An Intro To AIOps: How To Scale IT Operations With AI
In this talk, the speaker covers how to leverage AI and quantitative techniques in order to scale and optimize large scale product infrastructure in the cloud or on the edge. In particular, they will explain how techniques like time series forecasting, operations research, and statistical and causal inference could be leveraged to optimize infrastructure investments and resource allocations, enable predictive maintenance, and allow building infrastructure that is more aware of the needs of products such as video, real time messaging and the metaverse
Ghida is a lead quantitative engineer at Meta (previously Facebook) where she uses automated decisioning and advanced analytics to help scale and optimize Meta internal cloud and edge infrastructure, used to serve billions of people across Meta family of apps and products. Prior to joining Meta, Ghida worked for 6+ years in the Telco and media industries in multiple analytics and engineering roles, mainly focusing on optimizing large scale distributed systems. She holds a PhD and master’s (Diplome d’Ingénieur) in computer engineering from Institut Polytechnique de Paris.
Ghida also teaches a course on using AI for scaling IT operations at the university of Oxford. She is a TED speaker and an Expert of the World Economic Forum, providing expertise on the future of computing. In the past, Ghida prepared and delivered the first online course on data science in Arabic attracting 30k+ learners, and built an award-winning platform for connecting refugees to opportunities, among others.
Ghida's expertise is at the intersection of computing infrastructure, data engineering and AI. It covers Edge Computing, Cloud Computing, Content Delivery Networks, time series analysis, operations research, statistical inference, ETL, expert systems, recommender systems, machine learning and federated learning, among others.