Sijng Tu

I recently received my Ph.D. from KTH Royal Institute of Technology under the supervision of Professor Aristides Gionis.

My research focuses on designing unbiased algorithmic systems, particularly in the context of online social networks. These platforms, and their timeline and recommendation algorithms, face many emerging challenges.

• For instance, the timeline algorithms often prioritize user engagement, encouraging people to spend more time on the platform. However, this can lead users to become trapped in repetitive content streams, especially of negative news. One research question that motivates my work is: How can we design timeline algorithms that ensure the users to exposure to a diverse and representative set of content?

• Another concern is the vulnerability of social networks to external interventions, such as the spread of biased or misleading information aimed at shaping public opinion. During major societal events, users may be exposed to only a limited or skewed subset of information, and algorithms can unintentionally reinforce false balance. My research investigates the how vulnerable the social networks are to such interventions, how to mitigate disinformation and misinformation, and how to improve the underlying mechanisms of social media systems to promote trustworthy and balanced information flows.

The problems I study are inherently interdisciplinary, lying at the intersection of computer science, social science, and human behavior. My work builds on, and extends, models inspired by real-world phenomena to capture the interplay between information flow, user behavior, and algorithmic interventions. These models bridge the gap between real-world phenomena and mathematical formulations, allowing me to analyze the computational complexity of the underlying problems and to design provable approximation algorithms with theoretical guarantees.

Beyond real-world applications, I also have a broad interest in approximation algorithm design. I am particularly drawn to instances that bridge theory and practice, where rigorous algorithmic analysis has interesting real-world implications. Currently, I am particularly interested in computational social choice.