Alex Casey
Engineering · Purdue University West Lafayette
Publications
23
Citations
252
Est. group size
—
Recurring co-author estimate
Active years
12
Publishing since 2014
This researcher's work centers on energetic materials (explosives, propellants, and related high-energy compounds), studying how their physical and chemical properties relate to sensitivity, burning behavior, and shock response. Recent work applies machine learning and neural network methods to predict material properties and performance from underlying molecular and structural data. Note that a few unrelated publications (on sports medicine and antitrust law) also appear in the record, which may reflect co-authorship, name overlap, or interdisciplinary side projects.
Publication output peaked around 2020 with a burst of activity but has slowed to about one publication per year since then, averaging roughly 0.6 papers annually over the last five years.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Generative AI Supply Chain Bottlenecks: When Might an Antitrust Duty to Deal be the Answer?
SSRN Electronic Journal · 2025
- Interpretable Performance Models for Energetic Materials using Parsimonious Neural Networks
The Journal of Physical Chemistry A · 2024
- Prediction of Solid Propellant Burning Rate Characteristics Using Machine Learning Techniques
Propellants Explosives Pyrotechnics · 2023
- Simultaneous Bilateral Tibial Tubercle Avulsion Fracture
Medicine & Science in Sports & Exercise · 2021
- Prediction of Energetic Material Properties from Electronic Structure Using 3D Convolutional Neural Networks
Journal of Chemical Information and Modeling · 2020
- The effect of the chosen distribution form on reaction probability estimates from drop-weight impact results
Journal of Energetic Materials · 2020
- Compendium of Energetic Materials Data
Zenodo (CERN European Organization for Nuclear Research) · 2020
- Hi-ya!: A Rare Quadriceps Lesion In A Rising Champion
Medicine & Science in Sports & Exercise · 2020
- Deep Learning for Energetic Materials: Predicting Material Properties from Electronic Structure using Convolutional Neural Networks
Bulletin of the American Physical Society · 2020
- PREDICTING ENERGETIC MATERIAL PROPERTIES AND INVESTIGATING THE EFFECT OF PORE MORPHOLOGY ON SHOCK SENSITIVITY VIA MACHINE LEARNING
Purdue e-Pubs (Purdue University) · 2020
- Compendium of Energetic Materials Data
Zenodo (CERN European Organization for Nuclear Research) · 2020
- A comparison of Gaussian Process Classification to classical statistical methods in sensitivity tests
Bulletin of the American Physical Society · 2019
- The effects of crystal proximity and crystal-binder adhesion on the thermal responses of ultrasonically-excited composite energetic materials
Journal of Applied Physics · 2017
- Visualization of hot spot formation in energetic materials under periodic mechanical excitation using phosphor thermography
Bulletin of the American Physical Society · 2017
- Burning Surface Temperature Measurements of Propellants and Explosives using Phosphor Thermography
Purdue e-Pubs (Purdue University System) · 2017
- Bulletin of the American Physical Society×3
- Zenodo (CERN European Organization for Nuclear Research)×2
- Purdue e-Pubs (Purdue University)×2
- Medicine & Science in Sports & Exercise×2
- Journal of Chemical Information and Modeling×1
- I. Emre Gunduz
Engineering · Purdue University West Lafayette
- Steven F. Son
Engineering · Purdue University West Lafayette
- Robert E. Ferguson
Engineering · Purdue University West Lafayette
- Timothy D. Manship
Engineering · Purdue University West Lafayette
- Diane N. Collard
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