Summary
Gaurav Deshmukh is a bioprocess modelling lead with eight years of experience applying computational modelling, data science, and first-principles methods to solve chemical engineering problems. He holds a PhD from Purdue where he combined DFT, chemical engineering fundamentals, and graph neural networks to design alloy electrocatalysts, and completed a postdoc at Northwestern focused on multiscale modelling of small molecules and polymers. At Lemnisca he now leads bioprocess modelling efforts, translating advanced simulation and ML tools into actionable process insights. He has hands-on experience building scientific code and materials informatics workflows (including GNNs in PyTorch) and has collaborated closely with experimental groups to validate predictions. Beyond research, he writes technical and creative pieces for a large Medium audience on programming and mathematical modelling, reflecting his ability to communicate complex ideas to diverse audiences. Based in Bengaluru, he blends deep theoretical rigor with practical process engineering and software development experience.
7 years of coding experience
Bachelor of Chemical Engineering (B. Chem. Engg.), Bachelor of Chemical Engineering (B. Chem. Engg.) at Institute Of Chemical Technology
Doctor of Philosophy - PhD, Chemical Engineering, Doctor of Philosophy - PhD, Chemical Engineering at Purdue University