Hohmann transfer orbit modeling with Hall-Effect thruster integration, implemented in Python, C++ and MATLAB with 3D visualization and validated delta-V calculations for LEO to GEO missions

A Physics-Informed Neural Network (PINN) pipeline that demonstrates the Dark Energy inverse problem and simulates the Quantum Vacuum Catastrophe.

Fourier-based Low-Frequency Spectral Dynamics Network for differentiable spectral learning, early-warning analysis, and physics-aware modeling of complex dynamical systems.

Hybrid Physics-Informed Neural Network for Robot Joint State Prediction and Parameter Identification

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Beam Weaver is a physics-informed SAC agent to implement event-by-event stochastic photon transport in water.

Physics-informed image denoiser built from scratch — Poisson-Gaussian noise modeling, residual CNN, no pretrained weights or APIs

A flexible PyTorch Lightning framework for climate forecasting, featuring a customizable, knowledge-aligned latent diffusion model for high-resolution predictions.

Architecting stateful Agentic AI, aerospace simulations, SiN chip design workflows, and specialized deep-tech/medical LLM data pipelines

Modeling the Tumor Microenvironment (TME) as a many-body gravitational system. A synthetic data engine that applies astrophysics principles (N-Body dynamics) to simulate immune-tumor topology and generate ground-truth spatial data.

Physics-informed AI system for predicting aircraft bird strike risk using impact force calculations and machine learning techniques.

Physics-Anchored Deepfake Detection Framework

Predicting traffic accident risk using Physics-Informed Feature Engineering and Advanced Stacking Ensemble (XGBoost, LightGBM, CatBoost).

SymRegLab — Interactive Symbolic Regression & AI Equation Discovery Laboratory. 6 modules: GP evolution, physics rediscovery, expression trees, Pareto front, dimensional analysis, benchmark arena. Zero dependencies.