Associate Professor
Ph.D., National Taiwan University
Office: Room 1534, Technology Building
Telephone: 886-2-2771-2171 ext.4238
Email: jhwang@ntut.edu.tw

Social Web mining, information retrieval and knowledge discovery, big data analytics, distributed and cloud computing, network and information security

Dr. Wang’s research covers the area of Web information retrieval, text mining, data analysis, and knowledge discovery using distributed computing frameworks. His major works focus on statistical and linguistic analysis of text documents in social Web. Multimedia contents are analyzed, stored, and searched using data mining and deep learning techniques. He has published more than 60 journal and conference papers in related fields. Most recently, he joined cross-domain research projects in Cyber-Physical Systems and Radio archive retrieval. Various types of data such as equipment and sensor data in smart factories and speech transcripts are processed for more effective big data analytics. Also, natural language processing techniques are used to answer questions and make recommendations.

Before joining Taipei Tech., Dr. Wang worked in Academia Sinica as a Postdoctoral Fellow under the supervision of Dr. Lee-Feng Chien in the Institute of Information Science (IIS) from 2002 to 2007. He received his B.S. and Ph.D degrees in Computer Science from National Taiwan University, Taiwan, in 1994 and 2002, respectively.

Dr. Wang is a member of ACM and IEEE. He was an editorial board member of International Journal on Digital Library Systems (IJDLS) and International Journal of Data Mining Science. He served as program committee members of major international conferences including: JCDL 2018, ACM SIGIR 2010, IEEE SC2 2014-2018, SocialNLP 2013-2018, IEEE ISI 2009-2018, and TAAI 2012-2018. He was also session chairs of ACM SAC 2018, ICMLC 2018, and TAAI 2015. He was also reviewers of many prestigious journals and conferences (e.g. ACM TOIS, ACM TALIP, JASIST, KAIS, DSS, IP&M, DKE). He won the best paper award in ICADL 2007, and the 52nd Golden Bell Award in Broadcast Radio, Innovative Research and Application Award in 2017.