Synthetically generating student data
Monday 22 June 2020 - 3:30-4:30 pm
[UPDATE: watch the seminar recording on the ALSET YouTube Channel]
Every university collects data on their students and their activities. When developing a what-if application (e.g. to predict the impact of increasing shuttle bus frequency or enforcing social distancing), a developer may want to test the application with the student data. However, for privacy reasons, student data should not be freely available. One alternative is to generate synthetic student data that is similar to the real data, and only give the developers the synthetic data. This talk illustrates how this can be done for student WiFi connection data.
FENG Ben is currently pursuing a bachelor's degree with the School of Software Engineering, Sichuan University. He was an exchange student at NUS in Semester 2 of AY2019/20.
Y. C. TAY received a B.Sc. degree from the University of Singapore, and a PhD degree from Harvard University. He is currently a Professor with the Department of Mathematics, the Department of Computer Science, and Tembusu College at the National University of Singapore. He has spent sabbaticals at Princeton, MIT, Cambridge, UCLA, National Taiwan University, Microsoft, Intel, and VMware. He is author of Analytical Performance Modeling for Computer Systems (Morgan & Claypool, 3rd ed.). His main research interest is performance modelling (database transactions, wireless protocols, Internet traffic, and cache misses). Other interests include database systems (synthetic generation of data and social networks) and the use of local time in distributed computing. He has served on program committees for ACM SIGMETRICS, ACM SIGMOD, IFIP PERFORMANCE, VLDB, IEEE ICDE, IEEE MASCOTS, IFIP NETWORKING, WWW and ICS. He is also a Senior Associate Editor of the ACM Transactions on Modeling and Performance Evaluation of Computer Systems.
The presentation will be held online.
Please RSVP to be invited to the webinar
(picture credits: CC BY-NC 2.0 Kjetil Korslien)