Research Method

Computation

I use first-principles electronic structure calculations and computational materials theory to predict material properties directly from atomic composition and crystal structure. This is important because computation provides a microscopic and quantitative foundation for understanding materials without relying solely on empirical intuition.

Simulation & Modeling

I employ simulation to study how electrons, spins, orbitals, and lattices interact across different length and time scales. Simulation is essential because it connects fundamental theory with realistic material behavior, helping reveal hidden mechanisms, test physical models, and guide experimental design.

Data-Driven ML & AI

I integrate machine learning and AI-assisted approaches into materials research to accelerate screening, identify patterns in complex data, and support inverse design. These tools are increasingly important because they allow us to move beyond slow trial-and-error discovery toward faster, scalable, and more predictive materials development.

Research Interests

Low-Dimensional Functional Materials

I study low-dimensional materials and interfacial systems where reduced symmetry, quantum confinement, and layer-dependent interactions create highly tunable physical properties. These materials provide a powerful platform for developing next-generation electronics, optoelectronics, and energy-related devices, because their behavior can often be controlled at the atomic scale.

Topological and Quantum Materials

My research explores topological and quantum materials with unconventional electronic and magnetic states. These systems are important because they host robust, symmetry-protected, and often exotic phenomena that can enable low-dissipation transport, novel spin functionalities, and new device principles beyond conventional semiconductors.

Correlated Magnetic Materials & Spin Functionalities

My research is interested in magnetic quantum materials in which competing interactions, frustration, and complex spin textures give rise to emergent behavior. Such materials are promising for spintronics and information technologies, because they may realize large magnetoresponse, self-organized spin control, and intrinsically functional magnetic architectures.

Strongly Correlated Materials

Strongly correlated materials offer a fertile ground for quantum computing because they can host highly entangled many-body states, unconventional excitations, and interaction-driven quantum phases that are inaccessible in weakly interacting systems. Understanding and designing these materials may open new routes toward robust quantum platforms, including topological qubits, quantum memory, and controllable quantum matter for future computing architectures.

Ferroelectric and Multiferroic Materials

I also work on ferroelectric and multiferroic materials, where electric polarization, magnetism, and structural degrees of freedom can be coupled and controlled. These materials are attractive for low-power memory, sensing, neuromorphic devices, and multifunctional electronics, because they allow information to be written, stored, and manipulated through multiple physical channels within a single material system.

...To be continued

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