Haizhao Yang
Professor
Develops deep learning theory and machine learning methods for scientific computing and partial differential equations.
Haizhao Yang's lab at UMD works on physics, climate & scientific computing and learning theory & optimization. 41 papers since 2023, 5 at top venues, mostly TMLR and JMLR. 11 PhD students. 41 alumni.
At a glance
- papers, 2023–2026
- 11/ year
- at T1 venues
- 12%
- PhD students
- 11
- MS students
- 0
- alumni listed
- 41
Papers by yearfrom the lab homepage, 2023–2026
- 15 papers2026 · T1 0 · collecting
- 9 papers2025 · T1 1
- 11 papers2024 · T1 3
- 6 papers2023 · T1 1
T1 venuesOtherVenues: TMLR, JMLR
Research focuspaper titles that use each topic's words
- Learning theory & optimization16 papers
- partial4 papers
- partial differential3 papers
- Physics, climate & scientific computing1 paper
- scientific computing1 paper
Paper list
From the lab homepage.
202615 papers
- To appear, Communications on Pure and Applied Analysis. [pdf]Accelerating Multi-Block Constrained Optimization Through Learning to Optimize
- Agenthon : Verifiable AI for Quantitative Finance, NeurIPS Workshop [pdf]AgonAlpha: Autonomous Alpha Discovery via Prompt Economy and Scalable Agentic Search
- AI&PDE: ICLR Workshop on AI and Partial Differential Equations [pdf]AutoNumerics: An Autonomous, PDE-Agnostic Multi-Agent Pipeline for Scientific Computing
- International ACM Conference on Knowledge and Information Management (CIKM ) [pdf]Bringing Agentic Search to Earth Observation Data Discovery
- Information and Inference: A Journal of the IMA, [pdf] [doi]Curse of Dimensionality in Neural Network Optimization
- Journal of Geophysical Research - Machine Learning and Computation, . [pdf] [doi]Efficient Kilometer-Scale Precipitation Downscaling with Conditional Wavelet Diffusion
- Numerical Methods for Partial Differential Equations, [pdf] [doi]Finite Expression Method with TranNet-based Function Learning for High-Dimensional Partial Differential Equations
- To appear, Communications in Mathematical Sciences. [pdf]Finite Expression Methods for Discovering Physical Laws from Data
- SIAM Journal of Scientific Computing, [pdf]FMint-SDE: A Multimodal Foundation Model for Accelerating Numerical Simulation of SDEs via Error Correction
- To appear, SIAM Journal of Scientific Computing. [pdf]From Equations to Insights: Unraveling Symbolic Structures in PDEs with LLMs
- The Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS ) [pdf]GAIA: Geometry-Adaptive Operator Learning for Forward and Inverse Problems
- Multiscale Modeling and Simulation: A SIAM Interdisciplinary Journal, [pdf] [doi]Multi-Scale Finite Expression Method for PDEs with Oscillatory Solutions on Complex Domains
20259 papers
- SIAM Journal of Scientific Computing, . [pdf] [doi]A Finite Expression Method for Solving High-Dimensional Committor Problems
- Communications in Mathematical Sciences, . [pdf] [doi]Approximating Korobov Functions via Quantum Circuits
- Communications in Computational Physics, . [pdf]Deep Learning via Neural Energy Descent
- JMLR (T1)Finite Expression Method for Solving High-Dimensional Partial Differential Equations
- Advanced Theory and Simulations, . [pdf] [doi]FMint: Bridging Human Designed and Data Pretrained Models for Differential Equation Foundation Model
- IEEE International Conference on Intelligent Data and Security (IEEE IDS) Special Track: Financial Reinforcement Learning and Foundation Models (FinRLFM). [pdf]LLMs Meet Finance: Fine-Tuning Foundation Models for the Open FinLLM Leaderboard
- SIAM Journal of Scientific Computing, . [pdf] [doi]Nesterov's Accelerated Jacobi-Type Methods for Large-scale Symmetric Positive Semidefinite Linear Systems
- Journal of Scientific Computing, . [pdf] [doi]NewVEM: A Newton Vertex Exchange Method for a Class of Constrained Self-Concordant Minimization Problems
- Journal of Computational Physics, . [pdf] [doi]Solving High-Dimensional Partial Integral Differential Equations: The Finite Expression Method
202411 papers
- Journal of Scientific Computing, . [pdf] [doi]A Distributed Block Chebyshev-Davidson Algorithm for Parallel Spectral Clustering
- JMLR (T1)Deep Nonparametric Estimation of Operators between Infinite Dimensional Spaces
- Communications on Applied Mathematics and Computation, . [pdf] [doi]Hierarchical Interpolative Factorization for Self Green's Function in 3D Modified Poisson-Boltzmann Equations
- IEEE Conference on Multimedia Expo , Oral. [pdf] [doi]Lottery Ticket Hypothesis for Attention Mechanism in Residual Convolutional Neural Network
- The AAAI Conference on Artificial Intelligence (AAAI ). [pdf] [doi]Neural Network Approximation for Pessimistic Offline Reinforcement Learning
- Journal of Computational and Applied Mathematics, . [pdf] [doi]On the Convergence of Orthogonalization-Free Conjugate Gradient Method for Extreme Eigenvalues of Hermitian Matrices: a Riemannian Optimization Interpretation
- TMLR (T1)On the Stochastic (Variance-Reduced) Proximal Gradient Method for Regularized Expected Reward Optimization
- SIAM Journal of Scientific Computing, . [pdf] [doi]Reinforced Inverse Scattering
- Communication in Mathematical Sciences, . [pdf] [doi]Reproducing Activation Function for Deep Learning
- Applied and Computational Harmonic Analysis, . [pdf] [doi]Solving PDEs on Unknown Manifolds with Machine Learning
- TMLR (T1)What is the Solution for State-Adversarial Multi-Agent Reinforcement Learning?
20236 papers
- TMLR (T1)Deep Operator Learning Lessens the Curse of Dimensionality for PDEs
- SIAM Journal of Scientific Computing, . [pdf] [doi]Friedrichs Learning: Weak Solutions of Partial Differential Equations via Deep Learning
- Conference on Neural Information Processing Systems (NeurIPS ). [pdf] [doi]Nearly Optimal VC-Dimension and Pseudo-Dimension Bounds for Deep Neural Network Derivatives
- Scientific Report, [pdf] [doi]On Fast Simulation of Dynamical System with Neural Vector Enhanced Numerical Solver
- Applied and Computational Harmonic Analysis. [pdf] [doi]PiPs: a Kernel-based Optimization Scheme for Analyzing Non-Stationary 1D Signals
- SIAM Journal on Numerical Analysis, . [pdf] [doi]Stationary Density Estimation of Itô Diffusions Using Deep Learning
Where alumni went41 listed
Apply to UMDFall 2027
Not announced yet
UMD Computer Science PhD
- Round
- Single round
- Opens
- —
- GRE
- See program page
- English
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- Fee
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Not yet confirmed for this intake.
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