Alessandro D’Anca is a Scientist at the CMCC Foundation and Director of the Advanced Scientific Computing (ASC) Division. He earned a degree in Computer Engineering at the University of Lecce in 2006.
From 2008 to 2011, he worked as Junior Computer Systems Analyst for the ComputerVar S.r.l company at the Euro-Mediterranean Center on Climate Change (CMCC) in Lecce. He joined the Scientific Computing and Operations Division (current ASC division) at CMCC in 2011, where he started working in the Scientific Data Management research group. In 2015, he became Head of the Scientific Data Management research group of the ASC Division and was later appointed Division Director in 2018. His research activities focus on high performance computing, distributed and grid computing, and in particular on distributed data management, data analytics/mining and high-performance database management. He has been involved in many national and international projects (TESSA, CLIP-C, OFIDIA, MARSOP4, INDIGO-Datacloud, ESIWACE), working on development, project or scientific management and coordination tasks. He is also the author and co-author of several papers on big data analytics for eScience.
- Towards an Open (Data) Science Analytics-Hub for Reproducible Multi-Model Climate Analysis at Scale
- Big Data Analytics on Large-Scale Scientific Datasets in the INDIGO-DataCloud Project
- On the Use of In-Memory Analytics Workflows to Computer eScience Indicators from Large Climate Datasets
- Distributed and cloud-based multi-model analytics experiments on large volumes of climate change data in the earth system grid federation eco-system
- Big data analytics for climate change and biodiversity in the EUBrazilCC federated cloud infrastructure
- Ophidia: A Full Software Stack for Scientific Data Analytics
- A big data analytics framework for scientific data management
- Ophidia: Toward Big Data Analytics for eScience
- A multi-service data management platform for scientific oceanographic products
- An in-memory based framework for scientific data analytics