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20.590 Phd Pro-Seminar In Architecture And Sustainable Design

ISTD PhD Oral Defence Seminar by Tan Yu Xiang – Adverse conditions such as rain or murky water environment, significantly impacts various perception tasks. In rain conditions, the images captured are easily corrupted by both raindrops on the lenses and lens flare. Meanwhile in turbid underwater conditions, the murkiness reduces the contrast and saturation of the image. To tackle these problems, we utilise contextual information to improve robustness of perception algorithms.

ISTD PhD Oral Defence Seminar by Mark He Huang – Modern AI systems often struggle in physical environments where observations are incomplete, noisy and constantly changing. This seminar presents a feedback-guided representation learning framework that helps AI systems revise what they know, maintain useful representations over time and generate physically plausible outcomes. The work spans machine unlearning, object-centric 3D visual memory and simulator-guided video generation, with the broader aim of enabling more reliable reasoning in the dynamic physical world.