Graph Computing (GC) 2021

 

Graphs are widely used to model complex data nowadays: social networks, recommendation engines, computer networks, bio-informatics, to name a few. Graph theory has traditionally been a core area of research in computer science and artificial intelligence. With the growing number of applications and amount of data, Graph Computing addresses the storage, analysis, synthesis, and processing of (possibly large) graphs to solve complex problems in industry applications. 

Graph Computing 2020 (GC 2020) is an international forum for academia and industries to exchange visions and ideas in the state of the art and practice of Graph Computing, as well as to identify the emerging topics and define the future of Graph Computing.

TOPICS OF INTEREST​​ include, but are not limited to:

  • Graph algorithms for industry applications

  • Fundamentals of graph computing including storage of graphs, graph databases,  query languages, query optimization, integrity and security, graph OLAP, graph mining, graph learning, graph reduction, and graph visualization.

  • Knowledge graphs

  • Network analysis

  • Big graph analytics

  • Integration and platforms

Graph Computing 2021 Co-Chairs

Joseph Barr, Acronis SCS, USA
Gregory Gutin, Royal Holloway, University of London, UK
Peter Shaw, Massey University, New Zealand​

Phillip Sheu, University of California, Irvine. USA

Program Committee (tentative)

Antonio Badia, University of Louisville, USA
Elisa Bertino, Purdue University, USA  
Martin Berzins, University of Utah, USA
Burcin Bozkaya, New College of Floriday, USA
Keke Chen, Wright State University, USA 

Malolan Chetlur, IBM, India
Kenneth Chiu, Binghamton University, USA
Alfredo Cuzzocrea, ICAR-CNR and University of Calabria, Italy
Magdalini Eirinaki, San Jose State University, USA
Sameh Elnikety, Microsoft Research, USA  
Wayne Goddard, Clemson University, USA
David Kaeli, Northeastern University, USA
Verena Kantere, University of Ottawa, Canada
Yiping Ke, Nanyang Technological University, Macau

Alexander Kotov, Wayne State University, USA
Eren Kursun, Columbia University, USA
Jay Lofstead, Sandia National Laboratories, USA  
Amirreza Masoumzadeh, SUNY at Albany, USA
Dana Petcu, West University of Timisoara, Romania
Katerina Potika, San Jose State University, USA    
Weidong Shi, University of Houston, USA
Koichi Shirahata, Fujitsu, Japan
Rekha Singhal, TCS, USA
Srivathsan Srinivasagopalan, Visa, USA
Dimitrios Tsoumakos, Ionian University, Greece
Jianwu Wang, University of Maryland Baltimore County, USA
Ka-Chun Wong, City University of Hong Kong, Hong kong
Feng Yan, College of William and Mary, USA