Ph.D. 2026, Mechanical Engineering
Joined Summer 2020
- Ph.D., Mechanical Engineering, Iowa State University, 2026
- B.S., Mathematics, Iowa State University, 2020
Ethan was a Ph.D. student in Mechanical Engineering and joined the Self-aware Complex Systems Laboratory in Summer 2020, after receiving his B.S. in Mathematics from Iowa State University in Spring 2020. His research interests were machine learning, deep learning, and optimization, and he worked on applying deep learning methods to topology optimization. His other activities include high-powered rocketry, cooking, and various outdoor activities.
Research interests: Machine learning, deep learning, optimization
Publications with the lab (12)
- Benchmarking scientific machine-learning approaches for flow prediction around complex geometries — Communications Engineering (2025)
- 3D multiphase heterogeneous microstructure generation using conditional latent diffusion models — Digital Discovery (2025)
- STITCH: Surface reconstrucTion using Implicit neural representations with Topology Constraints and persistent Homology — arXiv preprint arXiv:2412.18696 (2024)
Show all 12
- Geometry matters: benchmarking scientific ml approaches for flow prediction around complex geometries — arXiv preprint arXiv:2501.01453 (2024)
- Neural pde solvers for irregular domains — Computer-Aided Design (2024)
- Latent diffusion models for structural component design — Computer-Aided Design (2024)
- 3d reconstruction of protein structures from multi-view afm images using neural radiance fields (nerfs) — Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern … (2024)
- Deep learning-based 3D multigrid topology optimization of manufacturable designs — Engineering Applications of Artificial Intelligence (2023)
- Generative design of material microstructures for organic solar cells using diffusion models — AI for Accelerated Materials Design NeurIPS 2022 Workshop (2022)
- Algorithmically-consistent deep learning frameworks for structural topology optimization — Engineering Applications of Artificial Intelligence (2021)
- Multigrid Distributed Deep CNNs for Structural Topology Optimization — AAAI 2022 Workshop on AI for Design and Manufacturing (ADAM) (2021)
- Cross-gradient aggregation for decentralized learning from non-iid data — International conference on machine learning (2021)
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