- Hi, I’m Nitesh Kumar (@KMNitesh05), Postdoctoral Research Associate, Material Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California.
- I’m interested in Data-Driven Chemistry and Topological Data Analysis
- 📫 [email protected]
I have a broad range of interests in Computational & Data-driven Chemistry, Interfacial Chemistry, and Chemical Topology, particularly in its applications to Machine Learning method and workflow development. My work focuses on characterizing and elucidating fundamental concepts in Physical Chemistry and Chemical Physics that are essential for engineering chemical processes at industrial scales. I develop computational methods, theories, and software tools to uncover the underlying structure, fluctuations and electronic properties of complex chemical systems at interfaces and in confined environments. By integrating molecular simulations, algebraic topology, network theory, and advanced statistical mechanics, I design novel chemical descriptors and analytical techniques that provide deep insight into interfacial phenomena, reactivity, and molecular transport mechanisms. At PNNL, I studied the aggregation behavior of flow battery electrolytes as part of the Physical Biosciences group. At Oak Ridge National Laboratory, I studied fundamental chemistry at interfaces and supramolecular systems. Currently, I am affiliated with the Materials Science Division at Lawrence Berkeley National Laboratory, where I develop data-driven high-throughput models and machine learning interatomic potentials to investigate chemical reactions and physical processes at soft and condensed matter interfaces. My career aspirations are to conduct research in Physical Chemistry and to teach and train students.
Check out the sub-level set persistent homology codes I wrote for the analysis of adsorption-surfaces