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- IEEE AIVR 18
- Dec December 10, 2018
Jacob Biehl, Ph.D.
Senior Research Scientist

Jacob’s work at FXPAL centers on the design and development of collaborative systems and supporting technologies. At FXPAL, he has worked on Loco, MyUnity, and Jarvis. He holds a B.S. in Statistics and Computer Science from the University of Illinois at Urbana-Champaign, where he also earned a M.S. and Ph.D. in Computer Science.
Co-Authors
Publications by Jacob Biehl
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- International Conference on Indoor Positioning and Indoor Navigation
- Sep September 24, 2018
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- 9th International Conference on Indoor Positioning and Indoor Navigation
- Sep September 24, 2018
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- The 23rd ACM Symposium on Access Control Models & Technologies (SACMAT)
- Jun June 13, 2018
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- International Conference on Robotics and Automation
- May May 21, 2018
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- Fuji Xerox Technical Report
- Oct October 1, 2017
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- CHI 2016
- May May 7, 2016
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- Personal and Ubiquitous Computing (Springer)
- Feb February 19, 2016
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- ACM Multimedia Conference 2015
- Oct October 26, 2015
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- UbiComp 2015
- Sep September 7, 2015
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- Presented in "Everyday Telepresence" workshop at CHI 2015
- Apr April 18, 2015
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- CSCW 2015
- Mar March 14, 2015
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- Ubicomp 2014
- Sep September 9, 2014
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- Future Generation Computer Systems
- May May 28, 2013
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CloseCollaboration technologies must support information sharing between collaborators, but must also take care not to share too much information or share information too widely. Systems that share information without requiring an explicit action by a user to initiate the sharing must be particularly cautious in this respect. Presence systems are an emerging class of applications that support collaboration. Through the use of pervasive sensors, these systems estimate user location, activities, and available communication channels. Because such presence data are sensitive, to achieve wide-spread adoption, sharing models must reflect the privacy and sharing preferences of their users. This paper looks at the role that privacy-preserving aggregation can play in addressing certain user sharing and privacy concerns with respect to presence data. We define conditions to achieve CollaPSE (Collaboration Presence Sharing Encryption) security, in which (i) an individual has full access to her own data, (ii) a third party performs computation on the data without learning anything about the data values, and (iii) people with special privileges called “analysts” can learn statistical information about groups of individuals, but nothing about the individual values contributing to the statistic other than what can be deduced from the statistic. More specifically, analysts can decrypt aggregates without being able to decrypt the individual values contributing to the aggregate. Based in part on studies we carried out that illustrate the need for the conditions encapsulated by CollaPSE security, we designed and implemented a family of CollaPSE protocols. We analyze their security, discuss efficiency tradeoffs, describe extensions, and review more recent privacy-preserving aggregation work.
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- IPIN2012
- Nov November 13, 2012
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- CHI 2012
- May May 7, 2012
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- ACM MMSYS 2012
- Feb February 22, 2012
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- Fuji Xerox Technical Report No.21 2012
- Feb February 2, 2012
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- ACM Multimedia Industrial Exhibits
- Nov November 28, 2011
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- MobileHCI
- Aug August 30, 2011
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- SECOTS 2011
- May May 23, 2011
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- NPUC2010
- Oct October 22, 2010
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- In Proc. CHI 2010
- Apr April 10, 2010
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- In Proc. CHI 2010
- Apr April 10, 2010
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- Symposium on Eye Tracking Research and Applications 2010
- Mar March 22, 2010