DeepLenseSim (built on lenstronomy) requires substantial manual intervention for configuring parameters, managing outputs, and iterating on failures...

A preliminary pipeline on 30 COCA patients achieves Spearman rho = 0.986 between extracted calcium volume and Agatston score, with 11/15 features...

Exoplanet Atmosphere Characterisation plays a vital role in understanding chemical compositions, weather patterns and habitability of the exoplanet....

Strong gravitational lensing is a powerful probe of dark matter structure and cosmology, yet no foundation model exists that is purpose-built for...

Frameworks like PennyLane and Qiskit handle circuit construction and simulation well but provide almost no tools for measuring the quantum resources...

The proposal titled "Event Classification With Masked Transformer Autoencoders" aims to enhance particle jet tagging by developing a...

Symbolic regression (SR) aims to discover human-interpretable mathematical expressions from numerical data. While recent transformer models achieve...

In GSoC 2025, I prepared a novel physics-informed Swin Transformer to classify between lens models in simulated gravitational lensing images. The...

Vanilla MLP PINNs suffer from spectral bias and slow convergence, which directly limits the quality of shapes produced by PINN-based shape...

This proposal is for the ML4SCI GSoC 2026 project “Brain-to-Brain Decoder – Validating Neural Synchrony Patterns in Human Conversation.” The project...

This proposal presents a plan to develop hybrid quantum-classical models for classifying dark matter substructure from strong gravitational lensing...

The High Luminosity LHC program requires novel computational approaches to process massive datasets and identify rare signals. This project...

Hundreds of BSM Lagrangians have been proposed in the literature, but translating them into validated FeynRules .fr model files is still a manual,...

This project addresses a key challenge in High Energy Physics: efficient and accurate end-to-end reconstruction of particle properties from detector...

Astronomical observations of protoplanetary disks often contain noise that obscures important structures such as rings and gaps that may indicate...

Strong gravitational lenses are rare and scientifically valuable, but finding them in large imaging surveys requires automated methods. Furthermore,...

Accurate simulation of particle interactions within detectors is one of the most computationally expensive tasks in High Energy Physics (HEP). While...

This project develops linear-scale attention vision transformers for CMS End-to-End jet classification and proxy mass regression on 8-channel 99.1%...

Strong gravitational lensing is a key observational probe for dark matter and cosmology, but traditional ray-tracing simulations are computationally...

Strong gravitational lensing is among the most powerful observational probes of dark matter substructure. High-resolution lensing images encode the...

This project develops a high-precision, clinically viable pipeline for segmenting Coronary Artery Calcium (CAC) from non contrast cardiac CT scans...

At the CMS detector, jet images are stored at reduced resolution, discarding ~75% of total deposited energy. Standard super-resolution fails here...

This project aims to advance the SYMBA framework for calculating squared scattering amplitudes in high-energy physics by incorporating...

This project addresses the challenge of fast and accurate particle detector simulation in high-energy physics. Traditional Monte Carlo methods are...

This project addresses the challenge of limited and imbalanced datasets in coronary artery calcium (CAC) analysis, particularly for rare high-risk...

Generating simulations of calorimeter showers of interacting particles are a crucial step in analyzing the results of large scale experiments at LHC....

CAC segmentation is harder than it looks. Calcium deposits are tiny, sparse, and look identical to nearby bone a small miss doesn't just drop your...

This project aims to develop a multi-modal foundation model training pipeline for end-to-end particle reconstruction in the CMS experiment. Building...

Strong gravitational lensing is a powerful tool for studying dark matter, but machine learning models trained on simulated data often fail to...

This project aims to build a multimodal foundation model for exoplanet characterization by addressing the challenge of heterogeneous astronomical...

Building on the PINNDE proof-of-concept from GSoC 2025, I propose two directions: (1) systematic improvements to the PINN architecture and training —...

Variational quantum circuits are essential for near term quantum algorithms but designing them involves complex manual trial and error. This project...

This project proposed to develop a graph-based unsupervised Anomaly Detection model for identifying new physics at the LHC, combining contrastive...