Hello!

I am a computational researcher with interest in solving chemical engineering problems (with a focus on adsorption and separation) using molecular modeling and simulations, mathematical modeling, and machine learning and optimization.

Motivations

Computers are quite an effective tool for studying various physical systems at certain conditions for properties/quantities of interest. Simulations and mathematical modeling (besides machine learning and other surrogate modeling methods) are amazing tools that help us to conduct these experiments. Besides, I like the elegance of mathematical models and the scalability and universality they provide.
Computation-based predictions are a great support pillar to real-life experiments. Besides, in many cases, experiments may have limitations such as challenges in creating a specific condition, synthesis of some rare material, scaling a method to large feature-space, or perhaps cost. For such cases, simulations or mathematical models can lead the way and fill the gap to guide investigations.

Professional Summary

I am currently working as a postdoctoral research scholar at Ganesan Polymer Physics Lab at the University of Texas at Austin (under Dr. Venkat Ganesan), in collaboration with Saudi Aramco. My main project is the development of machine learning models for predicting gas permeability in polymeric membranes, where I conceived and led the gas-conditioned message passing neural network (GC-MPNN), a model that can predict permeability for a gas species it has never seen during training. I also work on computational frameworks for designing new membrane polymers, and on differentiable molecular dynamics for coarse-graining polymer-gas systems.
My past research at University of Notre Dame (under Dr. Yamil J. Colón) was focused on applying molecular simulations (monte carlo and molecular dynamics), machine learning, and theory to understand adsorption, selectivity, and other properties in nanoporous systems. I worked on various adsorption and sensing applications ranging from oxygen, nitrogen to hydrogen sulphide, water and other. I also worked on modeling multi-component adsorption and applied various theoretical models such as ideal adsorbed solution theory, real adsorbed solution theory etc.
I have communicated my research work to a wide audience through speaking at conferences, publishing in journals, and of course many academic meetings.
My expertise is in this order: molecular simulations, mechanistic modeling, machine learning models, mathematical modeling, and optimization, first-principle calculations of small molecules. For more details, I encourage you to visit my research and publications page.
Below I have tried to summarize some major research topics I have worked on and the related skills I gained: