Min-Jun Choi

I am Min-Jun Choi, a developer proficient in both data analysis and AI model development. My years of research in mathematics have endowed me with exceptional problem analysis and problem-solving skills. These abilities enable me to contribute innovative ideas and effective solutions to the projects I participate in. My goal is to be a developer who significantly contributes to my company by developing necessary data analysis tools and AI models for various projects. I am committed to using my expertise to drive progress and deliver value in every endeavor I undertake. Ph.D. / Department of Mathematics(PDE) / Sogang University (2013.2~2019.8) Postdoctoral Researcher / BK21+ SNU Mathematical Sciences Division for Creative Human Resources Development / Seoul National University (2019.9~2020.8) NRF Postdoctoral Researcher / Kunsan National University (2020.9~2021.9) Sandslab (2021.10 ~ ) / Head of AI Technology Development Team / Principal Research Engineer 1-1 Development of a nonexecutable malware detection product for APT attack response. (2021.10 ~ 2023.08) - Development and continuous performance improvement of an AI model for detection of malicious files (Anti-Virus vs AI : https://youtu.be/foi9qO2alu8) - Creation of parsers for data analysis and metadata extraction for each nonexecutable file type. - Acquired new technology certification (NET 2022, 3 years) for profiling technology in nonexecutable files. - Product feature development: Document Preview, AI Chart - GS Certification * Languages and Development Environment: - Python & Linux, Windows, WSL, VMware, TSNE, KNN * Pipeline construction for securing AI model training data. - Extracting and vectorizing metadata from secured samples for storage along with features. - Improvement of training speed and performance monitoring. * Languages and Development Environment: - Python & inux, Elasticsearch, Kibana 1-2 CVE-TID Mapping Model Development (2022.5 - 2022.6) * Main tasks and detailed roles: - Development of an AI model to map CVE with TID (technique ID). - Development of Tokenizer and AI model using Word2Vec. * Languages and Development Environment: - Python & Linux 1-3 Automatic Yara Rule Generation (2023.12 - 2024.01) * Main tasks and detailed roles: - Data preprocessing for Prompt using base data analysis. - Automatic rule generation through Prompt Engineering. - Construction of a complete pipeline for automatic rule generation. - Dashboard construction for pipeline. * Languages and Development Environment: - Python & Linux, PostgreSQL, Grafana, gpt4