SCALES Research - School of Engineering | School of Engineering

Research Areas

Predictive Modeling & Simulation

Interdisciplinary foundational research on predictive modeling and simulation informed by data.
Multiphysics & Nonlinear Analysis

Advanced simulation of coupled physical systems and interactions.
Data-Enabled Simulation

Assimilation of experimental and observational data into simulations for validation and physically meaningful predictions.
Machine Learning & Artificial Intelligence

Using ML and AI to infuse advanced models with data or develop computationally less intensive surrogate models.
High-Performance Computing

Methods and code development and execution for large-scale computational research.
Computational Science & Engineering

New computational approaches addressing contemporary challenges in engineering and the sciences.

Potential Collaborations

Examples of potential research collaborations are:

Partner with the Institute of National Security to investigate the consequences of extreme physical events on the nation’s security infrastructure (e.g., power grid, lifelines, and computing infrastructure) and engage in collaborative research to develop quantum computing algorithms to address national security challenges.

Assist the Center for Sustainability, Energy and Climate (VSEC) in developing predictive modeling methods for alternative energy applications.

Collaborate with the Lab for Immersive AI Translation (VALIANT) on the generation of new Physics-Informed Neural Networks (PINNs) for a variety of contemporary engineering, physical, and medical science applications.

Collaborate with the Vanderbilt Institute of Nanoscale Science and Engineering (VINSE), which has established a very strong experimental program. SCALES could be instrumental in building strengths in computation and establishing a similar level of activity in computational nanoscience. For example, SCALES could collaborate on computational materials discovery and design in energy, nanophotonics, and quantum information science.

Collaborate with the Institute for Surgery and Engineering (VISE) to develop predictive modeling methods and software tools for patient-specific cardiovascular surgical planning and the design of prosthetic devices.

There are many other collaborative opportunities, and our mission is to seek these out and form transformative research collaborations to solve real-world problems.

Research Highlights

Researcher: Bin Ouyang

Viability Assessment of Desired Experimental Routes

Research Paper

Researcher: Ravindra Duddu

Mixed Mode Fracture in Composites

Research Paper

Researcher: Yuri Bazilevs

Predictive Modeling of Materials and Structures in Extreme Environments

Research Paper

Researcher: Haoxiang Luo

Computational Modeling of Hummingbird Flight

Research Paper

Publications

Professor De-en Jiang
1. Liu, L.-J.; Li, B.; Lin, Y.; Guo, J.; Zhang, M.-M.; Chen, J.; Jiang, D.-e.*; He, J.* Ligand-Shell-Enabled Silver Catalysis on Gold Nanoclusters for the Straightforward Synthesis of β-Naphthol Ethers from Alkynes. Journal of the American Chemical Society 2026. DOI: 10.1021/jacs.6c16373.
2. Fang, Y.; Wang, J.; Park, H.; Liu, X.; Surta, T. W.; Jagadeesan, S. N.; Sui, Y.; Jiang, Z.; Yu, M.; Jung, M. S.; Yang, S.; Murphy, S. P.; Zheng, X.; Jiang, D.-e.*; Li, Y.*; Liu, T.*; Ji, X.* Iron-Based Sodium-Salt Composite Cathode for Sodium-Ion Batteries. Advanced Energy Materials 2026, 16, e71154. DOI: 10.1002/aenm.71154.
3. Zingg, B. H. C.; Abdul Rahman, N. B.; Devi, N.; Zornes, A.; Damron, J. T.; Zuleta S., E. C.; Lin, Y.-R.; Arregui-Mena, J. D.; Liu, C.; Martins, M. L.; Yao, S.; Li, M.; Jiang, D.-e.; Meyer, H. M., III; Wu, Z.; Polo-Garzon, F. Enhanced Catalytic Dechlorination of Polyvinyl Chloride (PVC) and H₂ Production Enabled by Synergistic Ga^δ+/Ga⁰ Active Sites in Liquid Metal Particles. Journal of the American Chemical Society 2026. DOI: 10.1021/jacs.6c09418
Professor Bin Ouyang
1. Wang, B. Shen, Z. He, Z. Ye, Y. Zeng, C. A. Mirkin, and B. Ouyang, “Universal Framework for Efficient Estimation of Stability in Multi-Principal Element Alloys”, Nature Communications, 17 (2026) 3093. DOI: https://doi.org/10.1038/s41467-026-69585-9
2. Liu, B. Ouyang, and Y. Zeng, “Balancing Autonomy and Expertise in Autonomous Synthesis Laboratories”, Nature Computational Science, 5 (2025) 92–94. DOI: https://doi.org/10.1038/s43588-025-00769-x
3. Wang, Y. Zhang, K. James, and B. Ouyang, “General Model for d-Center Prediction in Multi-Principal-Element Alloys”, Journal of the American Chemical Society, 147 (2025) 22944–22950. DOI: https://doi.org/10.1021/jacs.5c05649
Professor Haoxiang Luo

Hyde, G., Tobalske, B.W., Cheng, B., & Luo, H. (2026). Flapping counter torque and active control in the escape maneuvers of hummingbirds. Bioinspiration & Biomimetics, 21(1), 016032. DOI: 10.1088/1748-3190/ae3ffa
Haque, M. N., Tobalske, B.W., Cheng, B., & Luo, H. (2024). Inertial coupling of the hummingbird body in the flight mechanics of an escape manoeuvre. Journal of the Royal Society Interface, 21(219), 20240391. https://doi.org/10.1098/rsif.2024.0391
Haque MN, Cheng B, Tobalske BW, Luo H. (2023) Hummingbirds use wing inertial effects to improve maneuverability. Journal of Royal Society Interface. 20:20230229. http://doi.org/10.1098/rsif.2023.0229
Haque MN, Cheng B, Tobalske BW, Luo H. (2023) Active wing-pitching mechanism in hummingbird escape maneuvers. Bioinspiration & Biomimetics, 2023 Aug 29;18(5). https://doi: 10.1088/1748-3190/acef85.
Professor Caglar Oskay
- Arora, B. M. Ward and C. Oskay, “An implementation of the finite element method in hybrid classical/quantum computers,” Finite Elements in Analysis and Design, 103:104733, 2025.DOI: 10.1016/j.finel.2025.104354
- Nasirov and C. Oskay, “Surrogate-enhanced higher order eigenstrain-based reduced
  order homogenization for polycrystal plasticity,” Computer Methods in Applied Mechanics and Engineering, 452B:118772, 2026.DOI: 10.1016/j.cma.2026.118772
- PHASE: Pauli Hierarchical Assembly on Subdivided Elements for Quantum-Compatible Operator Synthesis Tillman Philo, Caglar Oskay arXiv:2606.11478
Professor Yuri Bazilevs

A review of weakly enforced Dirichlet boundary conditions in computational flow analysis
MC Hsu, M Jaiswal, Y Bazilevs arXiv preprint arXiv:2609.06314
A layer-wise NURBS-based reconstruction method for cross-sectionally coherent geometries (LaNURM): An application to orientation optimization of RotTPMS-based trabecular bones TV Duong, KQ Tran, KD Nguyen, Y Bazilevs, H Nguyen-Xuan
Finite Elements in Analysis and Design 260, 104602
A Coupled Diffusion–Mechanics Isogeometric Kirchhoff–Love Thin-Shell Framework for Architected Materials and Structures K Ma, Y Zhu, Y Bazilevs Journal of the Mechanics and Physics of Solids, 106824
Professor Ahmad Peyvan

Deep neural operators as accurate surrogates for shape optimization K Shukla, V Oommen, A Peyvan, M Penwarden, N Plewacki, L Bravo, ... Engineering Applications of Artificial Intelligence 129, 107615
Computer simulation of the SARS-CoV-2 contamination risk in a large dental clinic
J Komperda, A Peyvan, D Li, B Kashir, AL Yarin, CM Megaridis, P Mirbod, ...Physics of Fluids 33 (3)
Riemannonets: Interpretable neural operators for riemann problems A Peyvan, V Oommen, AD Jagtap, GE Karniadakis
Computer Methods in Applied Mechanics and Engineering 426, 116996
Professor Ravindra Duddu

Gao, Y., Duddu, R., & Kolouri, S. (2026). Energy loss informed cell-based multilayer perceptron for solving elliptic PDEs with multiscale features. Computers & Mathematics with Applications, 212, 238-263. doi: 10.1016/j.camwa.2026.04.006 (link)
Rai, S., Gupta, A., Patel, B. P., & Duddu, R. (2026). Modeling of crack evolution in composite plates: A layerwise phase field approach with higher order plate theory. Computer Methods in Applied Mechanics and Engineering, 456, 118935. doi: 10.1016/j.cma.2026.118935 (link)
Sutcliffe, S. J., Coombs, W. M., Zhang, W., Duddu, R., & Augarde, C. E. (2026). Modelling cliff collapse and run-out with the material point method. Computers and Geotechnics, 189, 107608. doi: 10.1016/j.compgeo.2025.107608 (link)