Photo of Daniel Kifer

Daniel Kifer

Associate Professor

Affiliation(s):

  • School of Electrical Engineering and Computer Science
  • Computer Science and Engineering

W333 Westgate Building

duk17@psu.edu

814-863-1186

Research Areas:

Interest Areas:

 
 

 

Education

  • BA, Computer Science & Mathematics, New York University, 2000
  • MS, Computer Science, Cornell University, 2004
  • Ph D, Computer Science, Cornell University, 2006

Publications

Books

  • Bee-Chung Chen, Daniel Kifer, Kristen LeFevre and Ashwin Machanavajjhala, 2009, Privacy-Preserving Data Publishing, NOW Publishers, pp. 1–167
  • , 2009, Encyclopedia of Database Systems, Springer US

Book, Chapters

  • Daniel Kifer, 2009, Change Detection on Streams, pp. 317–321
  • Daniel Kifer, Johannes Gehrke, Cristian Bucila and Walker M. White, 2005, How to Quickly Find a Witness, Springer-Verlag, pp. 216–242

Journal Articles

  • Kuai Fang, Chaopeng Shen, Daniel Kifer and Xiao Yang, 2017, "Prolongation of SMAP to Spatiotemporally Seamless Coverage of Continental U.S. Using a Deep Learning Neural Network", Geophysical Research Letters
  • Alexander G. Ororbia II, Daniel Kifer and C. Lee Giles, 2017, "Unifying Adversarial Training Algorithms with Data Gradient Regularization", Neural Computation
  • Hongjian Wang, Daniel Kifer, Corina Graif and Zhenhui Li, 2017, "Non-Stationary Model for Crime Rate Inference Using Modern Urban Data", IEEE Transactions on Big Data
  • A. G. Ororbia II, C. L. Giles and Daniel Kifer, 2016, "Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization", CoRR
  • Alexander G. Ororbia, II, Clyde L Giles and Daniel Kifer, 2016, "Unifying Adversarial Training Algorithms with Flexible Deep Data Gradient Regularization", Neural Computation, abs/1601.07213
  • Bing-Rong Lin and Daniel Kifer, 2015, "Information Measures in Statistical Privacy and Data Processing Applications", ACM Transactions on Knowledge Discovery from Data, 9, (4), pp. 28
  • Ashwin Machanavajjhala and Daniel Kifer, 2015, "Designing statistical privacy for your data", Communications of the ACM, 58, (3), pp. 58–67
  • Yue Wang, Jaewoo Lee and Daniel Kifer, 2015, "Differentially Private Hypothesis Testing, Revisited", CoRR, abs/1511.03376
  • Bing-Rong Lin and Daniel Kifer, 2014, "On Arbitrage-free Pricing for General Data Queries", PVLDB, 7, (9), pp. 757–768
  • Daniel Kifer and Ashwin Machanavajjhala, 2014, "Pufferfish: A framework for mathematical privacy definitions", ACM Trans. Database Syst., 39, (1), pp. 3
  • Bing-Ron Lin and Daniel Kifer, 2014, "Towards a systematic analysis of privacy definitions", Journal of Privacy and Confidentiality, 5, (2), pp. 57-109
  • Bing-Rong Lin and Daniel Kifer, 2012, "A Framework for Extracting Semantic Guarantees from Privacy", CoRR, abs/1208.5443
  • Ashwin Machanavajjhala, Daniel Kifer, Johannes Gehrke and Muthuramakrishnan Venkitasubramaniam, 2007, "L-diversity: Privacy beyond k-anonymity", TKDD, 1, (1)
  • David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke and Joseph Y. Halpern, 2007, "Worst-Case Background Knowledge for Privacy-Preserving Data Publishing", CoRR, abs/0705.2787
  • Manuel Calimlim, Jim Cordes, Alan J. Demers, Julia Deneva, Johannes Gehrke, Daniel Kifer, Mirek Riedewald and Jayavel Shanmugasundaram, 2004, "A Vision for PetaByte Data Management and Analyis Services for theArecibo Telescope", IEEE Data Engineering Bulletin, 27, (4), pp. 12–20
  • Manuel Calimlim, Jim Cordes, Alan J. Demers, Julia Deneva, Johannes Gehrke, Daniel Kifer, Mirek Riedewald and Jayavel Shanmugasundaram, 2004, "A Vision for PetaByte Data Management and Analyis Services for the Arecibo Telescope", IEEE Data Eng. Bull., 27, (4), pp. 12–20
  • Cristian Bucila, Johannes Gehrke, Daniel Kifer and Walker M. White, 2003, "DualMiner: A Dual-Pruning Algorithm for Itemsets with Constraints", Data Mining and Knowledge Discovery, 7, (3), pp. 241–272

Conference Proceedings

  • Omar Montasser and Daniel Kifer, 2017, "Predicting Demographics of High-Resolution Geographies with Geotagged Tweets"
  • Ryan Rogers and Daniel Kifer, 2017, "A New Class of Private Chi-Square Hypothesis Tests"
  • H. Dafang, X. Yang, Z. Zhou, C. Liang, Alexander G. Ororbia II, Daniel Kifer, and C. Lee Giles, 2017, "Multi-scale FCN with Cascaded Instance Aware Segmentation for Arbitrary Oriented Word Spotting in the Wild"
  • Xiao Yang, Ersin Yumer, Paul Asente, Mike Kraley, Daniel Kifer and C. Lee Giles, 2017, "Learning to Extract Semantic Structure from Documents Using Multimodal Fully Convolutional Neural Networks"
  • Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer and C. Lee Giles, 2017, "Improving Offline Handwritten Chinese Character Recognition by Iterative Refinement. ICDAR"
  • Dafang He, Scott Cohen, Brian L. Price, Daniel Kifer and C. Lee Giles, 2017, "Multi-Scale MultiTask FCN for Semantic Page Segmentation and Table Detection"
  • Xiao Yang, Dafang He, Zihan Zhou, Daniel Kifer and C. Lee Giles, 2017, "Learning to Read Irregular Text with Attention Mechanisms"
  • Xiao Yang, Dafang He, Wenyi Huang, Alexander Ororbia, Zihan Zhou, Daniel Kifer and C. Lee Giles, 2017, "Smart Library: Identifying Books on Library Shelves Using Supervised Deep Learning for Scene Text Reading"
  • Danfeng Zhang and Daniel Kifer, 2017, "LightDP: towards automating differential privacy proofs"
  • H. Wang, Y. H. Kuo, Daniel Kifer and Z. Li, 2016, "A simple baseline for travel time estimation using large-scale trip data", Association for Computing Machinery
  • W. Huang, D. He, X. Yang, Z. Zhou, Daniel Kifer and C. L. Giles, 2016, "Detecting arbitrary oriented text in the wild with a visual attention model", Association for Computing Machinery
  • H. Wang, Daniel Kifer, C. Graif and Z. Li, 2016, "Crime rate inference with big data", Association for Computing Machinery, 13
  • Jaewoo Lee, Yue Wang and Daniel Kifer, 2015, "Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints", pp. 635–644
  • Daniel Kifer, 2015, "On Estimating the Swapping Rate for Categorical Data", pp. 557–566
  • Daniel Kifer, 2015, "Privacy and the Price of Data", pp. 16
  • Bing-Rong Lin and Daniel Kifer, 2013, "Geometry of privacy and utility", pp. 281–284
  • Sirinda Palahan, Domagoj Babic, Swarat Chaudhuri and Daniel Kifer, 2013, "Extraction of statistically significant malware behaviors", pp. 69–78
  • Bing-Rong Lin and Daniel Kifer, 2013, "Information preservation in statistical privacy and bayesian estimationof unattributed histograms", pp. 677–688
  • Bing-Rong Lin and Daniel Kifer, 2013, "Information preservation in statistical privacy and bayesian estimation of unattributed histograms", pp. 677–688
  • Daniel Kifer and B.-R. Lin, 2012, "Analyzing Privacy and Utility Using Axioms", Proceedings of the Forty-Sixth Asilomar Conference on Signals, Systems and Computers
  • Daniel Kifer, Adam D Smith and Abhradeep Thakurta, 2012, "Private Convex Optimization for Empirical Risk Minimization with Applicationsto High-dimensional Regression", pp. 25.1–25.40
  • Daniel Kifer and Ashwin Machanavajjhala, 2012, "A rigorous and customizable framework for privacy", pp. 77–88
  • , 2012, "COLT 2012 - The 25th Annual Conference on Learning Theory, June 25-27, 2012, Edinburgh, Scotland", JMLR.org, 23
  • , 2012, "Conference Record of the Forty Sixth Asilomar Conference on Signals, Systems and Computers, ACSCC 2012, Pacific Grove, CA, USA, November 4-7, 2012", IEEE
  • , 2012, "Proceedings of the 31st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS 2012, Scottsdale, AZ, USA, May 20-24, 2012", ACM
  • Bing-Rong Lin and Daniel Kifer, 2012, "Reasoning about privacy using axioms", pp. 975–979
  • Daniel Kifer, Adam D Smith and Abhradeep Thakurta, 2012, "Private Convex Optimization for Empirical Risk Minimization with Applications to High-dimensional Regression", pp. 25.1–25.40
  • Daniel Kifer and Ashwin Machanavajjhala, 2011, "No free lunch in data privacy", pp. 193–204
  • Qi He, Daniel Kifer, Jian Pei, Prasenjit Mitra and Clyde L Giles, 2011, "Citation recommendation without author supervision", pp. 755–764
  • Bi Chen, Leilei Zhu, Daniel Kifer and Dongwon Lee, 2010, "What Is an Opinion About? Exploring Political Standpoints Using OpinionScoring Model"
  • Daniel Kifer and Bing-Rong Lin, 2010, "Towards an axiomatization of statistical privacy and utility", pp. 147–158
  • Qi He, Jian Pei, Daniel Kifer, Prasenjit Mitra and Clyde L Giles, 2010, "Context-aware citation recommendation", pp. 421–430
  • Johannes Gehrke, Daniel Kifer and Ashwin Machanavajjhala, 2010, "Privacy in data publishing", pp. 1213
  • Bi Chen, Leilei Zhu, Daniel Kifer and Dongwon Lee, 2010, "What Is an Opinion About? Exploring Political Standpoints Using Opinion Scoring Model"
  • Daniel Kifer, 2009, "Attacks on privacy and deFinetti’s theorem", pp. 127–138
  • , 2009, "Proceedings of the ACM SIGMOD International Conference on Management of Data, SIGMOD 2009, Providence, Rhode Island, USA, June 29 - July 2, 2009", ACM
  • Parag Agrawal, Daniel Kifer and Christopher Olston, 2008, "Scheduling shared scans of large data files", 1, (1), pp. 958–969
  • Ashwin Machanavajjhala, Daniel Kifer, John M. Abowd, Johannes Gehrke and Lars Vilhuber, 2008, "Privacy: Theory meets Practice on the Map", pp. 277–286
  • , 2008, "Proceedings of the 24th International Conference on Data Engineering, ICDE 2008, April 7-12, 2008, Cancún, México", IEEE
  • David J. Martin, Daniel Kifer, Ashwin Machanavajjhala, Johannes Gehrke and Joseph Y. Halpern, 2007, "Worst-Case Background Knowledge for Privacy-Preserving Data Publishing", pp. 126–135
  • , 2007, "Proceedings of the 23rd International Conference on Data Engineering, ICDE 2007, The Marmara Hotel, Istanbul, Turkey, April 15-20, 2007", IEEE
  • Daniel Kifer and Johannes Gehrke, 2006, "Injecting utility into anonymized datasets", pp. 217–228
  • Ashwin Machanavajjhala, Johannes Gehrke, Daniel Kifer and Muthuramakrishnan Venkitasubramaniam, 2006, "l-Diversity: Privacy Beyond k-Anonymity", pp. 24
  • , 2006, "Proceedings of the 22nd International Conference on Data Engineering, ICDE 2006, 3-8 April 2006, Atlanta, GA, USA", IEEE Computer Society
  • Daniel Kifer, Shai Ben-David and Johannes Gehrke, 2004, "Detecting Change in Data Streams", pp. 180–191
  • Daniel Kifer, Johannes Gehrke, Cristian Bucila and Walker M. White, 2003, "How to quickly find a witness", pp. 272–283
  • Cristian Bucila, Johannes Gehrke, Daniel Kifer and Walker M. White, 2002, "DualMiner: a dual-pruning algorithm for itemsets with constraints", pp. 42–51

Manuscripts

  • Daniel Kifer and B.-R. Lin, , "An Axiomatic View of Statistical Privacy and Utility", Journal of Privacy and Confidentiality

Research Projects

Honors and Awards

Service

Service to Penn State:

Service to External Organizations:

 


 

About

The School of Electrical Engineering and Computer Science was created in the spring of 2015 to allow greater access to courses offered by both departments for undergraduate and graduate students in exciting collaborative research in fields.

We offer B.S. degrees in electrical engineering, computer science, computer engineering and data science and graduate degrees (master's degrees and Ph.D.'s) in electrical engineering and computer science and engineering. EECS focuses on the convergence of technologies and disciplines to meet today’s industrial demands.

School of Electrical Engineering and Computer Science

The Pennsylvania State University

207 Electrical Engineering West

University Park, PA 16802

814-863-6740

Department of Computer Science and Engineering

814-865-9505

Department of Electrical Engineering

814-865-7667