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Assistant Professor
School of Information Sciences, University of Pittsburgh

710 IS Bldg, University of Pittsburgh
135 North Bellefield Ave., Pittsburgh, PA 15260

Phone: 412-624-9470
Fax: 412-624-5231

Email: yurulin (at) pitt.edu

     Yu-Ru Lin


I am an assistant professor at School of Information Sciences, University of Pittsburgh. In the past, I worked as an assistant research professor at the College of Social Sciences and Humanities, Northeastern University. I was also a postdoctoral research fellow at the Institute for Quantitative Social Science, Harvard University and College of Computer and Information Science, Northeastern University.

I am interested in studying social and political networks, as well as computational and visualization methods for understanding network data. My work has focused on large-scale community dynamics, rich-context (high-dimensional) social information summarization and representation. I have been using massive social media data and anonymized cellphone records (CDRs) to understand the collective responses with respect to political events and under exogenous shocks such as emergencies.

I am a computer scientist by training, and I identify myself as a computational social scientist as I concern more with questions like: "how would a society be informed?" "how do people share information, ideas and opinions in various contexts?" These questions have led me to explore analytical and computational techniques for mining heterogeneous, multi-relational, and semistructured data that can advance our understanding about structures in networked societies.

During my postdoctoral training, I have worked with colleagues from the disciplines of Physics and Social Sciences in the BarabasiLab and the LazerLab, where I worked with Dr. David Lazer. I received my Ph.D. in Computer Science from Arizona State University, with an interdisciplinary concentration in Arts Media and Engineering, where I worked with Dr. Hari Sundaram and Dr. Aisling Kelliher. My Ph.D. work focused on extracting human communities that collaborate around certain topics or shared media artifacts. I have proposed matrix and tensor based techniques for analyzing community structures and evolutions in time-varying heterogeneous social networks, and developed visualizations to support community discovery in the context of everyday social media use.

» Recruiting:   I am looking for highly motivated students who have strong interest in pursuing research careers in the new areas of Data Science, Network Science, and Computational Social Science. See more information.

research highlights

My publications and talk slides can be found here. Read earlier research highlights or detailed research description.

teaching & tutorials

selected services

I have served as a program committee member for international data and web mining conferences and workshops including KDD 2015, IJCAI 2015, MM 2014, MM 2013, WSDM 2014, WSDM 2013, WWW 2015, WWW 2014, WWW 2012, WWW 2011, HT 2013, HT 2012, ICWSM 2015, ICWSM 2014, ICWSM 2012, ICWSM 2011, ICWSM 2010, LDMTA 2010, SocInfo 2011, etc. I have served as a reviewer for journals including IEEE TKDE, ACM TOMCCAP, ACM TOIS, Communications of the ACM, IEEE TMM, etc., and conferences including IUI, ACM SIGKDD, ACM MM, etc.

Workshop Chair/Co-Chair: 2014 KDD Workshop on Learning about Emergencies from Social Information (KDD-LESI 2014), International Workshop on Collaborative Big Data (C-Big 2014), International Workshop on Challenges & Issues on Scholarly Big Data Discovery and Collaboration (SBD 2014), 2013 KDD Mutimedia Data Mining Workshop, 2011 Doctoral Symposium in ACM Multimedia.

Last updated: Feb. 1, 2015