RISE Talk 10/8/18: Fast, Efficient, and Complexity-overcoming; the needs for the next generation of the data analytic platform, a talk by Edmon Begoli, ORNL
October 8, 2018 —
Title: Fast, Efficient, and Complexity-overcoming — the needs for the next generation of the data analytic platform
Speaker: Edmon Begoli
Location: 405 Soda
Time: Monday, Oct. 8, 12 PM noon
Over the past ten years, we focused on the formulation of the platforms for large-scale, general-purpose data analytics that can bridge the gap between the traditional, business enterprise data systems,
and the new ones capable of processing data originating from the globally generated sources (web users, devices, etc.)
While many sophisticated solutions emerged, and many problems got to be solved, great many challenges related to the inherent complexity, origins, and structure of the data, its privacy, and the efficient derivation of insights from the data still remain.
Furthermore, there are still needs and the opportunities to bridge the technical domains of large-scale data processing (“Big Data”), data-intensive sciences and the applications, and the high-performance computing.
In this talk, and as a practical inspiration, we will review some of the national-scale projects that are happing at Oak Ridge National Laboratory (ORNL), and we will discuss relevant challenges, needs, and some preliminary solutions.
We will specifically reflect on the large-scale programs in precision medicine, population health, and other nationally significant domains, and we will discuss the needs and opportunities for further innovation and collaborative research.
Edmon Begoli, PhD, is the Chief Data Architect with the Computational Sciences and Engineering Division at Oak Ridge National Laboratory (ORNL). In this role, Edmon is responsible for the research and development of the advanced data-centric platforms and solutions in support of the applied research and mission-oriented programs, and for technical oversight of the data-related research programs. Edmon specializes in large-scale, heterogeneous platforms and methods for analytic data processing. He currently serves as the Principal Investigator (PI) for the joint DOE and VA precision medicine program (MVP CHAMPION), and for the forensic data science program with the Centers for Medicare and Medicaid Services. During his tenure at ORNL, Edmon also led several major national projects in healthcare and defense, and was a chief architect for Knowledge Discovery Initiative (KDI) for Centers for Medicare and Medicaid Services (CMS) — a large national program aimed at developing a platform for comprehensive and longitudinal analysis of the large, structured healthcare datasets (CMS data).
Prior to serving as the Chief Data Architect at ORNL, Edmon was a Chief Data Officer at the Joint Institute for Computational Sciences/National Institute for Computational Sciences (JICS/NICS), a NSF funded XSEDE national supercomputing facility and a joint institute between ORNL and University of Tennessee (UT). While at JICS, Edmon was one of the core members of the team that won and established the NSF-funded Southeast “Big Data” Hub, and was a principal investigator on a research project for the Intel Parallel Computing Center (PCC). Prior to working at the research institutes, Dr. Begoli held technology leadership positions at a technology startup, and the large commercial organizations.
Edmon is a member of the IEEE, ACM, and Apache Software Foundation (ASF) where he is a committer on the Apache Calcite project. He is also a principal member of the INCIT DM32.2 Task Group on Data Management and Databases.
Edmon holds undergraduate, graduate (University of Colorado-Boulder), and doctoral degrees (University of Tennessee) in Computer Science.