Michael Hay - Cornell University

Michael Hay
Contact
Education
Research Interests
4130 Upson Hall mhay@cs.cornell.edu
Cornell University (413) 835-5618
Ithaca, NY 14853
University of Massachusetts Amherst
Ph.D., Computer Science, 2010
Dissertation: Enabling Accurate Analysis of Private Network Data
Committee: Gerome Miklau, David Jensen, Don Towsley, Andrew Papachristos
University of Massachusetts Amherst
M.S., Computer Science, 2007
GPA: 4.0 / 4.0
Dartmouth College
A.B. cum laude, Computer Science, 1998
GPA: 3.6 / 4.0
Data management and data mining, with a focus on privacy. Other interests: machine learning,
social network analysis, security.
Research Experience
Computing Innovation Fellow, Cornell University 2010 - Present
Mentor: Johannes Gehrke.
Researching privacy-preserving data publishing. Developed a novel technique for generating
a synopsis of a sensitive dataset that is both accurate and safe for public release. Currently
investigating alternative definitions of privacy that are robust but not as conservative as
differential privacy, thereby offering the promise of greater utility and broader application.
Research Assistant, University of Massachusetts Amherst 2002 - 2010
Co-advisors: David Jensen and Gerome Miklau.
Thesis work: Investigated privacy implications of publishing anonymized network data
and developed techniques for safe publication. Other work: Designed machine learning
algorithms for various tasks—extraction, deduplication, classification—in network data.
Teaching Experience
Instructor, Cornell University Spring 2012
CS 1330 Privacy in Bits: How Digital Technology is Reshaping Privacy
A new course that I proposed and designed. Offered as a first-year writing seminar coordinated
by Cornell’s Institute for Writing in the Disciplines. Through student writing and
research, course investigates digital technologies and their apparent conflict with privacy.
Instructor, Cornell University Summer 2011
CS 2110 Object-Oriented Programming and Data Structures
Responsible for all aspects of this “CS2” course of 43 students. Supervised two teaching
assistants and three undergraduate graders. Used a combination of lecture and in-class
exercises—both brief “think-pair-share” activities and worksheet-based group exercises.
Instructor, University of Massachusetts Amherst Summer 2006
CS 121 Introduction to Problem Solving with Computers
Responsible for all aspects of this “CS1” course. Used a hybrid of lecture and laboratory.

Teaching Assistant, University of Massachusetts Amherst Spring 2006
CS 121 Introduction to Problem Solving with Computers
Responsible for teaching weekly section (roughly 40 students) and holding office hours in
computer laboratory. Assistant to Professor Robert Moll.
Guest Lecturer, Cornell University
CIS 3000 Introduction to Computer Game Design, Fall 2010, Fall 2011
Guest Lecturer, University of Massachusetts Amherst
CS 745 Advanced Database Systems, Fall 2008
CS 121 Introduction to Problem Solving with Computers, Fall 2006
CS 383 Artificial Intelligence, Fall 2006
CS 591Y Knowledge Discovery and Data Mining, Spring 2005
Ski Instructor, Various resorts 1992-1996
Taught all ages and skill levels.
Teaching Competencies
Any lower-level courses (CS0, CS1, CS2)
Upper-level courses: algorithms, artificial intelligence, databases
Advanced topics: machine learning, data mining, social network analysis, privacy
Math courses: discrete mathematics, probability, statistics
Writing seminars
Professional Experience
Summer Intern, Adverplex, Cambridge, MA Summer 2008
Applied machine learning algorithms to identify relevant keywords for search engine marketing
campaigns.
Program Manager, Second Nature, Boston, MA 2000 - 2002
Created online portal to connect academic institutions with resources on environmental
sustainability. Managed IT infrastructure.
Volunteer Intern, The Nature Conservancy, Boulder, CO 1999 - 2000
Volunteered part-time to research tracts of land for potential acquisition.
Software Engineer, Kenan Systems, Denver, CO 1998 - 2000
Developed software for customer care and data migration. Consulted clients on software
configuration and live production.
Trip Leader, Putney Student Travel, Arusha, Tanzania Summer 1998
Led a five week community service trip for high school students.
Awards Postdoctoral Fellowship, NSF/CRA Computing Innovation Fellow, 2010-2012
Dissertation Award, ACM Special Interest Group on Knowledge Discovery & Data Mining, 2011
Dissertation Award, U. of Massachusetts Amherst, CS Department, sponsored by Yahoo, 2011
Best Student Paper Award, IEEE International Conference on Data Mining, 2009
KDD Cup Winner, ACM International Conference on Knowledge Discovery & Data Mining, 2003
Citation for Meritorious Scholarship, Dartmouth College, 1996
Michael Hay Curriculum Vitae (2 of 4)

Publications
Journal Articles
Michael Hay, Gerome Miklau, David Jensen, Don Towsley, and Chao Li. Resisting structural
re-identification in anonymized social networks. International Journal on Very Large Data Bases
(VLDB Journal), 2010.
Conference Papers
Xiaokui Xiao, Gabriel Bender, Michael Hay, and Johannes Gehrke. iReduct: Differential privacy
with reduced relative errors. In ACM International Conference on the Management of Data
(SIGMOD), 2011.
Michael Hay, Vibhor Rastogi, Gerome Miklau, and Dan Suciu. Boosting the accuracy of differentially
private histograms through consistency. In Proceedings of the VLDB Endowment
(PVLDB), 2010.
Chao Li, Michael Hay, Vibhor Rastogi, Gerome Miklau, and Andrew McGregor. Optimizing
linear counting queries under differential privacy. In ACM Symposium on Principles of Database
Systems (PODS), 2010.
Michael Hay, Chao Li, Gerome Miklau, and David Jensen. Accurate estimation of the degree
distribution of private networks. In IEEE International Conference on Data Mining (ICDM),
2009.
Vibhor Rastogi, Michael Hay, Gerome Miklau, and Dan Suciu. Relationship privacy: output
perturbation for queries with joins. In ACM Symposium on Principles of Database Systems
(PODS), 2009.
Michael Hay, Gerome Miklau, David Jensen, Donald F. Towsley, and Philipp Weis. Resisting
structural re-identification in anonymized social networks. In Proceedings of the VLDB Endowment
(PVLDB), 2008.
Ben Wellner, Andrew McCallum, Fuchun Peng, and Michael Hay. An integrated, conditional
model of information extraction and coreference for citation matching. In Conference on Uncertainty
in Artificial Intelligence (UAI), 2004.
Jennifer Neville, David Jensen, Lisa Friedland, and Michael Hay. Learning relational probability
trees. In ACM International Conference on Knowledge Discovery and Data Mining (KDD),
2003.
David Jensen, Jennifer Neville, and Michael Hay. Avoiding bias when aggregating relational
data with degree disparity. In International Conference on Machine Learning (ICML), 2003.
Other Scholarship
Michael Hay, Kun Liu, Gerome Miklau, Jian Pei, and Evimaria Terzi. Privacy-aware Data Management
in Information Networks (Tutorial). In ACM International Conference on the Management
of Data (SIGMOD), 2011.
Michael Hay, Gerome Miklau, and David Jensen. Privacy-Aware Knowledge Discovery: Novel
Applications and New Techniques, chapter Enabling accurate analysis of private network data.
CRC Press, 2010.
Amy McGovern, Lisa Friedland, Michael Hay, Brian Gallagher, Andy Fast, Jen Neville, and
David Jensen. Exploiting relational structure to understand publication patterns in high-energy
physics. ACM SIGKDD Explorations, 2003.
Service Program Committees
World Wide Web Conference (WWW), 2012
Michael Hay Curriculum Vitae (3 of 4)

ACM International Conference on the Management of Data (SIGMOD), 2012
IEEE International Conference on Data Engineering (ICDE), 2011
International Conference on Machine Learning (ICML), 2011
Privacy Aspects of Data Mining Workshop at the IEEE International Conference on Data
Mining (ICDM), 2011
Journal reviewing
ACM Transactions on Database Systems (TODS), 2010
Data Mining and Knowledge Discovery (DMKD), 2010
Transactions on Data Privacy, 2010
IEEE Transactions on Knowledge and Data Engineering (TKDE), 2008
Proposal reviewing
National Science Foundation, Information & Intelligent Systems Division, 2011
Professional Memberships
Association for Computing Machinery (ACM)
ACM Special Interest Groups:
Computer Science Education (SIGCSE)
Knowledge Discovery and Data Mining (SIGKDD)
Management of Data (SIGMOD)
Michael Hay Curriculum Vitae (4 of 4)