I'm a third-year BS-MS Physics student at the Indian Institute of Science Education and Research, Mohali (IISER-M). My work sits at the intersection of theoretical physics, computational methods, and machine learning.

• High-Energy Physics & Lattice QCD: Currently working on simulating the deconfinement phase transition in SU(2) Lattice Gauge Theory.
• Machine Learning in Physics: Exploring the applications of Graph Neural Networks (GNNs) and Particle Transformers to handle sparse detector data.
• Research Interests: Quark-gluon plasma, BSM phenomenology, CP symmetry breaking, Higgs production, flavor violations, and many-body quantum physics.
• Open Source: Exploring contributions to organizations like ML4Sci, CERN-HSF, and The Julia Project.

• Languages: C++, Python
• Environment: Linux (Ubuntu, Fedora, Zorin OS)
• Tools & Workflow: Command Line, Obsidian (Resource Collection & Reference)

When I'm not running simulations or reading papers, I am extremely passionate about:

• 🌍 Geopolitics & Foreign Policy Analysis
• 📜 Political History & Culture
• 🧠 Religious Philosophy

• LinkedIn: koushik-v-680801285

⭐️ Feel free to reach out if you want to chat about computational physics, machine learning applications in high-energy physics, or history and philosophy!