Koushik Pal PhD

Background

About Koushik Pal PhD

• A condensed matter physicist and a materials scientist. Interested to explore the physics of materials using theory and quantum simulation AI/ML and materials informatics. • Strong domain expertise in quantum materials semiconductors electron-phonon physics thermal transport phenomena thermoelectrics photovoltaics catalysis alloys and nano-materials • Involved in developing automatic phase mapping tools to augment the data-analysis from high-throughput experiments to expedite new materials discovery • Extreme attention to details in modeling data handling data management data analysis • Technical expertise with machine learning statistical learning and data-driven modeling • Experienced in designing autonomous workflow for the design and discovery of novel materials utilizing machine learning method such as graph neural network • Highly enthusiastic about quantum computation and interested in applying my materials modelling skill to advance the field I have a strong interest in and a practioner of data science for scientific and engineering applications multi-scale materials modeling and scientific code development. My data science skills include usage and application of tools such as Mathematica Python NumPy SciPy TensorFlow Scikit-learn Pandas Matminer Matplotlib Seaborn Gnuplot Jupyter-notebooks Google Colab Git Unix/Linux/Mac OS. I am highly skilled in performing calculations based on density functional theory (DFT) ab initio molecular dynamics (AIMD) and effective model Hamiltonian. My favorite scientific modeling codes libraries and database include Vienna ab initio Simulation Package (VASP) Quantum Espresso WIEN2K Wannier90 pymatgen qmpy ASE Open Quantum Materials Database (OQMD) Materials Project (MP) and NOMAD. I have published 40 papers in reputed peer-reviewed scientific journals such as Physical Review Letters Applied Physics Letters npj Computational Materials Journal of the American Chemical Society Angew Chem Chemistry of Materials Physical Review X Nature Communications etc. on a variety of topics related to quantum materials and energy sustainability utilizing state of art theory ‌ computational methods experiment and data analysis.