Akash Vani

WORK HISTORY

EDUCATION

ABOUT AKASH VANI

I am a PhD researcher at the Max Planck Institute for Astrophysics, as part of the International Max Planck Research School at Ludwig Maximilian University of Munich, where I work at the intersection of computational modelling, data analysis, machine learning, and inference for complex systems. My research combines theory-driven and data-driven model development, simulation, inference, and large-scale data analysis to build, improve, and test physically motivated, self-consistent models in astrophysics. With a strong background in physics from Heidelberg University and Pune University, and research experience across multiple institutions in astrophysics, quantum computing, materials science, AI/ML, and code development, I have built a solid foundation in Python, C/C++, high-performance computing, and statistical methods. I enjoy developing computational workflows, analysing large and complex datasets, and designing robust, reproducible approaches that connect theory, simulation, and observation. A key part of my work involves developing and testing underlying physical models, alongside running and analysing large-scale simulations and multi-dimensional datasets in high-performance computing environments. I am particularly interested in interdisciplinary, data-intensive problems where scientific depth, computation, and modern statistical methods come together to address real-world challenges. I am always happy to connect around research, technology, scientific computing, and interdisciplinary collaboration. Explore more details on my website: https://a-vani.github.io/ Background image: ESA/Gaia/DPAC