About the Instructor

Mahsa Sheikholeslami works at the intersection of pharmaceutical sciences and artificial intelligence, with a focus on AI-driven drug design and molecular discovery. During her Pharm.D. studies at Isfahan University of Medical Sciences, she became increasingly interested in how machine learning and deep learning could transform early-stage drug discovery and molecular optimization. This led her to independently develop strong computational and programming skills alongside her medical and pharmaceutical training.

Her work combines data-driven and physics-based approaches for small-molecule discovery, including molecular docking, molecular dynamics, reinforcement learning, and generative modeling. She has worked extensively with large-scale biomedical and chemical datasets such as ChEMBL, DrugBank, and PDB/RCSB, and has experience developing scalable computational pipelines for molecular optimization and virtual screening.

Mahsa is a researcher at the Regenerative Medicine Research Center in Isfahan, where she contributes to projects involving AI-assisted molecular generation, docking automation, and computational drug discovery workflows. She is also the author and co-author of multiple publications in AI-driven drug discovery and bioinformatics, including work on large language models and reinforcement learning for molecular design.