Won-Young Joo
Ewha Womans University
研究室紹介
Professor Won-Young Joo's research lab specializes in data-driven decision-making systems, focusing on personalized welfare program recommendations and intelligent portfolio management. The lab develops advanced machine learning models—such as conditional variational autoencoders combined with collaborative filtering—to address complex recommendation challenges in public welfare and finance. Research directions include attention-based learning in investment management, dynamic risk constraint adaptation, and scalable personalization using natural language and demographic data. The lab bridges artificial intelligence with real-world societal and economic applications.
Research Overview
Research Output Trend
Figures are computed from collected data and may differ slightly.
Selected Papers
2In delegated management, it is common practice to manage portfolios within specific risk tolerances based on benchmark indices. We provide insights into the fund manager’s optimal learning and investment behavior in re-sponse to changes in constituents of the benchmark. Our model allows us to examine the importance of allocating attention to newly listed stocks. The manager’s optimal effort exerted by the manager on new stock decreases as the constraint on tracking error becomes tighter. On the
Recently, the government of South Korea has offered a variety of welfare programs that are customized to diverse demands, such as diabetes management, alcohol addiction rehabilitation, living condition improvement, etc. These welfare programs have become too diverse to be remembered and recommended by individuals, and the government now has a list matching program recipients and programs for further studies. This research investigates such welfare program recommendation with a conditional variat