2021 ACM SIGMOD/PODS Conference to Feature World’s Foremost Data Scientists and Engineers
Virtual Conference to Explore Latest Innovations in Data Design, Automation, and Management with Blockbuster Program
New York, NY, June 10, 2021 – The Association for Computing Machinery’s Special Interest Group on Management of Data (ACM SIGMOD), together with PODS, the premier international conference on the theoretical aspects of database systems, will host its 2021 ACM SIGMOD/PODS Conference June 20 - 25, 2021. Held virtually this year with all the sessions available online, the conference will be complemented with a local physical event in Xi’an, China, primarily targeting the strong data management community in this region.
Global industries have become increasingly reliant upon data management to inform future operations and drive prosperity. Data management plays an increasingly vital role in the development and efficacy of machine learning, biometric analysis, and remote sensors across industries. As such, the ACM SIGMOD/PODS Conference presents a unique, international forum for database researchers, practitioners, developers, and users to share cutting-edge ideas and results, as well as exchange techniques, tools, and experiences across all aspects of data management. Conference participants will also have the opportunity to engage in a variety of new SIGMOD curated sessions, SIGMOD tutorials, and PODS sessions each day. The conference program consists of research papers, demo papers and industrial papers; tutorials; panel discussions; and keynote talks.
“Utilizing (and Designing) Modern Hardware for Data-Intensive Computations: The Role of Abstraction”
Kenneth A. Ross, Columbia University
“Deep Data Integration"
Wang-Chiew Tan, Facebook AI
“Complexity Theory and Efficient Algorithms for Big Data Computation with Limited Computing Resources”
Jianzhong Li, Shenzhen Institute of Advanced Technology and Harbin Institute of Technology
Rajeev Alur, University of Pennsylvania
“Modern Lower Bound Techniques in Database Theory and Constraint Satisfaction”
Dániel Marx, Max-Planck-Institut für Informatik
"Approximation Algorithms for Large Scale Data Analysis"
Barna Saha, University of California Berkeley
Contact Jim Ormond at firstname.lastname@example.org for media registration and related inquiries.
The ACM Special Interest Group on Management of Data (SIGMOD) is concerned with the principles, techniques and applications of database management systems and data management technology. Our members include software developers, academic and industrial researchers, practitioners, users, and students. SIGMOD sponsors the annual SIGMOD/PODS conference, one of the most important and selective in the field.
ACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting educators, researchers and professionals to inspire dialogue, share resources and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.