I work with Professor Marian when I was a Ph.D. student and has been investigated in various modeling problems.
I love to explore the physical mechanisms behind material phenomena. But I also use machine learning to let data speak. In UCLA, I worked on multi-scale modeling, fusion energy research, and advanced simulations for materials behavior.
I design and implemente data-driven modeling solutions. I'm passionate about using computational techniques like Kinetic Monte Carlo, Ab Initio etc. to solve real-world problems. I also enjoy coding in Java, Python, exploring new technologies, and applying machine learning to materials science.
When I'm not immersed in simulations, you'll probably find me experimenting with new coding projects or diving into the latest advancements in AI and computational modeling.
Exp 8 years
Exp 8 years
Exp 5 years
I am a computational science researcher with a strong background in modeling and simulation, specializing in computational techniques such as Kinetic Monte Carlo (KMC), Ab Initio (VASP), Machine Learning (ML), Finite Element Methods (FEM), and Molecular Dynamics (MD). With extensive experience in programming languages including Java, Python, PyTorch, JavaScript, and HTML, I develop and implement high-performance simulations to solve complex scientific and engineering problems. Passionate about computational research, I thrive at the intersection of physics, materials science, and software development.
My experiences honed my expertise in computational modeling, algorithm development, and data-driven material analysis..
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