Interview with Kunpeng Xu: Kernel representation learning for time series

In this interview series, we're meeting some of the AAAI/SIGAI Doctoral Consortium participants to find out more about their research. The Doctoral Consortium provides an opportunity for a group of PhD students to discuss and explore their research interests and career objectives in an interdisciplinary workshop together with a panel of established researchers. In the first of our interviews with the 2025 cohort, we meet Kunpeng (Chris) Xu and find out more about his research and future plans. I am a final-year Ph.D. student at the ProspectUs-Lab, Université de Sherbrooke, Canada, where I have been working with Professor Shengrui Wang and Professor Lifei Chen since 2021. I explore data-driven kernel representation learning to develop more adaptive and expressive models for complex time series, while also investigating subspace learning and its applications in AI.