Dr. Kritesh Kumar Gupta

Assistant Professor (Research Track Faculty)

Amrita School of Artificial Intelligence,

Amrita Vishwa Vidyapeetham, Coimbatore, India

Google Scholar: https://scholar.google.com/citations?user=T8qa1l4AAAAJ&hl=en

Email: g_kriteshkumar@cb.amrita.edu,

Research

Publications

Teaching & Mentoring

Research Interests:

Data-driven Materials Discovery, Digital Twin, Artificial Intelligence, Multiscale Material Modelling & Analysis, 2D materials and heterostructures, Multi-scale mechanics, Nano-mechanics, Stochastic analysis

Teaching Interests:

Introduction to AI and ML, machine learning, DeEp Learning, Materials Informatics, Computational Materials science, Uncertainty quantification, Nanomaterials and nanotechnology, computational programming, discrete mathematics

Skillset:

Applied MACHINE Learning, DATA DRIVEN DESIGN AND OPTIMIZATION, Molecular Dynamics Simulation (LAMMPS, GROMACS), Density Functional Theory (Quantum Espresso), Finite Element Analysis (ANSYS), Solid Modelling (CATIA), Programming (MATLAB, Python)

Welcome to my website!

I am currently working as an Assistant Professor in School of Artificial Intelligence at Amrita Vishwa Vidyapeetham, Coimbatore. I have completed my PhD from National Institute of Technology Silchar, India (2019 - 2023) with the specialization in Mechanical Engineering. My PhD research mainly utilized Physics informed Machine Learning Models to push the boundaries in the domain of Computational Materials Science (specifically atomistic simulations).

During my masters and PhD, I was awarded a fellowship from the Ministry of Education, Government of India, to perform teaching and research assistance. In this short tenure of my research experience, I actively participated in collaborative research with prestigious national and international research institutions, including IIT Kanpur (India), IIT Bombay (India), Swansea University (U.K.) and University of Southampton (U.K.). My research interests and expertise broadly lie in the domain of nanoscale mechanics, materials-informatics and computational characterization of the material system on different length scales. The research findings originating from our research group are regularly published in reputed journals (with publishers like RSC, IOP, Elsevier, Wiley, Springer, and Techno Press), conferences, and books. This website is intended to serve as a medium for sharing my research findings as well as for interaction with interested researchers. I would be delighted to share the source codes I have developed during the course of my research for further scientific development in relevant fields. Please do not hesitate to contact me.

The present focus of my research is on multi-principle element alloys (MPEAs) and their nanoscale investigation encompassing different critical aspects related to solid mechanics, materials, and structures. Please refer to different sections of this website for further details.

Machine Learning in Nanoscale Materials Design

Mission First

Panel Discussion on prospects of AI in Manufacturing