Extensively used for data analysis, scientific computing, and automation across multiple research projects.

Primary operating system for development and scientific computing; proficient in shell scripting and system management.

Experienced with macOS for development, leveraging its Unix-based tools and system capabilities.

Familiar with Windows development environments and cross-platform toolchains for research applications.

Proficient in version control with Git; extensively used in collaborative and open source development.

Experienced in containerizing applications, setting up reproducible research environments, and managing multi-stage builds.

Skilled in C++ for performance-critical applications and simulation tools in scientific computing.

Experienced with legacy Fortran code for numerical analysis and scientific computation in nuclear physics.

Utilizes Emacs as an extensible editor for efficient coding and project management.

Leverages VSCode for its modern development workflow, rich extensions, and debugging support.

Expert in LaTeX for academic writing and producing high-quality scientific publications.

Proficient in Bash scripting for automation, data processing, and system administration on Unix-like systems.

Uses Markdown for clear documentation and formatting of technical notes and project descriptions.

Familiar with Geant4 for simulating particle interactions and modeling detector responses in nuclear physics.

Experienced with ROOT for data analysis in high energy and nuclear physics experiments.

Uses Jupyter notebooks for interactive data analysis, visualization, and reproducible research workflows.

Familiar with Microsoft Azure for deploying cloud solutions and managing scalable research workflows.

Familiar in TensorFlow for building and training machine learning models applied in research settings.

Familiar with PyTorch for deep learning research.