what Lab

Welcome to what Lab.

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At what Lab, we are dedicated to solving diverse and meaningful problems in the world using data-driven approaches. Our mission is to tackle challenges that span across various domains, leveraging the power of data to uncover insights and drive impactful solutions. While we embrace cutting-edge technologies like machine learning, our primary focus remains on understanding and addressing the problems themselves.

what Lab thrives on curiosity and creativity. We believe that the best solutions emerge when we question assumptions, explore new perspectives, and combine knowledge from different fields. Our team is passionate about turning data into actionable outcomes, whether it’s optimizing systems, improving decision-making, or uncovering hidden opportunities.

We work on a wide range of issues, from societal challenges to business optimization, always keeping the end goal of positive change in mind. By grounding our work in data and collaborating across disciplines, we ensure that our solutions are not only innovative but also practical and impactful.

If you share our passion for solving real-world problems and enjoy exploring uncharted territories of knowledge, we’d love to hear from you. At what Lab, creativity meets purpose, and data meets action. Let’s make a difference together.

selected publications

Displays

L-Shape advertising for mobile video streaming services: Less intrusive while still effective

Taekyung Kim, Jaehwan Lee^*, and Jihae Suh

Displays, 2023

Abs DOI

Advertising is significant in video streaming services on mobile devices, as well as in other e-business services. Advertisement providers pay part or the entire service cost; hence, users enjoy services at a low price or free of charge. However, users perceive advertisements as clutter and avoid them. To reduce advertising avoidance and enhance advertising efficiency, various methods, such as raising advertising relevance, seeking advertisement permission, or changing advertisement position, are suggested. This study introduces L-Shape advertising, a new strategy suitable for mobile video streaming services, as it is less distractive and effective. We demonstrate the superiority of L-Shape advertising compared to popular advertising formats such as skippable and non-skippable advertisements. The study empirically tests how the proposed strategy performs and examines users’ cognitive processes applying eye-tracking technology. We found that L-Shape advertising is less distractive but still effective.