Official repo for "The impact of internal variability on benchmarking deep learning climate emulators" in JAMES25 (public)

Python Low-Code System Solutions

A Genetic Algorithm (GA) / Discrete Particle Swarm Optimization/ Hybrid (GA-PSO) for nuclear fuel optimization using ML surrogates (DNN, KNN, Random Forest, Ridge) and OpenMC. Optimizes fuel loading patterns for a target k-eff and minimal Power Peaking Factor (PPF).

Performance Modeling of Data Storage Systems Using Generative Models, IEEE Access, vol. 13, pp. 49643-49658, 2025, doi: 10.1109/ACCESS.2025.3552409

This repository provides an implementation of algorithmic support for dynamic pricing based on surrogate ticket demand modeling for a passenger rail company on open data.

A novel neural network for effective learning of highly impulsive/oscillatory dynamic systems by jointly utilizing low-order derivatives

Python code for running the numerical experiments in the paper "Neural Network Accelerated Implicit Filtering: Integrating Neural Network Surrogates With Provably Convergent Derivative Free Optimization Methods" by Brian Irwin, Eldad Haber, Raviv Gal, and Avi Ziv.

Physics-constrained TMM-SVR surrogate pipeline for PDMS thin-film infrared emissivity prediction

Uncertainty quantification, Bayesian inference, and scientific ML for physical/biological models

Master’s thesis project on AI-based crowd evacuation modeling using the SWIM algorithm, integrating simulation data and neural network surrogates.

Monte Carlo neutron transport simulation with neural-network surrogate models for fast transmission prediction.

Open benchmark of FNO, conditional-diffusion (U-Net & DiT), and ensemble-UQ surrogates for two-phase porous-media flow (CO2 sequestration).

Unified GPU pipeline merging Taichi LBM (LES + FSI) and JAX to train real-time neural surrogates for unsteady bio-aerodynamics via continuous online learning.

Python orchestrator for ROM, design of experiments, and optimization workflows.

CARDIOKOOP - Control-aware Koopman deep learning framework for real-time hemodynamic forecasting and cardiovascular digital twin applications.

Reduced Order Modeling framework for predictive modeling with neural networks, Gaussian processes, and RBFs.

Foundation-model-inspired spatiotemporal neural operator for CFD-based offshore structural response prediction with synthetic CFD data, physics-calibrated residual inference, explainability, tests, and figures.

Development of a surrogate-assisted multi-objective optimization framework for thermal systems using machine learning models and evolutionary algorithms such as NSGA-II.

GNN surrogate for 2D shallow water simulations

A baseline for building a PyTorch surrogate (Phase 1/Phase 2) that rapidly predicts hydrogen recycling distributions using W-H interaction data generated with LAMMPS.