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`CURRICULUM VITAE
`January 24, 2019
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`Work Address:
`Department of Computer Science and Engineering
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`University of Minnesota
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`4-192 Keller Hall, 200 Union Street SE
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`Minneapolis, MN 55455-0159
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`Phone: (612) 626-0044
`Fax: (612) 625-0572
`Email: jon@cs.umn.edu
`URL: http://www.cs.umn.edu/-jon
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`EDUCATION
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`Ph.D., Computer Science, University of Virginia, 1995.
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`M.S., Computer Science, University of Virginia, 1989.
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`B.S., Applied Mathematics and Computer Science, Carnegie-Mellon University, 1984.
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`PROFESSIONAL EXPERIENCE
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`Univ. of Minnesota (Summer 2012 to date)
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`Professor, Computer Science
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`Associate Professor, Computer Science
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`Univ. of Minnesota (Fall 2003 to Spring 2012)
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`Visiting Researcher and Distinguished Visitor
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`National e-Science Center, University of Edinburgh (2007-2008)
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`Assistant Professor, Computer Science
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`Univ. of Minnesota (1999-2003)
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`Assistant Professor, Computer Science
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`Univ. of Texas San Antonio (1995-1999)
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`Member of Technical Staff
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`Mitre Corporation, McLean Virginia (1989-1991)
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`Software A&E, Arlington Virginia (1984-1987)
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`Software Engineer
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`PROFESSIONAL ACTIVITIES
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`Tau Beta Engineering Honor Society, Member ACM, IEEE Senior Member
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`ACADEMIC AWARDS AND HONORS
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`(IC2E) 2015.•Best paper nominee, IEEE International Conference on Cloud Engineering
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`•Best paper, IEEE Grid conference, 2009.
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`2007-2008.University of Edinburgh, •Honorary Fellow, College of Science and Engineering,
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`•IEEE Senior Member, promoted 2003.
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`•Success Story, ARL HPC (HPCMO), Virtual Data Grid Project, 2002.
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`1996.•CAREER Award, National Science Foundation,
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`SC, 1995.Computing with Legion", •Supercomputing Award for "High-Performance
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`1995.Medal of Excellence, of Virginia Teaching •Teaching Award, University
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`EX 1007 Page 1
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`LITIGATION SUPPORT EXPERIENCE
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`Testifying Expert
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`•client: Faegre Baker Daniels LLP, case: ICN Acquisition, LLC vs. ipDataTel, LLC, area: home alarm systems
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`and networks, IPR declarations, represented: petitioner status: active, 2019. Likely expert witness in litigation.
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`•client: Cooley LLP, case: Vaporstream Inc vs. Snapchat Inc, area: mobile computing, project: patent analysis,
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`expert reports, represented: defense, status: stay, 2018.
`deposition,
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`•Thompson & Knight LLP, SEVEN NETWORKS, LLC, vs. GOOGLE LLC, area: mobile computing, project:
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`patent analysis, claim construction, represented: plaintiff, status: finished, 2018.
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`•client: Fenwick & West LLP, case: IBM vs. Groupon, area: security, web, client-server, project: patent
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`analysis, expert reports,
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`represented: defense, status: finished, 2017-2018.
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`deposition, testifying,
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`•client: DLA Piper LLP, WORKSPOT, Inc. vs. CITRIX SYSTEMS, INC., area: security, IPR declaration,
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`represented: petitioner, status: active.
`deposition,
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`•client: Keker, Van Nest & Peters LLP, BMC SOFTWARE, INC., vs. CHERWELL SOFTWARE. LLC, area:
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`software systems, IPR declaration, represented: petitioner, status: active.
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`•client: Cooley LLP, case: Sound View Inc vs. Faccbook, area: databases, web, project: patent analysis, expert
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`reports, represented: defense, status: settled, 2018.
`deposition,
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`represented:IPR declaration, •client: Fenwick & West LLP, case: IBM vs. Groupon vs. IBM, area: security,
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`patent owner, status: finished, 2017.
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`•client: Finnegan, Henderson, Farabow, Garrett & Dunner, LLP, area: Internet applications, IPR declaration,
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`represented: petitioner, status: finished, 2017. No associated litigation.
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`•client: McDonnell Boehnen Hulbert & Berghoff LLP, case: Trading Technologies Inc., area: distributed sys
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`owner, status: finished, declaration, represented: patent tems, project: Patent Examination,
`examiner inter
`view, 2016.
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`•client: Fenwick & West LLP, case: Actifio vs. Dclphix, area: cloud storage, project: patent analysis, expert
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`reports, represented: defense, status: finished (settled prior to trial), 2016.
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`•client: F isch Sigler LLP, case: Kaavo vs. Amazon and Tier3, area: cloud computing, IPR declarations,
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`represented: petitioner, status: finished, 2016.
`sition,
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`•client: Morrison and Foerster LLP, case: Ancora vs. Apple Inc, area: security, CBM declaration, represented:
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`petitioner, status: finished (settled prior to trial), 2016.
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`•client: Finnegan, Henderson, Farabow, Garrett & Dunner, LLP, area: mobile computer systems, 3 IPR decla
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`rations,
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`represented: petitioner, status: finished, 2016. No associated litigation.
`two depositions,
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`•client: Cooley LLP, case: BMC Inc vs. S rvic Now In·, area: computer systems, project: patent analysis,
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`expert reports, represented: defense, status: finished (settled prior to trial), 2016.
`deposition,
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`•client: Fish & Richardson P.C., case: Ericsson Inc vs. Apple Inc, area: mobile systems, project: patent
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`analysis, represented: defense, status: finished, 2015.
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`•client: Morrison and Foerster LLP, case: Good Technology Inc vs. Airwatch Inc, area: mobile systems, project:
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`patent analysis, 3 expert reports, represented: defense, status: finished (settled prior to trial), 2015.
`deposition,
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`•client: Troutman Sanders. Intellectual Ventures I LLC vs. Capitol One Financial Corp, claim construction
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`declarations, area: mobile interfaces, represented: defense, status: finished. 2015.
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`•client: Bryan Cave LLP, case: Symantec vs. Veeam Software Corporation, area: storage systems, IPR. decla
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`ration, represented: patent owner, status: finished, 2014.
`depo.sition,
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`EX 1007 Page 2
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`•client: F innegan, Henderson, Farabow, Garrett & Dunner, LLP, case: Clouding IP vs. Rackspace, area: storage
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`systems, project: patent analysis, IPR and CBM declarations, represented: petitioner, status:
`two depositions,
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`finished, 2014.
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`•client: Sidley Austin LLP, case: Motorola vs. Microsoft, area: mobile instant messaging, project: software
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`patent analysis, expert reports, represented: defense, status: finished (settled prior to trial), 2011-
`deposition,
`2012.
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`•client: Baker & McKenzie LLP, case: WMR e-PIN vs. Wells Fargo, area: Internet e-commerce applications,
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`project: software, patent analysis, expert reports,
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`represented: defense, status: closed,
`testifying,
`deposition,
`2008-2009.
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`Consulting Expert
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`•client: W illiam G. Osborne, Esq., Superior Edge vs. Monsanto, area: distributed software, project: code
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`analysis, report, represented: plaintiff, status: closed, 2015.
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`•client: Arnold & Porter LLP, Rosebud v. Adobe, area: distributed software, project: patent analysis, repre
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`sented: defense, status: closed, 2015.
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`•client: Jones Day, Summit 6 vs. Apple, area: web technologies, project: patent analysis, represented: defense,
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`status: closed, 2014.
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`•client: Ropes & Gray LLP, case: Parallel Iron vs. EMC, area: storage systems, project: patent analysis,
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`represented: defense, status: closed, 2012-2013.
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`•client: Bridges & Mavrakakis LLP, case: Nokia/HTC vs. Apple, area: operating systems, project: software,
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`patent analysis, represented: defense, status: closed, 2011.
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`Professional references
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`•P hil Haack: (Fenwick & West LLP): www.fenwick.com/professionals/pages/philliphaack.aspx
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`•P riya Viswanath: (Cooley LLP): www.cooley.com/pviswanath
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`•Diek Van Nort (Morrison & Foerster LLP): www.mofo.com/people/v/van-nort-diek-o
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`•Joshua Goldberg (Finnegan LLP): http:/ /www.finnegan.com/
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`•Jeffrey Totten (Finnegan LLP): http://www.finnegan.com/ JeffreyTotten/
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`•James Patterson (Patterson T hucnte LLP): http://www.ptslaw.com
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`EX 1007 Page 3
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`MAJOR RESEARCH AFFILIATIONS
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`1.Digital Technology Center, University of Minnesota, Investigator. The Digital Technology Center
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`(DTC)'s goal is to create, promote, and coordinate cooperative interdisciplinary advanced technology initiatives
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`between University, government, industry, and to serve as a point of entry into research and development
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`partnerships with various partners. The DTC is a hub of innovation and excellence at the University of
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`Minnesota in the digital technologies serving the industrial, educational, and public needs of the state of
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`Minnesota and the nation. The DTC integrates research, education, and outreach in digital design, computer
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`graphics and visualization, telecommunications, intelligent data storage and retrieval systems, multimedia,
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`datamining, scientific computation, and other digital technologies. See www. dtc. u.mn. edu.
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`The
`2.CRIS:Center for Research in Intelligent Storage, University of Minnesota, Investigator.
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`Center for Research in Intelligent Storage (CRIS) is a partnership between universities and industry, featuring
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`high-quality, industrially relevant fundamental research, strong industrial support of collaboration in research
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`and education, and direct transfer of university developed ideas, research results, and technology to U.S.
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`industry. Research areas include storage and memory technologies, big data, cloud computing, backup/restore,
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`u.mn. edu.data deduplication, and file systems. See eris. cs.
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`4
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`EX 1007 Page 4
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`GRANT FUNDING
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`CSR: Small: Location, location, location (13): Support for Geo-Centric Appli1.Co-Principal Investigator,
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`cations, NSF, 2016-2019, $528K (Pl Chandra).
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`II-NEW: One Cloud Does Not Fit All: Minnesota Integrated cloud Systems2.Co-Principal Investigator,
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`research Testbed (MIST), NSF, 2013-2016, $350K, (PI DU, co-Pls Chandra, Zhang).
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`Science,to Enable Extreme Collaborative An Integrated Middleware Framework 3.Principal Investigator,
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`DOE, 2012-2015, $342K UMn share, collaborative with Rutgers and University of Chicago.
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`T hrough The Cloud, NSF, 2012-CSR: Medium: Enriching Mobile User Experience 4.Principal Investigator,
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`2015, $700K (co-PI Chandra, Karypis).
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`Data-Intensive ApplicationsDC: Small: One T housand Points of Light: Accelerating 5.Principal Investigator,
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`By Proxy, NSF, 2009-2012, $482K, including REU supplement $36K (co-PI Chandra).
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`Storage, NSF,I/UCRC Center on Intelligent A Multi-University 6.Co-Investigator, Collaborative Research:
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`2009-2014, $400K, (DU PI, many co-Pis).
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`of Edinburgh,University Centre, National E-Science Grid Computing for E-Science, 7.Principal Investigator,
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`2007-2008, $52K.
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`8.Co-Investigator, ePCRN: Electronic Primary Care Research Network, NIH Roadmap, 2006-2008, $50K (CSE
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`share annual), (Peterson PI, Delaney PI, several co-investigators).
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`9.Co-Principal Investigator, ITR: A Data Mining and Exploration Middleware for Grid and Distributed
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`Computing, NSF ITR, 2003-2007, $1.5M, (Kumar PI, Weissman co-PI).
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`10.Investigator, Intelligent Storage Consortium, DTC, 2003-2009, $250K (Du PI, Weissman, Lilja, Tewfik, Kim
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`co-Pis).
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`11.Investigator, MRJ: Development of a System for Interactive Analysis and Visualization of Multi-Terabyte
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`Datasets, NSF MRI, 2004-2006, $300K (Woodward PI).
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`12.Contributor, NIH NCRR, Intelligent Data Storage Support for Microarray data, equipment, (Mayo Clinic
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`PI, with Du), 2004, $222K.
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`13.Co-Principal Investigator, Intelligent Storage Consortium -Engenio, Engenio Information Technologies,
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`2004-2005, $45K, (Du PI, Weissman co-PI).
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`Scienof Energy (Office of Advanced Easy, Department Making Parallel Computing 14.Principal Investigator,
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`tific Computing Research), 2002-2007, $250K, sole Pl.
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`$240K, soleNSF ACR-CNS, 2003-2008, Grid Services, A Framework for Adaptive 15.Principal Investigator,
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`PI.
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`16.Principal Investigator, Towards Community Services: Putting Parallel Network Services On-line, NSF EIA
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`NGS Program, 2002-2003, $30K, sole PI.
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`NSF EIA Research ResourcesCollaborative Data Analysis and Visualization, 17.Co-Principal Investigator,
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`(Collaborative Research), 2002-2005, $SOOK (incl. 2 RA's shared with Du), (Woodward PI, Weissman, Du,
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`R.etzcl, Wetherby co-Pls.)
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`and the Virtual Data Grid, Army High PerformanceEnabling Technologies 18.Investigator, Metacomputing:
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`Computing and Research Center (AHPCRC), 2000-2004, $260K, original contributor to center proposal.
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`for Parallel and Distributed Systems, Resource Management 19.Principal Investigator, NSF CAREER award
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`ACR, 1996-2001, $200K, REU supplement $5K (2000), sole PI.
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`File Access Paradigm, Texas AdvancedSmart File Objects: An Application-directed 20.Principal Investigator,
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`Research Program ARP-010115-226, 1997-2000, $106K, sole PI.
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`EX 1007 Page 5
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`21.Participant, Telecommunication Networks for Mobile and Distributed Computing and Communications,
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`AFOSR-F49620-96-1-0472, 1996-2000, $2M, (PI Hiromoto).
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`22.Co-Principal Investigator, Building a Pipeline for Minority Scholars, NSF CISE MI-I CDA-9633299, 1996
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`-1999, $I.3M. (Hiromoto PI, Weissman, Das, Boppana, Psarris, Jeffery, Rosen co-Pis).
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`23.Fellowship, Applying Parallel Object-Oriented Computing to Scientific Applications, NASA Graduate Student
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`Researchers Program Fellowship, Jet Propulsion Laboratory, 1991-1995, $66K.
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`EX 1007 Page 6
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`PUBLICATIONS
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`Journal Articles: for up-to-date-list, see www.cs.umn.edu/-jon
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`Dis1.Albert Jonathan, Mathew Ryden, Kwangsung Oh, Abhishek Chandra, and Jon Weissman, Nebula:
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`tributed Edge Cloud for Data Intensive Computing,
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`IEEE Transactions on Parallel and Distributed Systems,
`Vol. 28, No. 11, Nov 2017.
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`OptimizationEnd-to-end 2. Benjamin Heintz, Abhishek Chandra, Ramesh Sitaraman, and Jon B. Weissman,
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`for Geo-Distributed MapReduce,
`Vol. 4, No. 3, July 2016.
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`IEEE Transactions on Cloud Computing,
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`3.Jinoh Kim, Seonho Kim, and Jon B. Weissman, A Security-enabled Grid System for MINDS Distributed
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`Data Mining,
`2014.
`Journal of Grid Computing,
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`4.Murray Cole, Shantenu Jha, Daniel S. Katz, Manish Parashar, Omer Rana, and Jon B. Weissman, Dis
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`tributed Computing Practice for Large-Scale Science and Engineering Applications,
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`Concurrency: Practice
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`Volume 25, Issue 11, September 2013.
`and Experience,
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`5.Adam Barker,
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`Jon B. Weissman,
`5(3), 2012.
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`actions on Services Computing,
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`Jano van Hemert, Accelerating Service-Oriented Workflows,
`IEEE Trans
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`Estimation for LargePerformance Passive Network 6.Jinoh Kim, Abhishek Chandra and Jon B. Weissman,
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`Data-intensive Computing,
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`22(8), August 2011.
`scale,
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`IEEE Transactions on Parallel and Distributed Systems,
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`7.Jia Jingxi, Bharadwaj Veeravalli, and Jon B. Weissman, Scheduling Multi-source Divisible Loads on Arbi
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`trary Networks,
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`21(4), April 2010.
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`IEEE Transactions on Parallel and Distributed Systems,
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`8.Jinoh Kim, Abhishek Chandra and Jon B. Weissman, Using Data Accessibility for Resource Selection in
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`Large-scale Distributed Systems,
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`20(6), June 2009.
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`IEEE Transactions on Parallel and Distributed Systems,
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`scalable perforNam, Adaptive middleware supporting Young-Kwang 9.Byoung-Dai Lee, Jon B. Weissman,
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`mance for high-end network services,
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`32(3), May 2009.
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`Journal of Network and Computer Applications,
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`Avoiding WorkflowArchitecture: The Circulate van Hemert, 10.Adam Barker, Jon B. Weissman and Jana
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`Bottlenecks Caused By Centralised Orchestration,
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`12(2), 2009.
`Journal of Cluster Computing,
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`Scheduling on UnReputation-Based Adaptive 11.Jason D. Sonnek, Abhishek Chandra, and Jon B. Weissman,
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`reliable Distributed Infrastructures,
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`18(11), November
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`IEEE Transactions on Parallel and Distributed Systems,
`2007.
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`Tree Topology for Data12.Darin England, Bharadwaj Veeravalli, A Robust Spanning and Jon B. Weissman,
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`Collection and Dissemination in Distributed Environments,
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`IEEE Transactions for Parallel and Distributed
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`18(5), May 2007.
`Systems,
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`inWorkload Distribution 13.Rahul Trivedi, Abhishek Chandra, and Jon B. Weissman, Heterogeity-Aware
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`Donation Based Grids, invited to the International
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`Journal for High Performance Computing and Applications
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`(IJHPCA), 20(4), 2006.
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`invited to theComputing, for On-demand Leasing Policy A Resource 14.Darin England and Jon B. Weissman,
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`(IJHPCA), 20(1), 2006.
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`International Journal for High Performance Computing and Applications
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`Scheduling: The Best of BothAbburi Rao, "Integrated and Lakshman 15.Jon B. Weissman, Darin England,
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`Worlds,"
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`63(6), 2003.
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`Journal of Parnllel and Distributed Computing,
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`for Delivering High-EndGrid: An Architecture 16.Jon B. Weissman and Byoung-Dai Lee, "The Virtual Service
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`Services",
`Vol. 14, No. 4, April 2002.
`Network
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`Concurrency: Practice and Experience,
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`in Clusters", Parallel Applications of Adapting 17.Jon B. Weissman, "Predicting the Cost and Benefit
`Journal
`Vol. G2, No. 8, August 2002.
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`Computing, of Parallel and Distributed
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`Remote File Access for Parallel and"Optimiiing 18.Jon B. Weissman, Mike Gingras, and Mahesh Marina,
`
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`
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`Distributed Network Applications"
`Vol. 61, No. 11, November
`
`
`Journal of Parallel and Distributed Computing,
`2001.
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`7
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`EX 1007 Page 7
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`Networks", in Workstation of SPMD Programs 19.Jon B. Weissman, "Prophet: Automated Scheduling
`Con
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`
`
`Vol. 11, No. 6, August 1999.
`
`currency: Practice and Experience,
`
`Processing", for Parallel Computing of Wide-Arca 20.Jon B. Weissman "Gallop: The Benefits
`
`
`
`
`
`
`Journal of
`
`Vol. 54, No. 2, November 1998.
`
`
`Parallel and Distributed Computing,
`
`
`in Distributed Networks," 21.Jon B. Weissman and Xin Zhao, "Scheduling Parallel Applications
`
`
`
`
`Journal of
`
`Vol. 1, No. 1, May 1998, invited paper.
`
`Cluster Computing,
`
`for DynamicSupport Run-time Strayer, "Portable 22.Andrew S. Grimshaw, Jon B. Weissman, and W. Timothy
`
`
`
`
`
`
`
`
`Object-Oriented Parallel Processing,"
`Vol. 14, No. 2, May 1996.
`
`
`ACM Transactions on Computer Systems,
`
`
`
`
`
`
`inParallel Computations for Partitioning 23.Jon B. Weissman and Andrew S. Grimshaw, "A Framework
`
`Heterogeneous Environments",
`Vol. 7, No. 5, August 1995.
`
`
`Concurrency: Practice and Experience,
`
`An Approach24.Andrew Grimshaw, Jon B. Weissman, Emily West, and Edmond Loyot, Jr., "Metasystems:
`
`
`
`
`
`
`
`Combining Parallel Processing and Heterogeneous Distributed Computing Systems",
`
`Journal of Parallel and
`Vol. 21, No. 3, June 1994.
`Distributed Computing,
`
`Object-Oriented Computation25.Jon B. Weissman, Andrew S. Grimshaw, and Robert R. Ferraro, "Parallel
`
`
`
`
`
`Applied to a Finite Element Problem,"
`Vol. 2, No. 4, 1993.
`Journal of Scientific Programming,
`
`Books and Book Chapters
`
`in CloudOptimization in MapReduce, 1.Benjamin Heintz, Abhishek Chandra and Jon Weissman, Cross-Phase
`
`
`
`
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`
`
`
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`
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`Computing for Data-Intensive Applications, Springer, 2014.
`
`
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`
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`
`
`
`
`Grid Computing,Networks, in Desktop in Volunteer 2.Jon B. Weissman and Jinoh Kim, Network Awareness
`
`
`
`CRC Press, 2013.
`
`
`
`
`
`Arca),Systems Scheduling (Operating 3.Steve Chapin and Jon B. Weissman, Distributed and Multiprocessor
`
`
`
`
`
`
`
`
`The Computer Science and Engineering Handbook, 2004.
`
`EX 1007 Page 8
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`
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`Highly Selective Articles: : for up-to-date-list, see www.cs.umn.edu/-jon
`
`
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`
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`StreamAdaptability in Wide-Area 1.Albert Jonathan, Abhsishek Chandra, and Jon B. Weissman, Rethinking
`
`
`
`
`
`in Cloud Computing on Hot Topics Processing Systems, Workshop (HotCloud '18), June 2018.
`
`Data Placement inMulti-tiered Automated 2.Kwangsung Oh, Abhishek Chandra and Jon Weissman, TripS:
`
`
`
`
`
`
`
`
`
`
`
`
`Conference Systems and Storage a Geo-distributed Cloud Environment, 10th ACM International (SYSTOR),
`May 2017, Haifa Israel.
`
`Geo-DistributedFlexible Multi-Tiered 3.Kwangsung Oh, Abhishek Chandra, and Jon Weissman, Wiera: Towards
`
`
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`
`
`
`
`
`
`
`25th IEEE International Symposium on High Performance Distributed Computing
`
`Cloud Storage Instances,
`(HPDC}, June 2016, Kyoto, Japan.
`
`4.Matteo Turilli, Feng Liu, Zhao Zhang, Andre Merzky, Michael Wilde, Jon Weissman, Daniel S. Katz, and
`
`
`
`30th IEEE
`
`
`
`
`
`Shantenu Jha, Integrating Abstractions to Enhance the Execution of Distributed Applications,
`
`
`
`
`
`
`
`{IPDPS), Processing Symposium International Parallel & Distributed May 2016, Chicago, II.
`
`for Geo5. Albert Jonathan, Abhishek Chandra, and Resource Manager Jon Weissman, Awan: Locality-aware
`
`
`
`
`
`IEEE International Conference on Cloud Engineering,
`
`
`distributed Data-intensive Applications,
`April 2016,
`
`Berlin, Germany.
`
`Request Strategy for Large-ScaleAn Adaptive Resource Job Bundling: 6.Francis Liu and Jon Weissman, Elastic
`
`
`
`
`
`
`
`
`
`
`
`Computing, Networking,Conference for High Performance Parallel Applications, to appear in the International
`
`
`
`Storage, and Analysis {SC'15},
`
`Nov 2015, Austin, TX.
`
`7.John Kolb, Prashant Chaudhary, Alexander Schillinger, Abhishek Chandra and Jon Weissman, Cloud-Based,
`
`
`
`
`
`
`
`
`IEEE International Conference on Cloud Engineering,
`User-Centric
`Mobile Application,
`March 2015, Tempe,
`AZ.
`
`Flexible Multi-Tiered8.Ajaykrishna Raghavan, Abhishek Chandra, and Jon B. Weissman, Tiera: Towards
`
`
`
`
`
`
`
`
`ACM Middleware,
`
`Cloud Storage Instances,
`2014.
`
`User Interest9.John Kolb, Will Myott, Thao Nguyen, Abhishek Chandra and Jon B. Weissman, Exploiting
`
`
`
`
`IEEE Conference on Mobile Cloud Computing,
`
`
`in Data-Driven Cloud-based Mobile Optimization,
`April 2014,
`Oxford, UK
`
`Edge CloudDistributed 10.Mathew Ryden, Kwangsung Oh, Abhishek Chandra and Jon B. Weissman, Nebula:
`
`
`
`
`
`
`
`IEEE International Conference on Cloud Engineering,
`
`for Data Intensive Computing,
`March 2014, Boston,
`MA
`
`
`
`Edge Clouds, Heintz Decentralized 11.Abhishek Chandra, Jon Weissman, and Benjamin
`
`
`
`
`puting,
`2013.
`
`IEEE Internet Com
`
`Optimization in12.Benjamin Heintz, Chenyu Wang, Abhishek Chandra, and Jon B. Weissman, Cross-Phase
`
`
`
`
`
`
`IEEE International Conference on Cloud Engineering,
`MapReduce,
`
`March 2013, San Francisco, CA
`
`13.Chonglei Mei, Daniel Taylor, Chenyu Wang, Abhishek Chandra, and Jon B. Weissman, Sharing-aware
`
`
`
`
`
`
`IEEE 5th International Conference on Cloud Computing,
`
`Cloud-based Mobile Outsourcing
`2012.
`
`Framework for Video De-duplication,An Application-Aware 14.Atul Katiyar and Jon B. Weissman, ViDeDup:
`
`
`
`
`
`
`
`Third Usenix Workshop on Hot Topics in Storage and File Systems
`
`
`(HotStorage'll), Portland, OR 2011.
`
`Algorithmand Certification 15.Louis-Claude Canon, Emmanuel Jeannot, and Jon B. Weissman, A Scheduling
`
`
`
`
`
`
`
`
`
`31st IEEE International Conference on Distributed Computing Sys
`
`
`
`for Defeating Collusion in Desktop Grids,
`
`
`tems (ICDCS), Minneapolis, MN, June 2011.
`
`for Characterizing16.Louis-Claude Canon, Emmanuel Jeannot, and Jon B. Weissman, A Dynamic Approach
`
`
`
`
`
`
`
`
`24th IEEE International Parallel and Distributed Processing Symposium
`
`
`Collusion in Desktop Grids,
`(IPDPS),
`2010.
`
`to Build Clouds,Voluntary Resources Using Distributed 17.Abhishek Chandra and Jon B. Weissman, Nebulas:
`
`
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`
`
`
`
`
`Workshop on Hot Topics in Cloud Computing
`
`(HotCloud '09), June 2009.
`
`9
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`EX 1007 Page 9
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`
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`18.Jon B. Weissman and Siddharth Ramakrishnan, Using Proxies to Accelerate Cloud Applications,
`Workshop
`
`
`
`
`
`
`{HotCloud '09), .June 2009.
`on Hot Topics in Cloud Computing
`
`19.Adam Barker, Jon B. Weissman and .Jano van Hemert, Eliminating the Middle-Man: Peer-to-Peer Dataflow,
`
`
`
`
`
`
`(HPDC), Boston, MA, June
`
`
`
`
`17th IEEE International Symposium on High Performance Distributed Computing
`2008.
`
`20.Jinoh Kim, Abhishek Chandra and Jon B. Weissman, Accessibility-based Resource Selection in Loosely
`
`
`
`
`
`coupled Distributed Systems,
`(ICDCS),
`
`
`
`
`28th IEEE International Conference on Distributed Computing Systems
`
`Beijing, China, June 2008.
`
`21.Krishnaveni Budati, Abhishek Chandra, and Jon B. Weissman, RIDGE: Combining Reliability and Per
`
`
`
`
`
`
`
`
`formance in Open Grid Platforms,
`
`
`
`16th IEEE International Symposium on High Performance Distributed
`(HPDC), June 2007.
`Computing
`
`22.Jason D. Sonnek, Mukesh Nathan, Abhishek Chandra, and Jon B. Weissman, Reputation Based Schedul
`
`
`
`
`
`ing on Unreliable Distributed Infrastructures,
`
`
`
`The 26th International Conference on Distributed Computing
`
`(ICDCS), July 2006.
`Systems
`
`23.Darin England, Jayashree Sadagopan, and Jon B. Weissman, A New Metric for Robustness with Application
`
`
`
`
`
`to Job Scheduling,
`
`
`
`
`
`Fourteenth IEEE International Symposium on High Performance Distributed Computing
`(HPDC), 2005.
`
`24.Jon B. Weissman and Xin Zhao, "Run-time Support for Scheduling Parallel Applications in Heterogeneous
`
`
`
`
`
`NOWs," Proceedings
`
`
`
`
`of the Sixth IEEE International Symposium on High Performance Distributed Computing
`(HPDC), August 1997.
`
`25.Jon B. Weissman and Andrew S. Grimshaw, "A Federated Model for Scheduling in Wide-Area Systems,"
`
`
`
`
`(HPDC),
`
`
`
`
`
`Proceedings of the Fifth IEEE International Symposium on High Performance Distributed Computing
`August 1996.
`
`26.Jon B. Weissman and Andrew S. Grimshaw, "Network Partitioning of Data Parallel Computations,"
`
`
`
`
`Pro
`(HPDC),
`
`
`
`
`
`ceedings of the Third IEEE International Symposium on High Performance Distributed Computing
`August 1994.
`
`10
`
`EX 1007 Page 10
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`
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`Selective Articles: : for up-to-date-list, see www.cs.umn.edu;-jon
`
`Sharing in Mobile Cloud27.Albert Jonathan, Abhishek Chandra, and Jon Weissman, Locality-Aware Load
`
`
`
`
`
`
`
`
`IEEE/ A CM International Conference on Utility and Cloud Computing,
`Computing
`2017.
`
`in Geo-Distributed Edge28.Albert Jonathan, Abhishek Chandra, and Jon Weissman, Ensuring Reliability
`
`
`
`
`
`
`
`
`
`Cloud, IEEE RWS (Resilience Week), Wilmington, Delaware, 2017.
`
`forData Locality 29.Kwangsung Oh, Ajaykrishna Raghavan, Abhishek Chandra and Jon Weissman, Redefining
`
`
`
`
`
`
`
`
`
`
`International Workshop on Software-Defined Ecosystems
`
`Cross-Data Center Storage,
`
`(BigSystem 2015), June
`
`2015, Portland, OR.
`
`30.William Myott, Thao Nguyen, Abhishek Chandra, George Karypis, and Jon B. Weissman, Opportunities
`
`
`
`
`
`Conference on Collaborationfor Data-Driven Cloud-based Mobile Optimization, invited to 2014 International
`
`
`
`
`
`
`Technologies and Systems,
`
`Minneapolis, MN, May 2014.
`
`Dis31.Siddharth Ramakrishna, Robert Reutiman, Abhishek Chandra, and Jon B. Weissman, Accelerating
`
`
`
`
`
`
`
`
`
`
`Second International Workshop on Workfiow Models, Systems, Ser
`
`tributed Workflows With Edge Resources,
`
`vices and Applications in the Cloud {CloudFlow),
`Boston MA, May 2013.
`
`32.Mike Cardosa, Anshuman Nangia, Chenyu Wang, Abhishek Chandra and Jon B. Weissman, Exploring
`
`
`
`
`
`andWorkshop on MapReduce MapReduce Efficiency with Highly-Distributed Data, The Second International
`
`
`
`
`its Applications
`
`(MapReduce '11), June 2011.
`
`33.Pradeep Sundarrajan, Abhishek Gupta, Matthew Ryden, Rohit Nair, Abhishek Chandra, and Jon B. Weiss
`
`
`
`
`
`
`
`
`Workshop on DataCloud, The Fourth International
`man, Early Experience with the Distributed Nebula
`
`
`Intensive Distributed Computing
`
`(DIDC '11), June 2011.
`
`Perspectives on34.Shantenu Jha, Daniel S. Katz, Manish Parashar, Omer Rana, and Jon B. Weissman, Critical
`
`
`
`
`
`
`10th IEEE/ A CM Conference on Grid Computing
`
`
`
`
`Large-Scale Distributed Applications and Production Grids,
`
`
`
`(Grid 2009), Banff, Canada, 2009, winner best paper award.
`
`ChoreographyOf Service 35.Adam Barker, Paolo Besanay, David Robertson, and Jon B. Weissman, The Benefits
`
`
`
`
`
`
`
`
`Proceedings of the 2009 Workshop in Challenges of Large Applications in
`
`For Data-Intensive Computing,
`
`Distributed Environments
`
`(CLADE), 2009.
`
`IEEE/ACM
`
`
`
`
`Data-centric Workflows, Orchestrating 36.Adam Barker, Jon B. Weissman and Jano van Hemert,
`
`
`
`
`
`
`CCGrid International Symposium on Cluster Computing and the Grid (CCGrid), Lyon, France, May 2008.
`
`Tradeoffthe Throughput-Fairness 37.Vasumathi Sundaram, Abhishek Chandra and Jon B. Weissman, Exploring
`
`
`
`
`
`
`Proceedings of the A CM International
`
`
`
`
`of Deadline Scheduling in Heterogeneous Computing Environments,
`
`
`
`
`Conference on Measurement and Modeling of Computer Systems
`
`(SIGMETRICS), short paper, Annapolis,
`MD, June 2008.
`
`in OpenAdaptation 38.Krishnavcni Budati, Jinoh Kim, Abhishek Chandra and Jon Weissman, NGS: Service
`
`
`
`
`
`
`
`Proceedings of the IPDPS NSF Next Generation Software Workshop,
`Grid Platforms,
`March 2007.
`
`Lcvent Ertoz, Gyorgy Simon, Sconho39.Jon B. Weissman, Vipin Kumar, Varun Chandola, Eric Eilertson,
`
`
`
`
`
`Middleware for Grid and DistributedKim, and Jinoh Kim, DDDAS/ITR: A Data Mining and Exploration
`
`
`
`
`Workshop on Dynamic Data Driven Application Systems -DDDAS 2007, Beijing, China, May
`Computing,
`2007.
`
`Data DownHeterogeneity for Collective 40 . .Jinoh Kim, Abhishck Chandra, and Jon B. Weissman, Exploiting
`
`
`
`
`
`
`
`
`
`Computing IEEE/ A CM CCGrid International Symposium on Clusi<!r
`
`
`loading in Volunteer-based Networks,
`
`and the Grid (CCGrid), 2007.
`
`41.Jon B. Weissman, Seonho Kim, and Darin England, A Framework for Dynamic Service Adaptation in the
`
`
`
`
`Software Workshop Denver, Proceedings of the IPDPS NSF Next Generation
`
`Gri<l,
`
`Colorado, April 2005.
`
`42 .. Jason D. Sonnek an<l Jon B. Weissman, A Quantitative Comparison of Reputation Systems in the Grid, 6th
`
`
`
`
`
`
`
`IEEE/ACM International Workshop on Grid Computing
`(GRID).
`
`11
`
`EX 1007 Page 11
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`
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`Lifecycle,the Dynamic Grid Service 43.Jon B. Weissman, Seonho Kim, and Darin England, Supporting
`
`
`
`
`
`
`
`IEEE/ACM CCGrid International Symposium on Cluster Computing and the Grid (CCGrid),
`2005.
`
`of Dynamic GridControl Model for the Deployment 44.Darin England and Jon B. Weissman, "A Stochastic
`
`
`
`
`
`
`5th IEEE/ACM International Workshop on Grid Computing
`
`Services",
`(GRID), 2004.
`
`45.Darin England
`
`and Jon B. Weissman, "A Load Sharing Model for the Computational
`
`
`
`Job Scheduling Strategies for Parallel Processing
`
`
`(JSSPP) with Sigmetrics 2004.
`
`Grid," Workshop on
`
`46.Seonho Kim and Jon B. Weissman, "A GA-based approach for scheduling decomposable data grid applica
`
`
`
`
`
`
`
`
`
`International Conference on Parallel Processing
`(ICPP) 2004.
`tions,"
`
`for Grid-enabled Network Services,"47.Byoung-Dai Lee and Jon B. Weissman, "Adaptive Resource Selection
`
`
`
`
`
`
`
`
`
`
`IEEE 2nd International Symposium on Network Computing and Applications (NCA), 2003.
`
`IEEE 3rd
`for Network Services," Resource Scheduling 48.Byoung-Dai Lee and Jon B. Weissman, "Adaptive
`
`
`
`
`
`
`
`
`International Workshop on Grid Computing,
`2002.
`
`
`
`of Networkfor Rapid Deployment Service Toolkit 49.Byoung-Dai Lee and Jon B. Weissman, "Community
`
`
`
`
`
`
`
`IEEE 2002 Workshop on Cluster Computing,
`Services,"
`2002.
`
`on the ComputaCo-Allocation Resource 50.Jon B. Weissman and Pramod Srinivasan, "Ensemble Schedulng:
`
`
`
`
`
`
`
`Grid", IEEE 2nd International Workshop on Grid Computing
`
`
`tional
`(GRID), November 2001.
`
`for Dynamic Replication,"Service Grid Architecture 51.Byoung-Dai Lee and Jon B. Weissman, "An Adaptive
`
`
`
`
`
`
`IEEE 2nd International Workshop on Grid Computing
`
`
`(GRID), November 2001.
`
`Services inScalable Heterogenous Grid: Supporting 52.Jon B. Weissman and Byoung-Dai Lee, "The Service
`
`
`
`
`
`
`
`
`The IEEE 2001 Symposium on Applications and the Internet
`
`Wide-Area Networks,"
`
`(SAINT), January 2001.
`
`Het
`in Heterogeneous Wide-area Networks," 53.Jon B. Weissman, "Scheduling Multi-Component Applications
`
`
`
`
`
`erogeneous Computing Workshop,
`
`
`
`
`
`International Parallel and Distributed Processing Symposium, May 2000.
`
`IEEE Workshop on Fault-Tolerant
`
`Parallel Computing," 54.Jon B. Weissman, "Fault Tolerant Wide-Arca
`
`
`
`
`
`Parallel and Distributed Systems,
`
`
`
`
`International Parallel and Distributed Processing Symposium, May 2000.
`
`
`File Objects," 55.Mike Gingras and Jon B. Weissman, "Smart Multimedia
`
`
`cations
`(WIA), July 1999.
`
`
`
`IEEE Workshop on Internet Appli
`
`56.Jon B. Weissman, "Smart File Objects: A Remote File Access Paradigm,"
`
`
`
`
`Parallel and Distributed Systems
`
`(IOPADS), May 1999.
`
`Sixth ACM Workshop on I/O in
`
`
`Heterogeneous Computing
`57.Jon B. Weissman, "The Interference Paradigm for Network Job Scheduling,"
`
`
`Workshop,
`
`
`
`
`
`Tenth International Parallel and Distributed Processing Symposium, April 1996.
`
`Object-Oriented Computation58.Jon B. Weissman, Andrew S. Grimshaw, and Robert R. Ferraro, "Parallel
`
`
`
`
`
`Object-Oriented Numerics, 1993.
`
`
`
`Applied to a Finite Element Problem,"
`
`
`
`
`
`in Parallel Simulation"The Role of Event Granularity 59.Lisa Sokol, Jon B. Weissman, and Paula Mutchler,
`
`
`
`
`Proceedings of the Parallel and Distributed Simulation Conference
`
`(PADS), 1992.
`Design,"
`
`Proceedings
`Protocol," Level Simulation 60.Richard Weatherly, David Seidel, and Jon B. Weissman, "Aggregate
`
`
`
`
`
`
`of the 1991 Summer Computer Simulation Conference,
`J