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Shirley (Xiaoqi) Liu 
Background -
Research -
Publications
My first name is pronounced as "Sh-ih-ow Chi"
but feel free to call me Shirley.
Position: PhD Student
E-mail: xl394 [at] cam.ac.uk
Office Location: BN3-02
Thesis Title:
Supervisor: Dr Ramji Venkataramanan
Background
I completed my BA and MEng degrees at Cambridge with Distinction in June 2019. My MEng thesis was titled
Efficient Sparse Principal Component Analysis for Low-rank Matrices using Linear Codes. From 2019 till now, I've been pursuing a PhD in coding theory. I'm currently in the fourth year of my PhD, aiming to graduate by mid-2024.
Research Interests
Coding theory, probabilities and message-passing algorithms. In particular, I have been looking at designing low-complexity message-passing algorithms for signal estimation (e.g. matrix sketching, multiple access channels).
From a more technical perspective, I've been interested in analysing message-passing algorithms on sparse and dense graphs.
Publication and Preprint
X. Liu and R. Venkataramanan, "Sketching sparse low-rank matrices with near-optimal sample- and time-complexity,"
2022 IEEE International Symposium on Information Theory (ISIT), Espoo, Finland, 2022, pp. 3138-3143, doi: 10.1109/ISIT50566.2022.9834693.
X. Liu and R. Venkataramanan, “Sketching sparse low-rank matrices with near-optimal sample- and time-complexity using message passing,” arXiv:2205.06228, 2022. (Hopefully) to appear in IEEE transactions on Information Theory soon
Teaching
Supervisor for third-year courses
3F7 Information Theory & Coding and 3F4 Data Transmission
Demonstrator for 3F4 Data Transmission laboratory
