Summary
Turash Pial is a postdoctoral scholar with a decade of experience applying physics-based modeling, molecular simulation, and machine learning to biofunctional materials, currently optimizing therapeutic payload distribution in drug-delivery nanomaterials at Johns Hopkins. He has led computational R&D in industry-academia collaborations on peptide self-assembly for antibody purification and has a strong track record in molecular dynamics studies of protein–ligand interactions and polyelectrolyte nanochannels. His work has secured significant computational and DOE funding and introduced machine-learning workflows to analyze simulation data, including custom clustering for hydrogen-bond definitions. Comfortable bridging theory and application, he combines high-performance computing grant-writing with hands-on simulation and algorithm development. Outside the lab he blends a curiosity for technology and philosophy, and his early leadership projects—like founding a university car team that pioneered jute-based composites—hint at a pragmatic, materials-driven creativity.
10 years of coding experience
7 years of employment as a software developer
Doctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at University of Maryland
Mechanical Engineering, Mechanical Engineering at Bangladesh University of Engineering and Technology
High School, High School at Rangpur Zilla School
English, Bengali