EasyVista Publishes New Paper on Causal Discovery Methods on Real IT Monitoring Data
EasyVista to Present at the 39th Conference on Uncertainty in Artificial Intelligence
NEW YORK–(BUSINESS WIRE)–#EasyVista–EasyVista, a leading ITSM and ITOM solution provider, has published a new scientific paper, Case Studies of Causal Discovery from IT Monitoring Time Series. The paper was accepted for an oral presentation, led by EasyVista researchers Ali Ait-Bachir and Charles K. Assaad, at the workshop on The History and Development of Search Methods for Causal Structure of the 39th Conference on Uncertainty in Artificial Intelligence in Pittsburgh, PA from July 31 to August 4.
The paper was written by the EasyVista Lab team, composed of Ali Ait-Bachir, Charles K. Assaad, Lei Zan, Simon Ferreira, Hossein Mohanna, as well as Christophe De Bignicourt from the EasyVista Big Data team. Additionally, Emilie Devijver and Eric Gaussier from the Université Grenoble Alpes are also authors of the paper. Extensive experiments on real-world IT monitoring datasets were conducted. Charles K. Assaad, EasyVista Lab Researcher notes, “The case study presented in this paper shows both the potential benefits and ongoing challenges of applying causal discovery algorithms to IT monitoring data. This area should continue to be an active field of research and development, with the aim of improving the efficiency and performance of IT systems in diverse industries and applications.”
Michael Cohen, Chief Technical Officer at EasyVista adds, “We couldn’t be more proud of the EasyVista Lab team and their hard work. The publication of this paper and the presentation of it at Carnegie Mellon in August shows that the future of IT is research-backed.”
The paper was accepted for an oral presentation at the workshop on The History and Development of Search Methods for Causal Structure at the 39th Conference on Uncertainty in Artificial Intelligence. The presentation will be on August 4th, 2023, at Carnegie Mellon University in Pittsburgh, PA. EasyVista’s publication of this paper amplifies its dedication to developing the IT field with innovative, research-driven solutions that support customers.
For more information about EasyVista visit www.easyvista.com.
About EasyVista
EasyVista is a leading IT software provider of end-to-end IT solutions including service management, remote support, IT monitoring, and self-healing technologies. EasyVista makes it easy for companies to embrace a customer-focused, proactive, and predictive approach to their IT service, support, and IT operations. Today, EasyVista helps over 3,000+ companies around the world to accelerate digital transformation, empower leaders to improve employee productivity, reduce operating costs, and increase employee and customer satisfaction across financial services, healthcare, education, manufacturing, and other industries. Learn more at www.easyvista.com.
Contacts
Sarah Hudlow
shudlow@easyvista.com