Come hear about how different NYC Startups apply big data in the areas of Content Recommendations, Music, and Ad Tech. Area of focus include Geospatial data, real-time analytics, and data cleaning, normalization, and presentation. We'll also touch on tools such as Pig, Hive, Sqoop, HBase, MongoDB, Finagle and Storm and how they are used in the production environment working with real-world data.
• Alex Poon (Outbrain - VP, Engineering)
• Eric Czech (Next Big Sound - Chief Architect)
• Jonathan Lenaghan (PlaceIQ - Head of Data Science)
Moderator: Chris Wiggins (HackNY - Co-founder, Columbia - Associate Professor)
Bios of Panelists & Moderator
Alex is a VP of Engineering at Outbrain. He co-founded Visual Revenue, Inc., which was acquired by Outbrain in 2013. He loves data, real-time analytics and scalable systems. Prior to Visual Revenue, Alex was a co-founder at a nano technology startup, Phoebus Optoelectronics. During his career as a management consultant, he advised numerous Fortune 500 companies in the media and technology space. Alex began his career as an engineer at Lockheed Martin, building software for unmanned aerial vehicle and radio/wireless signal analysis. Alex received his MBA from Columbia Business School. He also holds a MS and BS degree in Electric Engineering from WPI and Boston University, respectively. Zerg is his preferred race at Starcraft II.
Jonathan Lenaghan is head of the PlaceIQ data science team. After receiving his PhD in physics at Yale University, Jonathan worked as a researcher studying phase transitions in the very early universe. His academic work focused on developing theoretical and computational tools to understand the statistical properties of very hot, strongly interacting matter. After leaving academia, Jonathan worked in scientific publishing as an assistant editor for the Physical Review, a leading physics journal. Prior to joining PlaceIQ, Jonathan spent several years in the quantitative trading industry where he applied large-scale optimization and machine learning techniques to tick-level equity pricing data and developed several real-time trading algorithms and analytics platforms.
Application and systems architect currently managing a 150+ Linux server deployment utilizing Apache Cassandra, Apache Hadoop (using Pig, Hive, Sqoop, and HBase), MongoDB, MySQL, and Chef. Responsible for server configuration, monitoring, and optimization as well as database schema design and application interface specification and implementation.
Chris Wiggins is an Associate Professor of applied mathematics at Columbia and holds a PhD in theoretical physics from Princeton. His research centers on “big data” in the natural sciences, developing machine learning and statistical inference methods for making sense of sequence and network data in physics and biology. He is the faculty representative for Columbia’s chapter of SIAM (Society for Industrial and Applied Mathematics) and the cofounder of hackNY.org, which organizes student hackathons and summer internships at startups to federate and mentor the next generation of NYC’s technologists.
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