MayAI Recruits AI Expert Professor Lee Jong-seok from Yonsei University as Technical Advisor

Officially Joined MayAI Machine Learning Research Team
Advancing Technology and Expanding Solution Supply Scope for Global Market Entry

Meiai, the operator of the video processing artificial intelligence (AI) solution ‘mAsh,’ announced on the 26th that it has recruited Professor Jongseok Lee of Yonsei University as a technical advisor to advance its AI-based technology.

Technical advisor Jongseok Lee, affiliated with the Department of IT Convergence Engineering at Yonsei University’s College of AI Convergence, is an expert who has accumulated extensive expertise through 20 years of research in AI fields such as machine learning, computer vision, and video signal processing. He is currently a senior member, selected within the top 10% of all members, at the global academic organization Institute of Electrical and Electronics Engineers (IEEE), and holds over 120 international conference papers, more than 40 registered domestic patents, and about 50 patent applications.

Professor Lee Jong-seok, Yonsei University

mAsh is a solution developed by Meiai using its proprietary deep learning algorithm that analyzes visitor data captured by offline store CCTV to provide meaningful marketing insights. By recruiting this advisor into the machine learning research team, Meiai plans to significantly enhance mAsh’s data analysis capabilities and the ease of implementation across various offline stores, as well as its technical performance.

In particular, Meiai will conduct joint research with the advisor on the theme of ‘Advancement of Person Re-identification and Attribute Classification Functions in CCTV Environments.’ Through this, they aim to implement technology capable of precisely recognizing visitors’ movement paths, gender, and age even in limited CCTV environments with various noise, thereby providing customers with enhanced services of higher accuracy.

Junhyuk Park, CEO of Meiai, said, “With the addition of technical advisor Jongseok Lee, we have taken a step closer to our research team’s goal of ‘analyzing more specific data more accurately and more efficiently.’ We will focus on advancing the technology so that mAsh can be easily introduced not only in domestic but also global offline stores.”