Dr. Kritesh Kumar Gupta
(M.Tech., PhD)
Assistant Professor,
Center for Computational Engineering and Networking,
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,
Just developing a machine learning model is enough?
Deployment of such models can do wonders. Want to know how?, visit
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:
Advanced Materials Science, Computational Materials science, Nanomaterials and nanotechnology,
machine learning, computational programming, discrete mathematics, materials-informatics,
uncertainty quantification
Skillset:
Molecular Dynamics Simulation (LAMMPS, GROMACS), Density Functional Theory (Quantum Espresso), Finite Element Analysis (ANSYS), Solid Modelling (CATIA), Programming (MATLAB, Python), Machine Learning
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.
Research highlights
The strategic positioning of defects in CNT can be utilized for programming its spatio-mechanical properties. Recenlty, published a paper titled 'Random topological defects in double-walled carbon nanotubes: On characterization and programmable defect-engineering of spatio-mechanical properties ' read about it here.
How machine learning can be helpful in designing the soil-stabilization framework ensuring the utilization of sustainable rice husk ash (RHA) replacing the lime content. Recently published a paper in prestigious ASCE journal, read the article here.
How graphene coating can further enhance the nano-indentation response of Al0.3CoCrFeNi HEA. What is the underlying mechanism of deformation, dislocation, and structural transformation, read about it here.