Robert Hollebeek

While studying for his doctorate at UC Berkeley, Robert Hollebeek was a member of one of the first particle physics experiments to use completely digital techniques for acquiring data from fast electronic detectors with hundreds of thousands of electronic elements. This experiment was conducted at the Stanford Linear Accelerator and discovered the charm quark, later leading to the Nobel Prize for Burton Richter.

From the Stanford accelerator, Hollebeek joined Columbia University as a post-doctoral researcher and was the lead for computing and electronics from the Columbia group at the CERN Accelerator lab in Geneva Switzerland. From CERN, Hollebeek returned to Stanford as an Assistant Professor, and was involved there in several particle physics experiments with very large scale data and computing needs.

Hollebeek went to the University of Pennsylvania in 1986. The experiment he joined was the largest electronic detector in the world at the time. The research was conducted at the Fermi National Accelerator Laboratory in Chicago, and again involved the collection and analysis of ultra-large data samples. To accomplish this, Hollebeek began designing clustered computing architectures that were in turn used to simulate and analyze physics data. The experiment was one of two detectors responsible for the discovery of the top quark. During this time, Professor Hollebeek became interested in other areas with ultra-large data and computing needs in particular medical images. A pilot program in functional MRI for example used the parallel clustered computing architectures to analyze patterns in brain imaging. At that time, Professor Hollebeek joined an effort to design data storage and index handling for mammography images.

Professor Robert Hollebeek was the technical lead for the National Library of Medicine sponsored National Digital Mammography Archive (NDMA). This digital storage and search/retrieval system funded by the US National Insitutes of Health established a distributed grid of systems for medical records and image storage. Previously, Professor Hollebeek was also co-founder of the National Scalable Cluster Project at the University of Pennsylvania (NSCP); a multi-university consortium that built data mining infrastructure and ultra-large databases connected by high-speed wide area networks. His activities at the University of Pennsylvania included parallel and distributed computing approaches to the analysis of data from many fields including medical data, social and economic data, and scientific data. Common across these areas is the need for ultra-large data systems, data mining, scalable systems, and efficient access to terabyte and petabyte scale data. Dr. Hollebeek and the NSCP group won several national prizes for their work in distributed clustered systems and data mining.

The work on mammography led to the establishment of i3ARCHIVE, Inc. later renamed NDMA, which provides distributed grid systems for medical storage and records handling. Hollebeek was the Chief Technology Officer for NDMA and expanded the functionality of the original systems into other areas of medical records handling, new grid systems for electronic health records access, established physical and network infrastructure to support NDMA data systems, added new retrieval and search mechanisms, and helped create new products in the area of disaster recovery and data mining in medical records.

 In 2009-2011, Hollebeek proposed a new system for measuring proton beams used for cancer therapy at the Roberts Proton Therapy Center (University of Pennsylvania). A first single layer prototype of the new detector measured the beam with greatly increased precision and showed that it was possible to improve the ability of the therapy to target cancer cells more precisely and avoid radiation to sensitive adjacent areas.  A new detector, electronics readout, and computer processing system is being developed with multiple layers which could be used to provide crucial measurements of the positions where the protons in the beams stop within the patient.