How to Read and Summarize Existing Research Studies?

Date & Time

Date: Nov 14, Friday

Time: 2:00-3:00PM

Venue: IB 3106& Zoom

Zoom ID:  789 843 9496

Speaker

Prof. Tsz Nam Chan

Distinguished Professor at the Big Data Institute of Shenzhen University (SZU)

Abstract

Many junior research students struggle to conduct research. One of the main reasons is that they have the wrong mindsets for dealing with existing research studies. They may be frustrated by the sheer number of research papers in the literature and feel that their reading/understanding speed cannot keep up with the pace of publication. Worse still, some of these students may even think that they need to read every research paper from cover to cover in order to achieve “fully understanding”. In this talk, I will discuss the correct mindsets for reading and summarizing research papers (e.g., “how to avoid reading some irrelevant papers by using the inverted triangle filtering approach?” and “how to extract common concepts from a group of research papers?”). I strongly encourage those junior students to attend this talk, as mastering these correct mindsets is fundamental to building a successful research career.

BIO

Tsz Nam Chan (Edison) is currently a Distinguished Professor at the Big Data Institute of Shenzhen University (SZU). His research interests are mainly in large-scale geospatial analytics and large-scale data visualization. He published several research papers in prestigious conferences and journals in both database and data mining areas, including SIGMOD, VLDB, ICDE, SIGKDD, and TKDE. Prior to joining SZU, he was a Research Assistant Professor in the Hong Kong Baptist University from Sep 2020 to Aug 2023 and a postdoctoral researcher in The University of Hong Kong from Sep 2018 to Aug 2020. He received the PhD degree in computing and the BEng degree in electronic and information engineering from The Hong Kong Polytechnic University in 2019 and 2014, respectively. He is an IEEE senior member, an ACM member, and a recipient of the National Science Fund for Excellent Young Scholars in China (with age 32 at that time).