Born and raised in the greater Seattle-area, Greg Hay has more than 24 years of experience working with Relational Databases. His industry experience includes positions with Microsoft, Walt Disney, WebMD and Bill and Melinda Gates Foundation among many others.

Greg is an experienced educator, presently lectures at University of Washington and has successfully developed curriculum and taught numerous Database and Business Intelligence courses. He has also taught Database courses at Microsoft, University of Chicago, City University of Seattle and Bellevue College. He holds a Master’s degree in Information Management from University of Washington.


Brendan Farrell has a PhD in Applied Mathematics, taught at Caltech and has a dozen publications. He is a Data Scientist and engineer who loves math, algorithms and the power of data.

Brendan is the Founder and primary Data Scientist at HowLoud, Inc. He has implemented Machine Learning algorithms for commercial problems ranging from automated text analysis to traffic modeling to financial modeling.


Revin is a Big Data Development Engineer at Expedia with extensive hands-on experience in Hadoop eco-system components and Spark. Revin’s expertise include HDFS, MapReduce, Hive, Spark, Sqoop, Big Data Services in Amazon Web Services, programming in Java and Python, Bash scripting, MongoDB, Sql Server and PostgresQL.

He has more than 13 years of hands-on design and development experience in Data centered Analytical solutions and has completed entire life cycle of several Big Data projects in multi-terabyte environments. Revin’s prior work experience includes positions with Microsoft, International Game Technology and CapitalOne.



Ramkumar Hariharan is a Research Scientist at the Institute for Systems Biology, Seattle where he analyzes biomedical data. He is also a visiting scientist to RIKEN, Japan. He uses both Python and R statistical programming language extensively on his job.

He holds a PhD in an interdisciplinary field. In his career so far, he has transitioned seamlessly across different job profiles globally, stating out as a bioinformatics faculty in India. Outside of work, he loves spending time with his family, trying out new eat-outs, and is passionate about writing short stories for children.


Abhishek works in the Azure Machine Learning team at Microsoft. He has several papers and patents in the field of data science, machine learning and big data. He has been using machine learning in diverse real-world scenarios, such as ad pricing, click prediction, financial forecasting, user segmentation, customer churn prediction and natural language processing.

Abhishek blends ML theory with practice, and has hands-on experience with several machine learning libraries such as scikit-learn, vowpal wabbit, sparkml, tensor-flow and cntk. Abhishek did his M.S. from SUNY, Stony Brook with a focus on unsupervised learning and graphical models.



Sharath is a Data Scientist with strong experience in software and database development and has been working with Microsoft since 2004. Sharath’s expertise include Machine Learning algorithms for regression and classification, data analysis, data visualizations and hypothesis testing. He currently works on operationalizing machine learning solutions on the Azure platform for the Azure Machine Learning team in Microsoft.

Sharath holds a Master’s degree in Computer Science from the University of Louisiana at Lafayette and a Bachelors degree in Chemical Engineering from IIT, Madras.


Twinkle is a Software Engineer at International Game Technology with extensive experience in designing, developing and supporting Relational Databases. She leads and mentors junior Engineers at IGT and enjoys resolving complex problems.

Prior to joining IGT in 2010, Twinkle worked as Systems Specialist for IBM. Her interests include T-Sql programming, indexing and performance tuning. Twinkle is certified in ITIL Foundation V2 and is Microsoft Certified Technology Specialist in SQL Server.