IBM fellow and director, Watson Content Services, IBM
Shivakumar Vaithyanathan is an IBM fellow and director, Watson Content Services. Prior to his current position he managed the Machine Learning Systems group at IBM Research, and prior to that he started and built the Search & Analytics Department at IBM Almaden, with research focus ranging from Natural Language Processing to Entity Resolution and Machine Learning. Multiple technologies developed in this department ship with several IBM products, including IBM’s big data efforts. He also initiated and ovesaw the build-out of IBM’s next generation Enterprise search technology that currently powers IBM’s external-facing www.ibm.com. His research is at the cusp of three areas, namely natural language processing, machine learning, and databases. Prior to IBM, Shivakumar was one of the founding members of the Altavista Group at Digital. He has co-authored more than 40 papers in major conferences including ACL, EMNLP, SIGMOD, VLDB, ICML, NIPS, and UAI. He was an invited keynote speaker at the 2011 German Database Conference, and 2011 ACM SIGIR Industrial Track. He was an associate editor for Journal of Statistical Analysis and Data Mining from inception to 2012.
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Comments
Comparing SystemML to SQL was a neat idea. However, I don’t think the presenter realizes how negatively that came across. SQL was promised to solve so many different problems. However, it created 2 big ones. The first is that it created the need for database administrators which are hard to find and expensive. The second is that we now have a huge industry devoted to SQL tuning. People live with these 2 major issues on a daily basis.