We are an independent research group focusing on applying message-passing neural networks to model potential energy surfaces and point cloud–based deep learning methods for drug discovery.
> B.Sc. Applied Chemistry — University of Tehran
> M.Sc. Physical Chemistry — Sharif University of Technology
Supervisor:
Prof. Zahra Jamshidi (Link)(Link)
Professor of Physical Chemistry Department of Chemistry Sharif University of Technology
E-mail: mahdi.zardoshti02@sharif.edu
CV: [Download Link]
LinkedIn: [Link]
X: [Link]
GitHub: [Link]
> M.Sc. Biochemistry— University of Tehran
Supervisor:
Prof. Reza Yousefi (link)
Professor of Biochemistry, University of Tehran – Institute of Biochemistry & Biophysics(IBB)
E-mail: Reza.zardoshti@ut.ac.ir
CV: [Download Link]
LinkedIn: [Link]
GitHub: [Link]
>>> Point cloud–based deep learning for predicting drug efficacy on the VEGFR2 protein.
>>> Generative point-cloud models combined with transformer-based SMILES captioning for de novo drug design.
>>> Machine-learning–enhanced molecular dynamics for infrared (IR) spectral simulation.
>>> Learning the Potential Energy Surface of Ag Clusters with Active Learning–Enhanced Interatomic Potentials.
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| # | Methods | MPNN | CADD |
|---|---|---|---|
| 1 | PCA/FPS | SchNet | PointNet |
| 2 | GPA/SVM | PhysNet | PointNet++ |
| 3 | Active Learning | FieldSchNet | GNN |
| 4 | Transfer Learning | PAINN | FoldingNet |
| 5 | Transformer/LSTM |
Research Interests
> Geometric Deep Learning
> Point Clouds-based Deep Learning
> Message Passing Neural Network (MPNN)
> Generative Models
Home | Research | Contact
Deep Learning for Computational Chemistry and Drug Design
Zardosht Research Group
Tehran/Iran
