David Palacios holds a PhD and a MSc in Telecommunications Engineering from the University of Málaga, where he worked as a researcher for the last five years. His research focused on the development and application of machine learning techniques to the automation of cellular network management through the concept of self-organizing networks (SON). This resulted in several top-tier publications, a patent, and the national award of the best PhD thesis in Communications and Information Technologies in Banking, granted by the Colegio Oficial de Ingenieros de Telecomunicación, given the applicability of his work to the banking environment. Currently, he works in Tupl as an R&D engineer, where he develop machine learning mechanisms to automate complex systems.
TuplOS: Big data-empowered environment and tools for automation of complex systems
The size and complexity of current and forthcoming industry use cases make their management become cumbersome, making the deployment of scalable and flexible tools for process management automation a pressing need. Consequently, Tupl has developed TuplOS®: a big data-empowered set of functionalities under a machine learning approach, specially devised for this task. This session aims at providing an overall vision of TuplOS® operation under a realistic use case for process automation: failure root cause analysis and action recommendation in a cellular network, whose main concepts (such as performance indicators, anomaly detection or dimensionality reduction) and benefits may be easily transferred to the finance environment.
Event Timeslots (1)
Big data-empowered environment and tools for automation of complex systems