Our current research interests are:

1. Fabrication of 2D Materials-based Devices
   This activity focuses on the fabrication and characterization of 2D materials-based devices in a cleanroom environment. We explore materials such as Transition Metal Dichalcogenides (TMDs) for the development of advanced nanoelectronics devices such as FETs and memories. Our research aims to understand the properties of these materials to optimize their performance in real-world applications.
   
   

2. Simulation and Modelling of 2D Materials-based Logic and Memory Devices
   In this area, we focus on simulating and designing logic and memory devices based on 2D materials using advanced first-principles simulations and TCAD modelling tools. Our simulation models are validated through experimental data and atomistic-level simulations to ensure accuracy and reliability in device design.
   
   

3. Machine Learning Approaches for High-Speed Simulations
   We apply machine learning techniques to accelerate the simulation of 2D materials-based devices. By leveraging machine learning algorithms, we aim to reduce the computational cost and time required for simulating complex devices, enabling faster prototyping and optimization of nanoelectronics systems.
   
   

4. Experimental-Modeling Integration for Device Performance Optimization
   Our group is committed to bridging the gap between theoretical predictions and experimental demonstrations. We focus on developing models that can guide experimentalists in designing better devices and provide insights into how new technologies will perform in real-world scenarios.
   
   

5. Development of Unconventional Computing Devices
   We are also exploring the design and simulation of 2D materials based non-charge-based computing devices, such as quantum bits (qubits) and bio-inspired devices. This research aims to contribute to the future of computing by designing devices that go beyond traditional charge-based electronics, enabling the development of quantum computing and innovative bio-inspired technologies.
   
   

Our group is at the forefront of developing 2D materials-based devices, combining cleanroom fabrication, advanced simulations, and machine learning to accelerate the development of next-generation nanoelectronics.