Speakers CWI's Lectures on Database research (2020)

* Anastasia Ailamaki (EPFL, Switzerland)
Nothing is for granted: Making wise decisions using real-time intelligence

Anastasia Ailamaki is a Professor of Computer and Communication Sciences at the École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland and the co-founder of RAW Labs SA, a Swiss company developing real-time analytics infrastructures for heterogeneous big data. She earned a Ph.D. in Computer Science from the University of Wisconsin-Madison in 2000. She works on strengthening the interaction between the database software and emerg- ing hardware and I/O devices, and on automating data management to support computationally-demanding, data- intensive scientific applications. She has received the 2019 ACM SIGMOD Edgar F. Codd Innovations and the 2020 VLDB Women in Database Research Award. She is also the recipient of an ERC Consolidator Award (2013), a Finmeccanica endowed chair from the Computer Science Department at Carnegie Mellon (2007), a European Young Investigator Award from the European Science Foundation (2007), an Alfred P. Sloan Research Fellowship (2005), an NSF CAREER award (2002), and ten best-paper awards in database, storage, and computer architecture conferences. She is an ACM fellow, an IEEE fellow, the Laureate for the 2018 Nemitsas Prize in Computer Science, and an elected member of the Swiss, the Belgian, and the Cypriot National Research Councils. She is a member of the Academia Europaea and of the Expert Network of the World Economic Forum.

* Gustavo Alonso (ETH, Switzerland)
Data Processing in the Era of Specialization

Gustavo Alonso is a Professor of Computer Science at ETH Zürich where he is a member of the Systems Group (www.systems.ethz.ch). He has a degree in electrical engineering from the Madrid Technical University as well as a M.S. and Ph.D. degrees in Computer Science from UC Santa Barbara. Gustavo's research interests encompass almost all aspects of systems, from design to run time. He works on distributed systems, data processing on data centers and the cloud, as well as hardware acceleration using FPGAs. Gustavo has received numerous awards for his work, including four Test-of-Time awards for contributions to databases, programming languages, mobile computing, and systems. He is a Fellow of the ACM and of the IEEE as well as a Distinguished Alumnus of the Department of Computer Science of UC Santa Barbara.

* Gerhard Weikum (MMPI, Germany)
Machine Knowledge: How I Stopped Worrying about Databases and Started Loving the Web

Gerhard Weikum is a Scientific Director at the Max Planck Institute for Informatics in Saarbruecken, Germany, and an Adjunct Professor at Saarland University.
He co-authored a comprehensive textbook on transactional systems, received the VLDB Test-of-Time Award 2002 for his work on automatic database tuning, and is one of the creators of the YAGO knowledge base which was recognized by the WWW Test-of-Time Award in 2018.
Weikum received the ACM SIGMOD Contributions Award in 2011, a Google Focused Research Award in 2011, an ERC Synergy Grant in 2014, and the ACM SIGMOD Edgar F. Codd Innovations Award in 2016.

Patrick Valduriez (Inria & LeanXcale, France)
Distributed Database Systems: the case for NewSQL

NewSQL [Valduriez & Jimenez-Peris 2019] is the latest technology in the big data management landscape, enjoying a fast-growing rate in the DBMS and BI markets. NewSQL combines the scalability and availability of NoSQL with the consistency and usability of SQL. By blending capabilities only available in different kinds of database systems such as fast data ingestion and SQL queries and by providing online analytics over operational data, NewSQL opens up new opportunities in many application domains where real-time decision is critical. Important use cases are eAdvertisement (such as Google Adwords), IoT, performance monitoring, proximity marketing, risk monitoring, real-time pricing, real-time fraud detection, etc.
NewSQL may also simplify data management, by removing the traditional separation between NoSQL and SQL (ingest data fast, query it with SQL), as well as between operational database and data warehouse / data lake (no more ETLs!). However, a hard problem is scaling out transactions in mixed operational and analytical (HTAP) workloads over big data, possibly coming from different data stores (HDFS, SQL, NoSQL). Today, only a few NewSQL systems have solved this problem. In this talk, I introduce the solution for scalable transaction and polystore data management in LeanXcale, a recent NewSQL DBMS.


Patrick Valduriez is a senior scientist at Inria, France, and the scientific advisor of the LeanXcale company. He has also been a professor of computer science at University Pierre et Marie Curie (UPMC), now Sorbonne University, in Paris (2000-2002) and a researcher at Microelectronics and Computer Technology Corp. in Austin, Texas (1985-1989).

He is currently the head of the Zenith team that focuses on data science, in particular, scientific data management. He has authored and co-authored many technical papers and several textbooks, among which “Principles of Distributed Database Systems” (with Professor Tamer Özsu, University of Waterloo). He has served as PC chair of major conferences such as SIGMOD and VLDB. He was the general chair of SIGMOD04, EDBT08 and VLDB09.

He received prestigious awards and prizes. He obtained several best paper awards, including VLDB00. He was the recipient of the 1993 IBM scientific prize in Computer Science in France and the 2014 Innovation Award from the French Academy of Science. He is an ACM Fellow.