Yongjin Han

My current research interests lie in certified/adversarial robustness through formal methods and optimization techniques. To develop reliable and secure software, I previously studied software verification/analysis, cybersecurity, and compiler optimization. Building on these experiences, my research goal remains to ensure the reliability and safety of software systems, now integrated with AI components.

In parallel, I am also exploring efficient AI approaches such as quantization, pruning, PEFT, since security mechanisms often compromise user availability and practicality. Ultimately, I aim to balance robustness and efficiency in AI systems, enabling users to leverage trustworthy AI technologies in real-world applications.

I am currently working with Prof. Suhyun Kim, who provides valuable guidance as I pursue independent research with strong self-motivation.

I earned a Master’s degree in Computer Science at University of California, Davis advised by Prof. Ian Davidson. Under supervision of Prof. Davidson, I studied deep fair clustering using constraint programing (CP) and learned that CP can be effectively apllied to ML systems. I obtained my Bachelor’s degree in Computer Science and Engineering at Dongguk University. Prof. Yunsik Son first introduced me to programming language, secure software and related research area.

In my free time, I usually cook or watch movies.