Naman Katyal
Postdoctoral Researcher
Contact
Naman Katyal
Postdoctoral Researcher
I am a postdoctoral researcher in the Materials Science Division at Lawrence Berkeley National Laboratory. My primary project involves developing computational models using electronic structure theory and machine learning to study phase transitions in materials for materials and melts.
I am a Ph.D. from the University of Texas @ Austin with Graeme Henkelman. I specialize in the computational modeling of electronic structures and developing machine learning force fields in energy storage and conversion applications. I am looking for projects where I can develop computational tools to solve challenging problems in a progressive environment.
My research involves working closely with experimental material characterization. I have extensive experience in modeling EXAFS, Raman, UV-Vis, IR, and XRDS from electronic structure methods that can be compared directly with experimental characterization. I believe in developing computational models which resemble experimentally synthesized material as closely as possible to make accurate predictions. I enjoy discussing science with everyone because there is so much I don't know, and fun to exchange ideas.
I also develop software for machine learning force fields for materials modeling. @ Henkelman group, I was a part of the team developing the atom-centered neural network package PyAMFF, which uses Behler-Parrinello fingerprints as inputs and produces energies and forces for structure. More than that, I have worked on developing tools to analyze force field models during training, selection of fingerprints, SHAP analysis, and selection of data points for training to make a force-field explainable, transferable, and as generic as possible. There is a long way to go to achieve all three goals listed above, and I am always looking for new methodologies from different sections of the artificial intelligence community, which is bigger than simple machine learning.
Other interests: I love reading books, watching football (Premier League and NFL), camping, paddle boarding, and traveling. I am always looking for an opportunity to travel to a new city or country and explore around.
If you made it all the way to the end, then I would like to leave you with a quote from Sapiens by Yuval Noah Harari, which I believe is truly inspiring: A theory that enables us to do something new constitutes knowledge. I think this quote sums up all the development humankind has achieved in everything and holds the key to our future.
I am a Ph.D. from the University of Texas @ Austin with Graeme Henkelman. I specialize in the computational modeling of electronic structures and developing machine learning force fields in energy storage and conversion applications. I am looking for projects where I can develop computational tools to solve challenging problems in a progressive environment.
My research involves working closely with experimental material characterization. I have extensive experience in modeling EXAFS, Raman, UV-Vis, IR, and XRDS from electronic structure methods that can be compared directly with experimental characterization. I believe in developing computational models which resemble experimentally synthesized material as closely as possible to make accurate predictions. I enjoy discussing science with everyone because there is so much I don't know, and fun to exchange ideas.
I also develop software for machine learning force fields for materials modeling. @ Henkelman group, I was a part of the team developing the atom-centered neural network package PyAMFF, which uses Behler-Parrinello fingerprints as inputs and produces energies and forces for structure. More than that, I have worked on developing tools to analyze force field models during training, selection of fingerprints, SHAP analysis, and selection of data points for training to make a force-field explainable, transferable, and as generic as possible. There is a long way to go to achieve all three goals listed above, and I am always looking for new methodologies from different sections of the artificial intelligence community, which is bigger than simple machine learning.
Other interests: I love reading books, watching football (Premier League and NFL), camping, paddle boarding, and traveling. I am always looking for an opportunity to travel to a new city or country and explore around.
If you made it all the way to the end, then I would like to leave you with a quote from Sapiens by Yuval Noah Harari, which I believe is truly inspiring: A theory that enables us to do something new constitutes knowledge. I think this quote sums up all the development humankind has achieved in everything and holds the key to our future.
