| Summary |
In recent years, modern AI/ML methods have revolutionized and have had phenomenal success in many technology areas such as computer vision, natural language processing, machine translation, speech recognition, autonomous driving, etc. Availability of high performance GPU accelerators, historical data and development of new algorithms/libraries have fueled such a surge. This has inspired chemists and biologists to apply these algorithms to problems in molecular science that are traditionally tackled using physics-based methods. The past few years have witnessed ML based solutions in molecular science that are more efficient and accurate compared to traditional methods. In this talk, I will initially introduce the philosophy of machine learning methods in the context of the three paradigms of research (experiments, theory and computations). I will also introduce the direct and inverse problems in the context of molecular/material design. Secondly, we will discuss development of ML algorithms for some direct problems that include predicting DFT energies/forces, solvation free energies and protein binding sites. In the last part of the talk, we will discuss inverse problem solving and explore some methods that may enable self-driving chemistry laboratories. We will discuss methods that are capable of generating novel molecules based on a chemist’s requirement (like ChatGPT for text), and how AI is capable of elucidating structures given molecular spectra as inputs. Finally, we will briefly discuss how the informatics based approaches could impact the way we do research in computational molecular science.
Brief Bio: Deva finished his PhD from Pondicherry University/IICT Hyderabad followed by a postdoctoral fellowship at the University of Maryland. He is currently Professor and Head of the Center for Computational Natural Sciences and Bioinformatics, and Project Director, IHub-Data, a Technology Innovation Hub on Data Driven Technologies. His major research interests are in the areas of applying computational methods for studying chemical and biological systems/processes. Recently, his group has made significant contributions in applying modern AI/ML techniques for molecular science research. He has received Indian National Science Academy Young Scientist Medal, Young Associate Fellowship from Indian Academy of Sciences, Innovative Young Biotechnologist Award, Distinguished Lectureship Award by CSJ, JSPS Fellowship, Chemical Research Society of India Medal and Google Impact Scholar award.
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