Sipeng Chen

I work on scientific machine learning, with a current focus on implicit neural representations, flow matching, Bayesian optimization, operator/function learning, and data-driven models for complex physical systems.

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About

Self Introduction

I am a Ph.D. student in Computer Science at Florida State University. I received my bachelor's degree from Nanjing University of Posts and Telecommunications and my master's degree from Florida International University, both in Electrical Engineering. My academic background sits at the intersection of engineering, mathematics, and machine learning. I am also proud to be a Choir member of Tallahassee Chinese Christian Church.

Research

Research Interests

Implicit Neural Representations

Representation, optimization, compression, and function approximation.

Flow Matching & Generative Modeling

Multi-fidelity refinement, PDE solution generation, and scientific simulation.

AI for Scientific Computing & Operator Learning

Learning functions, operators, and physical dynamics from scientific data.

Selected Work

Publications

2026

Closing the Capacity–Convergence Gap: Globally Optimal Configuration of Implicit Neural Representations

S Chen, Y Zhang, S Li

ECCV 2026

2026

Regime-Adaptive Bayesian Optimization via Dirichlet Process Mixtures of Gaussian Processes

Y Zhang, X Liu, S Chen, S Ranftl, C Liu, S Li

ICML 2026

2026

SFBench: Evaluating Data-Driven Models for Compound Flood Forecasting in South Florida

X Zheng, C Lin, S Chen, Z Chen, J Shi, W Cheng, J Obeysekera, J Liu, et al.

KDD 2026 · arXiv:2506.04281

2026

Multi-Fidelity Flow Matching: Cascaded Refinement of PDE Solutions

S Chen, J Liu, H Tang, S Li

arXiv preprint arXiv:2605.16118

Contact

Get in touch

For research discussions, collaboration, or academic correspondence, please contact me by email.

sc25bg@fsu.edu Google Scholar