Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Alexander Landauer (Fed)

Alex Landauer (he/him; ORCID: 0000-0003-2863-039X) is an experimental solid mechanician in the Security Technologies Group. Alex specializes in full-field measurements in mechanics across domains including soft materials, impact protection, 3D printing, semiconductors and cell mechanobiology. Methods include commercial off-the-shelf and custom instruments such as universal testing systems, dynamic mechanical analysis, drop tower impact, and optical imaging systems. Full-field measurement strategies focus on 2D, surface-3D and volumetric digital image correlation (DIC/DVC), particle image velocimetry and single particle tracking (PIV and PTV/SPT), in addition to other image analysis modalities. These enable advanced technique such as light field microscopy (LFM) and traction force microscopy (TFM) measurements, computational methods including finite element model updating (FEMU) and constitutive model fitting routines, and provide key data and diagnostics for material characterization.

Overall, Alex's experimental and computational capabilities build toward an experimental mechanics program that incorporates sophisticated force application and imaging, deformation reconstruction, inverse property identification, machine learning (ML) and constitutive modeling techniques for material measurement and characterization. His interests involve developing experimental systems and techniques to explore and model materials, structure-property relationships, and understand uncertainty and error sources. Alex's collaborative approach and commitment to open software and data (he recently joined the Editorial Board of Scientific Data) strives to help material and physical scientists, biomedical engineers, materials manufacturers, and protective equipment developers understand and design highly performant systems.

Research Interests

  • Non-contact deformation tracking (DIC/DVC/PIV, PTV and SPT) and uncertainty quantification
  • Material metrology for modeling soft, elastomeric and porous materials, including hierarchical and lattice-like engineered materials
  • Mechanical measurements with advanced optics for in situ mechanics experiments (LFM and TFM)
  • Combining experimental techniques and computation (FEMU, virtual fields methods, ML for material science)
  • Material systems for impact protection and mitigation strategies

Ongoing projects

  • Accurate Cure Kinetics, Stress, Mechanical Properties and Warpage: Focusing on DIC for cure shrinkage and wafer- or package-level warpage measurements in a CHIPS funded project (collaboration with MSED and BBD)
  • Impact mitigating materials: Developing measurement techniques and exploring material response for impact-like loading scenarios using tools including an instrumented drop tower and servo-hydraulic load frame with high-speed cameras and Digital Image Correlation (DIC), dynamic mechanical analysis, and micro-computed tomography (with ACMD collaborators Newell Moser and Orion Kafka)
  • Full-field uncertainty estimation for 2D-DIC using deep learning
  • Design of novel bio-inspired ballistic armor components (with Ran Tao, Michael Riley, Russell Maier, Amanda Forster, and UC-Berkley collaborators)
  • Dataset development for spectroscopic analysis of known provenance and post-consumer fabrics (with Katarina Goodge and Amanda Forster)
  • Single-fiber Kolsky bar testing of high-strength fibers to assess effect of artificial ageing and strain rate on ballistic performance (with Amanda Forster and RIT collaborators)

Recent Conference Presentations

  • Landauer A.K and Forster A.L., "Development of Standards and Test Methods for Ballistic Resistant Armor Materials" PANTHER Annual Meeting 2025, Sept, 2025
  • Landauer A.K., Centellas P, Romberg S, Tao R, Gayle A, Engmann S, "Exploring Shrinkage, Stress, and Mechanical Properties in Thermosetting Polymers for Advanced Semiconductor Packaging via Optical Metrologies", Society for Experimental Mechanics, Jun, 2025.
  • Landauer A.K., "Development of a digital image correlation system for in-situ epoxy cure shrinkage, thermal expansion, and wafer warpage measurements", PhotoMechanics - International Digital Image Correlation Society Conference, Oct, 2024
  • Landauer A.K., Faisal A., Adamy W., Goodge K.E., Forster A.L., Engelbrecht-Wiggans A., Paulter N.G., "Dynamic viscoelasticity of single fibers and fiber bundles via stress-relaxation Kolsky bar tension", Society for Experimental Mechanics, Jun, 2024.

Awards

  • NIST MML Early Career Researcher "Accolade" (Material Measurement Laboratory, 2023).
  • SEM Hetenyi Best Paper in 2022 Award (Experimental Mechanics, 2023)
  • NIST NRC Postdoctoral Research Associateship (National Research Council, Awardee, 2019)
  • International Student Paper Competition (Society of Experimental Mechanics, Finalist, 2018)
  • Graduate Research Fellowship (National Science Foundation, Program Fellow, 2015-2020)
  • James R Rice Graduate Fellowship in Solid Mechanics (Brown University, 2014-2015)

Selected Publications

DIC Challenge 2.0: Developing Images and Guidelines for Evaluating Accuracy and Resolution of 2D Analyses: Focus on the Metrological Efficiency Indicator

Author(s)
Philip Reu, EMC Jones, S.S. Fayad, B. Blaysat, E. Toussaint, Mark Iadicola, P. Lava, J Rethore, J. Yang, K. Bhattacharya, L. Yang, D. Deb, C.S.R. Vemulapati, M Klein, E Ando, E Roubin, O. Stamati, C Couture, Alexander Landauer, M. Liu, S Jaminion, T. Siebert, S.N. Olufsen
Background The DIC Challenge 2.0 follows on from the work accomplished in the first Digital Image Correlation (DIC) Challenge Reu et al. (Experimental Mechanics

Publications

IMPPY3D: Image Processing in Python for 3D Image Stacks

Author(s)
Newell Moser, Alexander Landauer, Orion Kafka
Image Processing in Python for 3D image stacks, or IMPPY3D, is a free and open-source software (FOSS) repository that simplifies post-processing and 3D shape

Selected Data and Software Publications

Data and Software Publications

IMPPY3D: Image Processing in Python for 3D Image Stacks

Author(s)
Newell H. Moser, Alexander K. Landauer, Orion L. Kafka
Image Processing in Python for 3D image stacks, or IMPPY3D, is a software repository comprising mostly Python scripts that simplify post-processing and 3D shape characterization of grayscale image
Created December 8, 2019, Updated January 7, 2026
Was this page helpful?