Current Research Focus
Eli is a researcher, author, and inventor, currently leading IBM’s research efforts for the development of a comprehensive environmental monitoring and management platform for the Jefferson Project at Lake George, NY. The Jefferson Project is a partnership between IBM, Rensselaer Polytechnic Institute, and The Fund for Lake George. The Jefferson Project partners are investing several years and several million dollars into solutions that not only improve the health of the lake, but as the Fund stated in its announcement of the project, “guide investment decisions … inform and, indeed, empower the constituency committed to protecting Lake George.” The project has numerous technical challenges including, but not limited to: utilizing existing data, along with new data to develop a number of complex physical and biological models of the lake and surrounding environment.. In parallel, we are deploying a complement of sensors in and around the lake to monitor the physical, chemical, and biological characteristics as was done in similar projects by IBM Research at Galway Bay, Ireland (SmartBay Galway) and the Hudson River in New York (The Beacon Institute for Rivers and Estuaries’ River and Estuary Observatory Network). Sensors will drive both a circulation model that describes how water moves within the lake, as well as driving a coupled instance of IBM's Deep Thunder weather modeling, and additional hydrological models, to help us understand the impact of external factors on the lake (e.g., precipitation and roadway salting in the winter). Further efforts will explore incorporating a coupled food web model that explores the impacts upon biological systems at work within the lake as a result of these external factors. The combined sensors and software infrastructure work in concert to form a “cyberphysical system” – a computational and visualization platform to collect data from sensors and to support advanced modeling approaches for Lake George.
Eli's Ph.D. dissertation is in the area of Infrastructure as a Service (IaaS) cloud computing optimization, specifically for load balancing and consolidation of virtual machines in a data center. Aspects of his research include peer-to-peer (hypervisor-to-hypervisor) cloud management software for rapid scale out, machine learning applied to virtual machine allocation within a single hypervisor instance, and predictive analytics for rebalancing and consolidating virtual machines across the hypervisors that make up a data center.
You can find a more comprehensive CV for Eli on Linkedin.
Running Xen: A Hands-On Guide to the Art of Virtualization
Prentice Hall, 2008
Linux for IBM System z9 and IBM zSeries
IBM Redbooks, 2006
Introduction to the New Mainframe: z/VM Basics
IBM RedBooks, 2008
ISBN-10: 0738488550 ISBN-13: 978-0738488554
(Presently In production)