conference Content Access Proceedings · 2024
- Validation of a multilayer perceptron for rapid, direct solution of the electrical impedance tomography inverse problem
MRS Communications · 2024
- Composites Science and Technology×8
- Composites Part B Engineering×5
- Journal of Intelligent Material Systems and Structures×5
- Smart Materials and Structures×4
- ASME 2021 Conference on Smart Materials, Adaptive Structures and Intelligent Systems×4
- Hashim Hassan
Environmental Science · Purdue University West Lafayette
- Curtis Walker
Environmental Science · The Ohio State University
- Julio A. Hernandez
Engineering · Purdue University West Lafayette
- Rafiul K. Rasel
Engineering · The Ohio State University
- Yen-Fang Su
Engineering · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile