Machine Learning for Science (ML4SCI)
Machine learning applications in science
- 152
- Projects
- 6
- Years accepted
- 33
- In 2026
Projects by year
1522026
33 acceptedShow
Agentic AI for Autonomous Gravitational Lensing Simulation Workflows
Accepted project · by Aatmaj28
DeepLenseSim (built on lenstronomy) requires substantial manual intervention for configuring parameters, managing outputs, and iterating on failures...
Radiomics Feature Extraction and Calcium Phenotype Discovery
Accepted project · by AdityaParashar
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 Characterization
Accepted project · by Anushree Upasham
Exoplanet Atmosphere Characterisation plays a vital role in understanding chemical compositions, weather patterns and habitability of the exoplanet....
[DeepLense] Foundation Model for Gravitational Lensing - WaveLens-JEPA
Accepted project · by Arnesh2212
Strong gravitational lensing is a powerful probe of dark matter structure and cosmology, yet no foundation model exists that is purpose-built for...
Quantum Resource Analysis and Benchmarking
Accepted project · by ashutoshm1771
Frameworks like PennyLane and Qiskit handle circuit construction and simulation well but provide almost no tools for measuring the quantum resources...
Event Classification With Masked Transformer Autoencoders
Accepted project · by Avishikta Bhattacharjee.
The proposal titled "Event Classification With Masked Transformer Autoencoders" aims to enhance particle jet tagging by developing a...
Using Next-Gen Transformers to Seed Generative Models for Symbolic Regression
Accepted project · by Dhruv1108
Symbolic regression (SR) aims to discover human-interpretable mathematical expressions from numerical data. While recent transformer models achieve...
DeepLense: Lens Finding for LSST Images
Accepted project · by DhruvSrivastava
In GSoC 2025, I prepared a novel physics-informed Swin Transformer to classify between lens models in simulated gravitational lensing images. The...
Physics-Informed Neural Network Shape Optimization
Accepted project · by George Liao
Vanilla MLP PINNs suffer from spectral bias and slow convergence, which directly limits the quality of shapes produced by PINN-based shape...
Brain-to-Brain Decoder: Leakage-Aware Validation and Interpretable CEBRA Mapping for Dyadic EEG
Accepted project · by Hubert Huang
This proposal is for the ML4SCI GSoC 2026 project “Brain-to-Brain Decoder – Validating Neural Synchrony Patterns in Human Conversation.” The project...
Hybrid Quantum-Classical Representation Learning for Dark Matter Substructure Classification
Accepted project · by Jen-Yu Chang
This proposal presents a plan to develop hybrid quantum-classical models for classifying dark matter substructure from strong gravitational lensing...
Quantum Sinusoidal Kolmogorov Arnold Networks for High Energy Physics
Accepted project · by Jorge Toral
The High Luminosity LHC program requires novel computational approaches to process massive datasets and identify rare signals. This project...
Agentic Lagrangian Extraction from the Literature ML4SCI – HEPSIM5
Accepted project · by kenwu
Hundreds of BSM Lagrangians have been proposed in the literature, but translating them into validated FeynRules .fr model files is still a manual,...
Linear attention vision transformers for end to end mass regression and classification
Accepted project · by Krish Malik
This project addresses a key challenge in High Energy Physics: efficient and accurate end-to-end reconstruction of particle properties from detector...
EXXA - Denoising Astronomical Observations of Protoplanetary Disks
Accepted project · by Krishan Yadav
Astronomical observations of protoplanetary disks often contain noise that obscures important structures such as rings and gaps that may indicate...
Machine Learning for Gravitational Lens Finding
Accepted project · by MichaelJiao
Strong gravitational lenses are rare and scientifically valuable, but finding them in large imaging surveys requires automated methods. Furthermore,...
Quantum Latent Diffusion Models for High-Resolution Simulation
Accepted project · by Miguel Pámanes
Accurate simulation of particle interactions within detectors is one of the most computationally expensive tasks in High Energy Physics (HEP). While...
Linear Attention Vision Transformers for CMS End-to-End Jet Classification and Mass Regression
Accepted project · by Naresh Meena
This project develops linear-scale attention vision transformers for CMS End-to-End jet classification and proxy mass regression on 8-channel 99.1%...
Neural Operators for Fast Simulation of Strong Gravitational Lensing
Accepted project · by PARAS BALANI
Strong gravitational lensing is a key observational probe for dark matter and cosmology, but traditional ray-tracing simulations are computationally...
Unsupervised Super-Resolution and Analysis of Real Lensing Images
Accepted project · by Prajwal Uday
Strong gravitational lensing is among the most powerful observational probes of dark matter substructure. High-resolution lensing images encode the...
Hybrid 3D CNN with Deformable Attention and FNO for CAC Segmentation
Accepted project · by Rajat Nandkumar Shedshyal
This project develops a high-precision, clinically viable pipeline for segmenting Coronary Artery Calcium (CAC) from non contrast cardiac CT scans...
Physics-Aware Super-Resolution of CMS Jet Images Using Transformer - Diffusion Architectures
Accepted project · by rajveer43
At the CMS detector, jet images are stored at reduced resolution, discarding ~75% of total deposited energy. Standard super-resolution fails here...
Physics-Informed Models for Squared Amplitude Calculation
Accepted project · by Ria Khatoniar
This project aims to advance the SYMBA framework for calculating squared scattering amplitudes in high-energy physics by incorporating...
Graph Representation Learning for Fast Detector Simulation
Accepted project · by Rushil Singha
This project addresses the challenge of fast and accurate particle detector simulation in high-energy physics. Traditional Monte Carlo methods are...
Data Augmentation Using Physics-Informed Plaque Growth Simulation
Accepted project · by Shriyam Baloni
This project addresses the challenge of limited and imbalanced datasets in coronary artery calcium (CAC) analysis, particularly for rare high-risk...
Physics Informed Neural Network Diffusion Equation (PINNDE)
Accepted project · by Sijil
Generating simulations of calorimeter showers of interacting particles are a crucial step in analyzing the results of large scale experiments at LHC....
Building and Comparing Segmentation Strategies for Coronary Artery Calcium CAC
Accepted project · by Soham Jadhav
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...
Foundation models for End-to-End event reconstruction
Accepted project · by Suryansh Mishra
This project aims to develop a multi-modal foundation model training pipeline for end-to-end particle reconstruction in the CMS experiment. Building...
Physics Guided Machine Learning on Real Gravitational Lensing Images
Accepted project · by Susmit
Strong gravitational lensing is a powerful tool for studying dark matter, but machine learning models trained on simulated data often fail to...
Foundation Models for Exoplanet Characterization
Accepted project · by Tanmay Singhal
This project aims to build a multimodal foundation model for exoplanet characterization by addressing the challenge of heterogeneous astronomical...
Physics-Informed Neural Network Diffusion Equation (PINNDE)
Accepted project · by Tina Shen
Building on the PINNDE proof-of-concept from GSoC 2025, I propose two directions: (1) systematic improvements to the PINN architecture and training —...
Quantum Circuit Design with LLMs
Accepted project · by Tomoya Hatanaka
Variational quantum circuits are essential for near term quantum algorithms but designing them involves complex manual trial and error. This project...
Deep Graph Anomaly Detection with Contrastive Learning for New Physics Searches
Accepted project · by Yeyang
This project proposed to develop a graph-based unsupervised Anomaly Detection model for identifying new physics at the LHC, combining contrastive...
2025
31 acceptedShow
Foundation models for End-to-End event reconstruction
Accepted project · by Aaditya Porwal
Current deep learning models for CMS particle reconstruction are often task-specific. This project aims to develop versatile foundation models by...
Super-Resolution and Analysis of Gravitational Lensing Images
Accepted project · by Aleksandr Duplinskii
This project develops an open-source, diffusion-based super-resolution (SR) pipeline for enhancing the resolution of gravitational lensing images....
Quantum Particle transformer for High Energy Physics Analysis at the LHC
Accepted project · by Alessandro Tesi
This proposal aims to build upon and expand the progress made in recent years on Quantum Vision Transformers (QViTs) for High Energy Physics (HEP)...
Discovering Hidden Symmetries in CMS Calorimetric Data via Semi-Supervised Learning
Accepted project · by Alexandra Murariu
This project tackles the challenge of learning hidden symmetries in complex, high-dimensional physics data using modern machine learning techniques....
Unsupervised super-resolution and analysis of observed lensing images
Accepted project · by Anirudh Shankar
Machine learning based analyses are proving to be very potent in understanding complex physical systems. This project aims to develop a reinforcement...
Q-MAML for Variational Quantum Algorithms for High Energy Physics Analysis at the LHC
Accepted project · by arnavsinghal09
This project focuses on developing a new machine learning approach called Quantum Model-Agnostic Meta-Learning (Q-MAML) specifically for high-energy...
Physics Guided Machine Learning on Real Lensing Images
Accepted project · by Ashutosh Ojha
The project aims to develop a physics-informed neural network framework to infer the properties and distribution of dark matter in the lensing galaxy...
Discovery of hidden symmetries and conservation laws
Accepted project · by Avishikta_Bhattacharjee
Because of its cylindrical shape, the Compact Muon Solenoid (CMS) detector has intrinsic rotational symmetries. Data analysis can be greatly improved...
Physics-Informed Performer for Symbolic Squared Amplitudes in HEP
Accepted project · by Ayush Mishra A
In high-energy physics (HEP), automating the symbolic computation of squared amplitudes is essential for predicting cross-sections and validating...
A Diffusion-Based Deep Learning Framework for Denoising Protoplanetary Disk Observations
Accepted project · by Chukwunwogor Faithful
This project proposes ProtoDiff, a diffusion-based deep learning model designed to denoise astronomical observations of protoplanetary disks from...
This project addresses the challenge of data drift in high-energy physics, where evolving detector conditions cause AI models for data quality...
This project aims to develop and optimize deep learning algorithms for identifying strong gravitational lenses within wide-field surveys such as the...
Exoplanet Atmosphere Characterization
Accepted project · by Gaurav Shukla
This project intends to develop cutting-edge machine-learning tools for spectral analysis to characterize the atmospheres of exoplanets. The project...
This project aims to uncover fundamental symmetries and conserved laws hidden within complex high-energy physics data (specifically CMS datasets). It...
My project focuses on developing diffusion models for gravitational lensing simulations. I will implement and evaluate various diffusion-based...
Foundation Model for Gravitational Lensing
Accepted project · by J Rishi
This project aims to develop a vision foundation model for strong gravitational lensing by comparing various self-supervised learning techniques,...
Latent Neural Signatures in Clinical vs. Neurotypical Dyads: A CEBRA Pipeline
Accepted project · by jeffreyhuang1009
This project aims to develop a cutting-edge computational pipeline—"Latent Neural Signatures in Clinical vs. Neurotypical Dyads: A CEBRA Pipeline"—to...
The project, "Data Processing Pipeline for the LSST," is designed to bridge the gap between the LSST data ecosystem and DeepLense's deep learning...
Problem: Symbolic regression is crucial for discovering underlying physical laws from data, but traditional methods are often computationally...
Neural Harmony – Decoding Social Interactions with CEBRA-based framework for analysing EEG data
Accepted project · by Maria Glushanina
This project aims to decode the neural dynamics of social interactions by adapting the CEBRA framework to analyze dyadic EEG data. Focusing on...
Diffusion models have experienced rapid growth in usability, availability, and research. The classical algorithm consists of two main parts: a...
Implementation of Quantum Generative Adversarial Networks to Perform HEP Analysis at the LHC
Accepted project · by Maya Ma
This project aims to implement a Quantum Generative Adversarial Network (QGAN) using the Pennylane framework to explore the advantages of quantum...
Building a Foundational Model for Symbolic Regression in High Energy Physics
Accepted project · by Miche
This project proposes the development of a foundational model for symbolic regression tailored to high energy physics (HEP). Symbolic regression can...
State-space models for squared amplitude calculation in high-energy physics
Accepted project · by Prasanth Naidu
One of the most important physical quantities in particle physics is the cross section, or a probability that a particular process takes place in the...
Quantum Kolmogorov-Arnold Networks for High Energy Physics Analysis at the LHC
Accepted project · by Ria Khatoniar
This project explores Quantum Kolmogorov–Arnold Networks (QKANs) as a novel and interpretable architecture for analyzing collider data from the...
Next-Generation Transformer Models for Symbolic Calculations of Squared Amplitudes in HEP
Accepted project · by Ritesh Bhalerao
In particle physics, a cross section is a measure of the likelihood that particles will interact or scatter with one another when they collide. It is...
Graph Representation Learning for Fast Detector Simulation
Accepted project · by Rushil Singha
High-fidelity detector simulations are critical for accurate analysis in particle physics, but traditional Monte Carlo-based methods are...
This project aims at incorporating Physics informed neural network (PINN) based ODE solvers into the Diffusion probabilistic models(DPM) , to build a...
Quantum Machine Learning For Exoplanet Characterization
Accepted project · by Sourish Phate
This project investigates the potential of quantum machine learning methods, such as quantum feature encoding and quantum neural networks (QNNs), for...
The project aims at building foundational models suitable for characterizing the vast astronomical data and emphasizing their use case for various...
A Self-Supervised, Physics-Informed Hybrid Transformer Framework for Multi-Tasks in HEP
Accepted project · by Thanh P Nguyen
Accurately classifying particle collisions—whether distinguishing quark- from gluon-initiated jets or isolating Higgs events from complex...
2024
26 acceptedShow
- Learning quantum representations of classical high energy physics data with contrastive learningSanya Nanda
- Non-local GNNs for Jet ClassificationTanmay Bakshi
- Quantum transformer for High Energy Physics Analysis at the LHCAlessandro Tesi
- Superresolution for Strong Gravitational LensingAtal
- Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger SystemVishak K Bhat
- Learning Representation Through Self-Supervised Learning on Real Gravitational Lensing Imagesyaashwardhan
- Equivariant quantum neural networks for High Energy Physics Analysis at the LHCLazaro Raul Diaz Lievano
- Masked Auto-Encoders for Efficient E2E Particle Reconstruction & Compression for CMS ExperimentLokesh Badisa
- Resilient Physics-Informed Anomaly Detection and Inference of Lensing Images on Sparse DatasetsAnirudh Shankar
- Quantum Graph Neural Networks for High Energy Physics Analysis at the LHCJogi Suda Neto
- QMLHEP3: Learning quantum representations of classical HEP data with contrastive learningduydl
- Equivariant Vision Networks for Predicting Planetary Systems' ArchitecturesAlexandra Murariu
- Physics-Guided Machine LearningAshutosh Ojha
- Evolutionary and Transformer Models for Symbolic RegressionAryamaan Thakur
- Quantum Generative Adversarial Networks for Monte Carlo SimulationsLuis Rey
- Diffusion Models for Gravitational Lensing SimulationJ Rishi
- Learning quantum representations of classical high energy physics data with contrastive learningAmey Bhatuse
- Implementation of Quantum Generative Adversarial Networks to Perform HEP Analysis at LHCAdithya Penagonda
- Exoplanet Atmosphere CharacterizationGaurav Shukla
- Quantum Diffusion Model for High Energy PhysicsMasha
- Learning Representation Through Self-Supervised Learning on Real Gravitational Lensing ImagesSreehari Iyer
- Masked Auto-Encoders for End-to-End Particle Reconstruction and Compression for the CMS ExperimentShashank Shekhar Shukla
- Self-Supervised Learning for End-to-End Particle Reconstruction for the CMS Experiment3podi
- Evolutionary and Transformer Models for Symbolic RegressionSamyak Jha
- Transformer Models for Symbolic Calculations of Squared Amplitudes in HEPRitesh Bhalerao
- Quantum Graph Neural Networks for High Energy Physics Analysis at the LHCHaemanth V
2023
23 acceptedShow
- Diffusion Models for Fast Detector SimulationAkshit Choudhari
- Graph Neural Networks for End-to-End Particle Identification with the CMS ExperimentAnthony Song
- Equivariant Quantum Neural Networks for Continuous Symmetry in High Energy PhysicsCosmos Dong
- Exploring the underlying symmetries in particle physics with equivariant neural networksDiptarko Choudhury
- Prediction of High Energy Particle Kinematics via Masked AutoencodingEric Reinhardt
- Quantum transformer for High Energy Physics Analysis at the LHCEyup
- Equivariant Neural Networks for Dark Matter Morphology with Strong Gravitational LensingGeo Jolly
- Quantum Graph Neural Networks for High Energy Physics Analysis at the LHCGopal Ramesh Dahale
- Identifying the Physical Process of Planet Formation (EXXA)Jason Terry
- Super-Resolution for Strong Gravitational LensingK Pranath Reddy
- Vision Transformers for End-to-End Particle Reconstruction for the CMS ExperimentKa Wa Ho
- Self-Supervised Learning for Strong Gravitational LensingKartik Sachdev
- Lensiformer: A Physics-Informed Vision Transformer Architecture for Dark Matter MorphologyLucas José
- Quantum Transformers for HEP Analysis at the LHCMarçal Comajoan Cara
- Finding Exoplanets with Astronomical ObservationsMihir Tripathi
- Symbolic empirical representation of squared amplitudes in high-energy physicsNeeraj Anand
- FASEROH : Building seq2seq model for mapping histograms to empirical symbolic representationsPushpdeep Singh
- Invariant and Equivariant Quantum Graph Attention Transformers for HEP Analysis at the LHCRoy T. Forestano
- Deriving planetary surface composition from orbiting observations from spacecraftSandeepan Dhoundiyal
- Updating the DeepLense PipelineSaranga Kingkor Mahanta
- Quantum Generative Adversarial Networks for HEP event generation the LHCToMago
- SYMBA - Symbolic empirical representation of squared amplitudes in high-energy physicsVBaules
- Self-Supervised Learning for Strong Gravitational Lensingyaashwardhan
2022
20 acceptedShow
- Finding Exoplanets with Astronomical ObservationsJack Mcnish
- Implementation of QGANs to Perform High Energy Physics Analysis at the LHCAbhay Kamble
- Anomalies DetectionAmal Saif
- Finding Exoplanets with Astronomical ObservationsMahdi Boulila
- Gravitational Lens Finding for Dark Matter Substructure PipelineMriganka Nath
- Quantum Generative Adversarial Neural Networks for High Energy Physics Analysis at the LHCAmey Bhatuse
- Updating the DeepLense PipelineSaranga Kingkor Mahanta
- Vision Transformers for End-to-End Particle Reconstruction for the CMS ExperimentDiptarko Choudhury
- Transformers for Dark Matter Morphology with Strong Gravitational LensingKartik Sachdev
- Finding Exoplanets with Astronomical ObservationsJason Terry
- Symbolic empirical representation of squared amplitudes in high-energy physicsMarco Knipfer
- Quantum Variational Autoencoders for HEP Analysis at the LHCToMago
- Graph Neural Networks for End-to-End Particle Identification with the CMS ExperimentJai Bardhan
- End-to-End Deep Learning Reconstruction for CMS ExperimentPurva Chaudhari
- Transformers for Dark Matter Morphology with Strong Gravitational LensingArchil Srivastava
- Graph Neural Networks for End-to-End Particle Identification with the CMS ExperimentXin Yi
- Equivariant Transformers for Decoding Dark Matter with Strong Gravitational LensingYurii Claus
- Quantum Convolutional Neural Networks for High Energy Physics Analysis at the LHCGopal Ramesh Dahale
- Fast Accurate Symbolic Empirical Representation of HistogramsAaron Mayer
- Deep Regression ExplorationZhongchao Guan
2021
19 acceptedShow
- Machine Learning Model for the Planetary AlbedoSofia Strukova
- Equivariant Neural Networks for Dark Matter Morphology with Strong Gravitational LensingApoorva Vikram Singh
- Graph Neural Networks for Particle Momentum Estimation in the CMS Trigger SystemEmre Kurtoglu
- On the potential of graph-based models in High Energy PhysicsAli A. Hariri
- Machine Learning Model for the Albedo of MercuryGeorgios Pipilis
- Direct Objective Function for Anomaly DetectionYurii Halychanskyi
- Background Estimation with Neural AutoRegressive FlowsMuhammad Ehsan ul Haq
- End-to-End Deep Learning Reconstruction for CMS ExperimentPurva Chaudhari
- Graph Neural Networks for End-to-End Particle Identification with the CMS ExperimentShravan Chaudhari
- Normalizing Flows for Fast Detector SimulationAditya Ahuja
- Quple - Quantum GANChi Lung Cheng
- Dimensionality Reduction for Studying Diffuse Circumgalactic MediumJakub Rybak
- Quantum Convolutional Neural Networks for High-Energy Physics Analysis at the LHCEraraya Ricardo Muten
- Background Estimation with Neural Autoregressive Flows ProposalSinan Gençoğlu
- Machine Learning for Turbulent Fluid DynamicsAmey Varhade
- End-to-End Deep Learning Regression for Measurements with the CMS ExperimentAnis Ismail
- Decoding quantum states through Nuclear Magnetic ResonanceAnantha Rao
- Domain Adaptation for Decoding Dark Matter with Strong Gravitational LensingMarcos Tidball
- Uncovering the Enigma of Type-Ia Supernovae: Thermonuclear Supernova Classification via their Nuclear SignaturesSophia He
Public proposals
4- gsoc proposal arnav2026 · kapoor · Rejected · from satwiksps/GSoC_archive_2026
- Neural Operators for Fast Simulation of Strong Gravitational Lensing2026 · Metrex-Nova · Accepted · from satwiksps/GSoC_archive_2026
- Physics-Informed Models for Squared Amplitude Calculation2026 · Accepted · from satwiksps/GSoC_archive_2026
- diffusion proposal hamees2025 · Accepted · from SammanSarkar/GSoC_archive_2025
Read them for structure, not to copy. All proposals for Machine Learning for Science (ML4SCI).
