Dr. Vivekanand Shukla is a computational materials physicist specializing in untangling the intricate connections between structures and properties of materials. His research revolves around harnessing computational techniques to investigate material behavior, strongly emphasizing energy-related applications and pioneering advancements in Density Functional Theory (DFT) methods. With a bachelor's degree in mathematics and a master's in physics from DDU Gorakhpur University, he pursued an MTech in materials science at the Indian Institute of Technology Kanpur. His master's thesis delved into synthesizing and characterizing Graphitic Carbon Nitride (g-C3N4) for diverse device applications. A recipient of the European Union's Erasmus Mundus scholarship, Dr. Vivek embarked on his doctoral journey in computational material physics in the materials theory division at Uppsala University, Sweden. His doctoral work involved employing first-principles DFT calculations, non-equilibrium Green’s function methods, ab initio molecular dynamics, and phonon dispersion analyses to investigate a wide array of nanomaterials, nanostructures, and biomolecular systems under varying conditions. His projects ranged from molecular electronics and 2D materials to energy storage and the intriguing anticarcinogenic properties of quantum dots. During his postdoctoral tenure at Chalmers University of Technology, Sweden, he was involved in developing and refining van der Waals (vdW) inclusive exchange-correlation functionals, notably the vdW-DF method. He helped introduce two range-separated hybrids (RSH) within vdW-DF, seamlessly integrated into the open-source Quantum Espresso code. During his second postdoctoral tenure at the Technical University Dresden, He delved into the transformative potential of heterostructures formed by novel magnetic 2D materials. This exploration included probing the interaction dynamics between 2D antiferromagnetic semiconductors, valley-polarized transition metal dichalcogenides, and superconductors. Currently contributing to the research community at IIT Ropar, his group is dedicated to tackling energy storage, energy harvesting, and nanotechnological challenges. Employing high-performance computational design, he seeks optimal material combinations based on stability, functionality, and practicality. He envisions integrating machine learning techniques and method development to explore novel functional materials and heterostructures, spanning applications from solar cells and light-emitting diodes to spintronics and quantum computing.