First and foremost, I love to solve real-world problems and like telling stories about them by quantifying the results. During my Ph.D. work, I developed skills to analyze and solve challenging problems in systematic ways. Utilizing my knowledge and skillsets, I tried to explain how superconductivity arises in high-temperature superconductors.
• More than 5 years of experience in material research using computational modeling, and numerical algorithms in a High-performance supercomputing environment.
Programming experience: Python, C/C++ (5+ years).
Data modeling framework: Scikit-Learn, Keras, TensorFlow, ML algorithms (2 years).
Visualization: Matplotlib, Seaborn, Gnuplot, Xmgrace, etc.
Scripting: Unix Commands, Bash Scripting, SQL queries.
Machine tools: Lathe, Milling, Band saw, and laboratory equipment like Laser, spectrometer, etc. (received Machine shop training)