We are continuously monitoring the COVID-19 situation from local authorities and the World Health Organization. RDAAPS'21 will be held in May 2021, and we warmly invite you to attend. RDAAPS'21 is going to be an online event; there will be virtual talks that attendees can attend.

We warmly invite you all again to submit your papers to RDAAPS'21.

The Reconciling Data Analytics, Automation, Privacy, and Security (RDAAPS) conference serves as a premier forum for advancing the state of the art in the intersection of the areas of Big Data Analytics for Decision Making, Accountable Data Analytics, Strings in Data Analytics, Security in Data Analysis, Domain knowledge modeling and generation, Automation for data analytics, security, and privacy in manufacturing, and Challenges of automation of data analytics processes.  RDAAPS brings together international experts from academia, industry, and government to present and discuss novel research in these areas. The call for papers can be found on the Academic's CFP page or the Industry Expert CFP page, or downloaded as a PDF (CFP for Academics, CFP for Industry Experts).



The current capacity to store, share and use vast amounts and formats of data has tremendous potential for a wide spectrum of stakeholders in a wide range of applications, including industrial, medical and public health, government, and business. Many of the most challenging problems related to big data occur at the intersection of several aspects including security, privacy, and automation. An integrated approach that considers these aspects and how they relate to each other both from a theoretical and applied perspective is needed to realize the comprehensive and scalable solutions required by the stakeholders.


The goal of RDAAPS is to promote academic and industrial collaborations, providing a platform for integrating the needs of the industry with the advancements in research and inspiring original research to solve enterprise data challenges.


The comprehensive and scalable solutions required to address the challenges of big data, security, privacy and automation will be achieved by creating a community to focus on problems that lie at the intersection of these concerns promoting collaborations and partnerships among the business and industrial stakeholders and the academic research community.


Amir Razavi

Senior Data Scientist (ML Team lead) at Bell Canada ... more

Ling Liu

Professor & Research director of Distributed Data Intensive Systems Lab (DiSL), IEEE Fellow ...  more


Lisa Kearney

President & CEO, Women CyberSecurity Society Inc. ... more

Mourad Debbabi

Professor & Tier I Industrial research chair in smart grid security ... more



and more


... Coming soon ...