The Second International Workshop on Deep Learning on Graphs: Methods and Applications (DLG-KDD’20)

August 24th, 2020
San Diego, CA, USA

In Conjunction with The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
August 23-27, 2020
San Diego Convention Center
San Diego, CA, USA
KDD 2020 logo

Face-to-face Workshop or Online Workshop or Mix?

The health and safety of our attendees and volunteers have always been our top priority at KDD-DLG'20, and we are taking measures beyond our existing practices in light of the unfolding COVID-19 outbreak. We will follow exactly the option that ACM SIGKDD and the KDD 2020 organization committee will suggest and have exact similar style as the main conference will take. Please check this website regularly for updates.

Call for Papers

Deep Learning models are at the core of research in Artificial Intelligence research today. It is well-known that deep learning techniques that were disruptive for Euclidean data such as images or sequence data such as text are not immediately applicable to graph-structured data. This gap has driven a tide in research for deep learning on graphs on various tasks such as graph representation learning, graph generation, and graph classification. New neural network architectures on graph-structured data have achieved remarkable performance in these tasks when applied to domains such as social networks, bioinformatics and medical informatics.

This wave of research at the intersection of graph theory and deep learning has also influenced other fields of science, including computer vision, natural language processing, inductive logic programming, program synthesis and analysis, automated planning, reinforcement learning, and financial security. Despite these successes, graph neural networks (GNNs) still face many challenges namely,

This one-day workshop aims to bring together both academic researchers and industrial practitioners from different backgrounds and perspectives to above challenges. The workshop will consist of contributed talks, contributed posters, and invited talks on a wide variety of the methods and applications. Work-in-progress papers, demos, and visionary papers are also welcome. This workshop intends to share visions of investigating new approaches and methods at the intersection of Graph Neural Networks and real-world applications.

Topic of interest (including but not limited to)

We invite submission of papers describing innovative research and applications around the following topics. Papers that introduce new theoretical concepts or methods, help to develop a better understanding of new emerging concepts through extensive experiments, or demonstrate a novel application of these methods to a domain are encouraged.

And with particular focuses but not limited to these application domains:

Awards and Sponsors

  • Best Paper Awards: the program committee will nominate a paper for the Best Paper Award and a paper for the Best Student Paper Award. The Best (Student) Paper Awards will include a cash prize. Stay tuned for this year!
  • Travel Awards: students with accepted papers have a chance to apply for a travel award (up to $500).
  • Sponsorship: TBD

Important Dates

Paper Guidelines

Submissions are limited to a total of 5 pages for initial submission (up to 6 pages for final camera-ready submission), excluding references or supplementary materials, and authors should only rely on the supplementary material to include minor details that do not fit in the 5 pages. All submissions must be in PDF format and formatted according to the new Standard KDD Conference Proceedings Template. Following this KDD conference submission policy, reviews are double-blind, and author names and affiliations should NOT be listed. Submitted papers will be assessed based on their novelty, technical quality, potential impact, and clarity of writing. For papers that rely heavily on empirical evaluations, the experimental methods and results should be clear, well executed, and repeatable. Authors are strongly encouraged to make data and code publicly available whenever possible. The accepted papers will be posted on the workshop website and will not appear in the KDD proceedings. Special issues in flagship academic journals are under consideration to host the extended versions of best/selected papers in the workshop.

All submissions must be uploaded electronically at

This year DLG will be held jointly with The International Workshop on Mining and Learning with Graphs (MLG-KDD'20). DLG and MLG will maintain a separate submission website and program committee.

Contact information:

Keynote Speakers / Invited Panelists

Workshop Co-Chairs

Organizing Committee

Technical Program Committee

Past workshops