torch-molecule is a deep learning package for molecular discovery, designed with an sklearn-style interface for property prediction, inverse design and representation learning.

An AI-driven materials science toolkit based on PaddlePaddle.

Chemical representation learning paper in Digital Discovery

CrysXPP: An Explainable Property Predictor for Crystalline Materials (NPJ Computational Materials - 2022)

Open Knowledge Enrichment for Long-tail Entities, WWW 2020

Predicting properties of small molecules using MPNN on QM9 dataset

An integrated Python package for molecular descriptor generation, data processing, model training, and hyper-parameter optimization.

EGAT - Edge Featured Graph Attention Networks for Property Prediction

Machine learning algorithm implementation in materials science

AI-powered real estate platform for property price prediction, recommendations, and market insights using Streamlit and Machine Learning.

P2MAT - A python based user interface to predict melting point and boiling point of chemical compounds.

CPU-only perimeter sanity filter for AI-predicted quantum-chemical properties (dipole, HOMO/LUMO, gap). Agnostic of the source model; flags violations of Koopmans theorem, molecular point-group symmetry, topology and physical ranges. Heuristic linter, not a DFT calculator.

Pittsburgh Single Family Home Prediction with Non-Conventional Data Streams

NP-specific chemical language models (NPCLMs) for molecule generation and property prediction using state-space and transformer architectures.

Smart, user-friendly property valuation app leveraging bulk price prediction, market summaries, feature insights, and top picks ,powered by Streamlit and machine learning.

A TensorFlow-based machine learning framework for predicting zeolite properties, particularly framework density, using neural networks and composite building unit fingerprints

ML for predicting the compressive strength of SCMs

🧭 Australian Property Orientation Finder

Machine learning and predictive intelligence framework for materials behaviour, phase stability, and property forecasting.

Atomcraft — AI operating system for accelerated materials discovery. Generate crystal structures, predict properties, simulate DFT, design synthesis, and track experiments in a closed-loop platform.