Rongjie Lai
Engineering · Purdue University West Lafayette
Publications
117
Citations
1,814
Est. group size
—
Recurring co-author estimate
Active years
25
Publishing since 2002
Rongjie Lai works at the intersection of applied mathematics, machine learning, and computational science. Much of the work develops mathematical theory and numerical methods for problems like mean-field games (models of many interacting agents), learning on curved data spaces (manifolds), and understanding how neural networks such as transformers generalize. Some projects also apply these methods to areas like model reduction and, in a few collaborative papers, hardware sensors.
Publication output has been fairly steady over the last decade, fluctuating between about 7 and 10 papers per year without a strong upward or downward trend.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Design, implementation, and validation of a portable electronic nose based on embedded system and deep learning model
Measurement Science and Technology · 2026
- Design of Electronic Nose Based on MOS Gas Sensors and Its Application in Juice Identification
Sensors · 2025
- Unsupervised solution operator learning for mean-field games
Journal of Computational Physics · 2025
- Emulating complex synapses using interlinked proton conductors
Physical Review Applied · 2025
- Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights
arXiv (Cornell University) · 2025
- Joint Inference of Trajectory and Obstacle in Mean-Field Games via Bilevel Optimization
arXiv (Cornell University) · 2025
- Understanding In-Context Learning on Structured Manifolds: Bridging Attention to Kernel Methods
arXiv (Cornell University) · 2025
- Generalization error guaranteed auto-encoder-based nonlinear model reduction for operator learning
Applied and Computational Harmonic Analysis · 2024
- A bilevel optimization method for inverse mean-field games<sup>*</sup>
Inverse Problems · 2024
- Manifoldron: Direct Space Partition via Manifold Discovery
IEEE Transactions on Neural Networks and Learning Systems · 2024
- A Bilevel Optimization Method for Inverse Mean-Field Games
arXiv (Cornell University) · 2024
- Generalization Error Guaranteed Auto-Encoder-Based Nonlinear Model Reduction for Operator Learning
arXiv (Cornell University) · 2024
- Unsupervised Solution Operator Learning for Mean-Field Games via Sampling-Invariant Parametrizations
arXiv (Cornell University) · 2024
- Unsupervised Solution Operator Learning for Mean-Field Games
SSRN Electronic Journal · 2024
- Improving Clean Accuracy via a Tangent-Space Perspective on Adversarial Training
arXiv (Cornell University) · 2024
- arXiv (Cornell University)×36
- Journal of Computational Physics×5
- Journal of Scientific Computing×3
- SSRN Electronic Journal×3
- IEEE Transactions on Neural Networks and Learning Systems×2
- Huamin Wang
Engineering · The Ohio State University
- Yichen Sheng
Engineering · Purdue University West Lafayette
- Asim Unmesh
Engineering · Purdue University West Lafayette
- Liang Pan
Engineering · Purdue University West Lafayette
- Xiaocheng Zhou
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