Seminars

For centuries, unraveling the mysteries of nature through the lens of physics has captivated countless scientists.

Abstract not available

Many cloud and edge AI services today perform machine learning inference in real time on end user requests. Over time, however, models could degrade in accuracy due to data and concept drifts, and full retraining can be infeasible because of limited training data, long training delay, and prohibitive computational overhead.

The seminar will be an interdisciplinary journey between applications of Artificial Intelligence (AI) Computer Vision based methods to the field of Forensics and Biomedical Imaging.

End-to-end encryption (E2EE) for messaging has become an industry standard and is widely implemented in many applications. However, applying E2EE to audio calls, particularly group calls, remains a complex challenge.

Equivariance can enhance the data efficiency of machine learning models by incorporating prior knowledge about a problem.
Thanks to their flexibility and generality, steerable CNNs are a popular design choice for equivariant networks.

*Abstract*

Stay tuned!

*Bio*

Yihang She is a first-year PhD student in Computer science at the University of Cambridge. His PhD focuses on the development of 3D vision algorithms to enable real-time and low-cost forest carbon estimation.

Abstract not available

Misogyny and domestic abuse are old problems, but tech companies have enabled these harms to grow and proliferate on their platforms in new forms, such as social media harassment, cyberstalking, and deepfake intimate image abuse.

Abstract not available