Dr. Pandi Divya P. is a semiconductor researcher specializing in semiconductor device engineering, advanced packaging, two-dimensional (2D) semiconductor materials, and AI-assisted device modeling. Her research focuses on integrating semiconductor physics, process engineering, and data-driven methodologies to develop next-generation electronic devices and intelligent manufacturing technologies.

Dr. Divya obtained her Dual Master’s and Ph.D. degree in Electrical Engineering and Computer Science from National Cheng Kung University (NCKU), Taiwan, where she conducted interdisciplinary research in semiconductor devices, flexible electronics, and additive manufacturing technologies. Her doctoral research explored environmentally sustainable semiconductor processes, including additive copper metallization techniques for flexible electronic devices and antenna systems, contributing to advancements in RFID antennas, automotive radar components, and flexible electronics.

Her research experience also includes TCAD-based modeling and design of semiconductor devices, including GaN high-electron-mobility transistors (HEMTs), SiC power devices, and advanced MOSFET structures. In particular, she has investigated the influence of SiNₓ passivation stress on GaN HEMT electrical characteristics, providing insights into the relationship between mechanical stress, polarization effects, and device reliability in wide-bandgap semiconductor technologies.

More recently, Dr. Divya’s research has expanded to two-dimensional (2D) semiconductor devices, focusing on MoTe₂-based transistors and emerging nanoelectronic materials. Her current work combines TCAD simulation, experimental material processing, and advanced characterization techniques to improve carrier transport properties and device reliability in next-generation semiconductor systems.

To further advance semiconductor research, Dr. Divya has begun integrating artificial intelligence (AI) and machine learning techniques with semiconductor device modeling and manufacturing data analysis. Her work explores AI-assisted TCAD frameworks, data-driven semiconductor process optimization, and intelligent defect detection in semiconductor manufacturing systems. This interdisciplinary approach supports the development of smart semiconductor manufacturing technologies aligned with Industry 4.0 principles.

Dr. Divya has published multiple peer-reviewed journal papers in international journals, including IEEE Transactions on Components, Packaging and Manufacturing Technology, Materials Science in Semiconductor Processing, Japanese Journal of Applied Physics, and International Journal of Antennas and Propagation. Her research contributions have received international recognition, including the Best Paper Award from IEEE Transactions on Components, Packaging and Manufacturing Technology (2024) and the Tech Innovation Excellence (TIE) Award from the National Science and Technology Council (NSTC), Academia Sinica, Ministry of Education, and Ministry of Health and Welfare (2022).

In addition to research, Dr. Divya is actively involved in mentoring graduate students and supervising international exchange students in interdisciplinary semiconductor research projects. Current student projects under her supervision focus on AI-assisted TCAD modeling, wide-bandgap power devices (GaN and β-Ga₂O₃), advanced MOSFET design, and semiconductor manufacturing data analytics. These projects aim to equip students with both fundamental semiconductor device knowledge and modern AI-based engineering tools.

Through the NSTC International Internship Pilot Program (IIPP), Dr. Divya’s research group aims to provide international students with hands-on experience in semiconductor device simulation, AI-enhanced semiconductor research, and advanced electronic materials, while fostering international collaboration and talent development in emerging semiconductor technologies.

The research group led by Dr. Pandi Divya P. focuses on interdisciplinary research in semiconductor devices, advanced electronic materials, and AI-assisted semiconductor engineering. The lab’s research integrates TCAD device simulation, semiconductor process engineering, and data-driven modeling to address challenges in next-generation semiconductor technologies.

The laboratory actively hosts international exchange students and graduate researchers, providing training in semiconductor device modelling, AI-based data analysis, and advanced electronic device design. Through these activities, the lab will promotes international collaboration and interdisciplinary innovation in emerging semiconductor technologies.