School of Engineering Department of Industrial Engineering and Decision Analytics 151 Department of Industrial Engineering and Decision Analytics Remote Vital Signs Supervisor: SO Richard Hau Yue / IEDA Student: CHENG Chun Hong / COMP Course: UROP1100, Fall UROP2100, Spring Based on the findings and research of previous UROP 1100E project, we dived deeper and analysed different methods for remote blood oxygen saturation (SpO2) measurement. During this UROP 2100F project, we have proposed a deep learning method for remote SpO2 measurement with the use of a spatial-temporal representation ― spatial-temporal map (STMap). We have evaluated this deep learning method with a largescale multi-modal public benchmark dataset, VIPL-HR. Our method outperforms existing traditional remote SpO2 measuring methods and it is also robust in different situations. This shows that our proposed method has a great potential to be applied for healthcare services. Data Analysis in Fintech Supervisor: ZHANG Jiheng / IEDA Student: LI Hao / DA Course: UROP1100, Fall UROP2100, Spring The Long-Shot Term Memory (LSTM) networks are used to predict the cryptocurrency prices. Our results show that LSTM gives good predictions for the time series in our study here, and makes much better predictions over the classical methods used in our previous study. Some of the technical issues and future directions are mentioned and discussed at the end of the report. Data Analysis in Fintech Supervisor: ZHANG Jiheng / IEDA Student: LIU Yuzhi / MATH Course: UROP1100, Fall The world has seen an explosive development of information technology during past decades. Following this trend, FinTech as well as algorithmic trading has rapidly flourished. The report gives a brief overview of the different cryptocurrencies available today and describes an implementation using a modified trading algorithm on a given database.