Panel

What is AI 2.0? Is it More than Just Deep Learning?
Moderator: C. Mohan (IBM Almaden Research Center)
Panelists: Christopher Re (Stanford University), Jian Pei (Simon Fraser University & JD.com), Michael Stonebraker (MIT), Jens Dittrich (Saarland University)

Christopher Ré

Christopher (Chris) Ré is an associate professor in the Department of Computer Science at Stanford University in the InfoLab who is affiliated with the Statistical Machine Learning Group, Pervasive Parallelism Lab, and Stanford AI Lab. His work’s goal is to enable users and developers to build applications that more deeply understand and exploit data. His contributions span database theory, database systems, and machine learning, and his work has won best paper at a premier venue in each area, respectively, at PODS 2012, SIGMOD 2014, and ICML 2016. In addition, work from his group has been incorporated into major scientific and humanitarian efforts, including the IceCube neutrino detector, PaleoDeepDive and MEMEX in the fight against human trafficking, and into commercial products from major web and enterprise companies. He cofounded a company, based on his research, that was acquired by Apple in 2017. He received a SIGMOD Dissertation Award in 2010, an NSF CAREER Award in 2011, an Alfred P. Sloan Fellowship in 2013, a Moore Data Driven Investigator Award in 2014, the VLDB early Career Award in 2015, the MacArthur Foundation Fellowship in 2015, and an Okawa Research Grant in 2016.

C. Mohan

Dr. C. Mohan has been an IBM researcher for 36 years in the database area, impacting numerous IBM and non-IBM products, the research and academic communities, and standards, especially with his invention of the ARIES family of database locking and recovery algorithms, and the Presumed Abort commit protocol. This IBM (1997), and ACM/IEEE (2002) Fellow has also served as the IBM India Chief Scientist for 3 years (2006-2009). In addition to receiving the ACM SIGMOD Innovations Award (1996), the VLDB 10 Year Best Paper Award (1999) and numerous IBM awards, Mohan was elected to the US and Indian National Academies of Engineering (2009), and was named an IBM Master Inventor (1997). This Distinguished Alumnus of IIT Madras (1977) received his PhD at the University of Texas at Austin (1981). He is an inventor of 50 patents. He is currently focused on Blockchain, Big Data and HTAP technologies (http://bit.ly/CMbcDB, http://bit.ly/CMgMDS). Since 2016, he has been a Distinguished Visiting Professor of China’s prestigious Tsinghua University. He has served on the advisory board of IEEE Spectrum, and on numerous conference and journal boards. Mohan is a frequent speaker in North America, Europe and India, and has given talks in 40 countries. He is very active on social media and has a huge network of followers. More information could be found in the Wikipedia page at http://bit.ly/CMwIkP

Jian Pei

Always eager to meet new challenges and opportunities, Jian Pei is currently Vice President, Big Data Platform and Products/Intelligent Supply Chains, at JD.com, China’s largest online retailer and its biggest overall retailer, as well as the country’s biggest Internet company by revenue. He is currently on leave from Simon Fraser University and holding the position of a Canada Research Chair (Tier 1) in Big Data Science. Recognized as an ACM Fellow and an IEEE Fellow, he published over 200 technical publications, which have been cited by 76000+ times, 33000+ in the last 5 years. His research has generated remarkable impact substantially beyond academia.

Michael Stonebraker

Michael Stonebraker is an adjunct professor at MIT. He earned his bachelor’s degree from Princeton University in 1965 and his master’s degree and his Ph.D. from the University of Michigan in 1967 and 1971, respectively. His awards include the ACM System Software Award (1992), the first SIGMOD Edgar F. Codd Innovations Award (1994), and the IEEE John von Neumann Medal (2005). In 1994 he was inducted as a Fellow of the Association for Computing Machinery. In 1997 he was elected a member of the National Academy of Engineering. In March 2015 it was announced he won the 2014 ACM Turing Award. In September 2015 he won the 2015 Commonwealth Award, chosen by council members of MassTLC.

Prof. Stonebraker has been a pioneer of data base research and technology for more than a quarter of a century. He was the main architect of the INGRES relational DBMS, and the object-relational DBMS, POSTGRES. These prototypes were developed at the University of California at Berkeley where Stonebraker was a Professor of Computer Science for twenty five years. More recently at MIT he was a co-architect of the Aurora/Borealis stream processing engine, the C-Store column-oriented DBMS, the H- Store transaction processing engine, the SciDB array DBMS, and the Data Tamer data curation system.

Jens Dittrich

Jens Dittrich is a Full Professor of Computer Science in the area of Databases, Data Management, and Big Data Analytics at Saarland University, Germany. Previous affiliations include U Marburg, SAP AG, and ETH Zurich. He received an Outrageous Ideas and Vision Paper Award at CIDR 2011, a BMBF VIP Grant in 2011, a best paper award at VLDB 2014, three CS teaching awards in 2011, 2013, and 2018, as well as several presentation awards including a qualification for the interdisciplinary German science slam finals in 2012 and three presentation awards at CIDR (Conference on Innovative Data systems Research, 2011, 2013, and 2015). He has been a PC member and area chair/group leader of prestigious international database conferences and journals such as PVLDB/VLDB, SIGMOD, ICDE, and VLDB Journal. He is a member of the scientific advisory board of Software AG. He was a keynote speaker at VLDB 2017: “Deep Learning (m)eats Databases” (http://bit.ly/DL_meats_DB) and will also be speaking at DEEM@SIGMOD (Data Management for End to End Machine learning, http://deem-workshop.org/). At Saarland University he co-organizes the Data Science Summer School.

His research focuses on big data analytics including in particular: data analytics on large datasets, scalability, main-memory databases, database indexing, reproducibility, and scalable data science. He enjoys coding data science problems in Python, in particular using the keras and tensorflow libraries for Deep Learning. Since 2017 he has been working on a start-up at the intersection of data science and databases (http://daimond.ai). He teaches some of his classes as flipped classrooms (https://www.youtube.com/user/jensdit) and tweets at https://twitter.com/jensdittrich.