data Molecular data Python · PyTorch · RDKit
ChemAI Lab
A learning-oriented platform for machine learning and quantum-chemistry practice. Architecture direction is separated from completed evidence.
Module Architecture
15 stable module IDsfeatures Feature engineering models Model registry nn Neural networks pipeline Pipelines qm Quantum chemistry automl AutoML evaluation Evaluation xai Explainability viz Visualization hub Model hub pretrained Pretrained weights cli CLI config Configuration utils Utilities Learning Roadmap
Data and chemical representation
Start with reliable data structures, descriptors, and reaction-condition encoding.
Models and evaluation
Train baselines, compare metrics, and record failure conditions.
Mechanism and interpretation
Then connect quantum features and explainability to research questions.
Credibility Boundary
A machine learning & quantum chemistry driven chemical research platform. Integrates RDKit, PyTorch, Lightning across 15 subpackages for data, features, modeling, XAI, and QM interfaces.
Chemistry Foundation
Chemistry competition training supports later interest in organic chemistry, computational chemistry, and AI chemistry.
Evidence is limited to public certificates; undergraduate research work remains framed as direction and training.