Nina Mishra's Home Page

Email

nmishra@gmail.com, nmishra@cs.stanford.edu

Synopsis

My research interests are in data science, data mining, web search, machine learning and privacy. I have many years of experience leading projects in industry at Amazon, Microsoft Research and HP Labs, as well as academia as Associate Professor at the University of Virginia and Acting Faculty at Stanford University.

The projects that I pursue encompass the design and evaluation of new data mining algorithms on real, colossal-sized datasets. I authored ~50 publications in top venues including: Web Search: WWW, WSDM, SIGIR; Machine Learning: ICML, NIPS, AAAI, COLT; Databases: VLDB, PODS; Cryptography: CRYPTO, EUROCRYPT; Theory: FOCS and SODA. My research publications received external recognition: best paper award nomination, algorithm in Wikipedia and taught in graduate courses around the world. Also, my research has product implications at Microsoft, specifically in the Bing search engine, and was featured in external press coverage including New Scientist, ACM TechNews, IEEE Computing Now, Search Engine Land and Microsoft Research. I've been granted 14 patent applications with a dozen more still in the application stage. I've had the distinct privilege of helping others advance in their careers, including 15 summer interns and many full-time researchers.

My service to the community includes: serving on journal editorial boards Machine Learning, Journal of Privacy and Confidentiality, IEEE Transactions on Knowledge and Data Engineering and IEEE Intelligent Systems; chairing the premier machine learning conference ICML in 2003, as well as numerous program committees for web search, data mining and machine learning conferences. I was awarded an NSF Grant as a Principal Investigator and served on 8 PhD dissertation committees. I taught several courses at Stanford University and the University of Virginia.

Biography

o   Principal Scientist, Amazon, 2015-present.

o   Visiting Scholar, Stanford University, 2014-present.

o   Senior Researcher, Microsoft Research Silicon Valley. 2007-2014.

o   Associate Professor, Computer Science Department, University of Virginia, 2005-2008.

o   Acting Faculty, Computer Science Department, Stanford University, 2002-2005.

o   Senior Research Scientist, Hewlett-Packard Labs, 1997-2005.

o   PhD Computer Science, University of Illinois at Urbana-Champaign, 1997 

Publications

o   Sudipto Guha, Nina Mishra, Gourav Roy, Okke Schrijvers. Robust Random Cut Forest Based Anomaly Detection on Streams. In International Conference on Machine Learning (ICML), 2016

o   Katherine Ellis, Moises Goldszmidt, Gert Lanckriet, Nina Mishra and Omer Reingold. Equality and Social Mobility in Twitter Discussion Groups, in International Conference on Web Search and Data Mining (WSDM), ACM, 2016

o   James Cook, Abhimanyu Das, Krishnaram Kenthapadi, and Nina Mishra, Ranking Twitter Discussion Groups, in ACM Conference on Online Social Networks (COSN), 2014

o   Nina Mishra, Ryen White, Samuel Ieong, and Eric Horvitz, Time-Critical Search, in SIGIR (Information retrieval), ACM, 2014

o   External Coverage:

o   How Search can Help in a Medical Crisis, Microsoft Research

o   Isabelle Stanton, Samuel Ieong, and Nina Mishra, Circumlocution in Diagnostic Medical Queries, in SIGIR (Information Retrieval), ACM, 2014

o   Ideas from this paper formed the basis for a CLEF eHealth challenge task.

o   Krishnaram Kenthapadi, Nina Mishra, and Kobbi Nissim, Denials Leak Information: Simulatable Auditing, in Journal of Computer and System Sciences, vol. 79 (8), pp. 1322-1340, Elsevier, December 2013

o   Nina Mishra, Daniel Romero, and Panayiotis Tsaparas, Estimating the Relative Utility of Networks for Predicting User Activities, in CIKM, ACM International Conference on Information and Knowledge Management (CIKM), 2013

o   Krishnaram Kenthapadi, Aleksandra Korolova, Ilya Mironov, and Nina Mishra, Privacy via the Johnson-Lindenstrauss Transform, in Journal of Privacy and Confidentiality, vol. 5 (1), July 2013

o   James Cook, Krishnaram Kenthapadi, and Nina Mishra, Group Chats on Twitter, in International World Wide Web Conference (WWW), ACM, 2013

o   Samuel Ieong, Nina Mishra, and Or Sheffet, Predicting Preference Flips in Commerce Search, in International Conference on Machine Learning (ICML), 2012

o   Samuel Ieong, Nina Mishra, Eldar Sadikov, and Li Zhang, Domain bias in web search, in International Conference on Web Search and Data Mining (WSDM), ACM, 2012

o   External Coverage:

o   Turn Domain Bias In Search Results To Your Advantage, Search Engine Land

o   Domain Name Matters: Searchers Pick Brand Over Quality, Study Finds, Search Engine Land

o   Srikanth Jagabathula, Nina Mishra, and Sreenivas Gollapudi, Shopping for Products You Don't Know You Need, in WSDM (Web Search and Data Mining), 2011

o   Shubha Nabar and Nina Mishra, Releasing Private Contingency Tables, in Journal of Privacy and Confidentiality, 2010

o   Gagan Aggarwal, Nina Mishra, and Benny Pinkas, Secure Computation of the Median (and Other Elements of Specified Ranks), in Journal of Cryptology, 2010

o   Umar Syed, Alex Slivkins, and Nina Mishra, Adapting to the Shifting Intent of Search Queries, in NIPS (Neural Information Processing Systems Conference), 2009

o   Aleksandra Korolova, Krishnaram Kenthapadi, Nina Mishra, and Alex Ntoulas, Releasing Search Queries and Clicks Privately, in International World Wide Web Conference (WWW), ACM, 2009.

o   Nominated for a Best Paper Award

o   External Coverage:

o   Noise could Mask Web Searchers' IDs, New Scientist, ACM TechNews, TechFlash

o   Making the Web More User-Friendly, Microsoft Research

o   Rakesh Agrawal, Alan Halverson, Krishnaram Kenthapadi, Nina Mishra, and Panayiotis Tsaparas, Generating Labels from Clicks, in International Conference on Web Search and Data Mining (WSDM), ACM, 2009

o   Nina Mishra, Robert Schreiber, Isabelle Stanton, and Robert E. Tarjan, Finding Strongly-Knit Clusters in Social Networks, in Internet Mathematics, 2009.

o   Invited to special issue of WAW'07.

o   Westley Weimer and Nina Mishra, Privately Finding Specifications, in IEEE Trans. Software Eng, vol. 34, no. 1, pp. 21-32, 2008

o   Shubha Nabar, Krishnaram Kenthapadi, Nina Mishra, and Rajeev Motwani, A Survey of Query Auditing Techniques for Data Privacy, in Privacy-Preserving Data Mining: Models and Algorithms, Kluwer Academic Publishers, 2008

o   Nina Mishra, Robert Schreiber, Isabelle Stanton, and Robert E. Tarjan, Clustering Social Networks, in WAW, 2007

o   Kamalika Chaudhuri and Nina Mishra, When Random Sampling Preserves Privacy, in CRYPTO, 2006

o   Nina Mishra and Mark Sandler, Privacy via pseudorandom sketches, in Proceedings of the Twenty-Fifth ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, Chicago, IL, USA June 26-28, 2006, 2006

o   Nina Mishra, Robert Schreiber, and Robert E. Tarjan, Finding Closely-Related Groups of Objects in Very Large Datasets, in Hewlett-Packard Technical Conference (HP TechCon), 2006

o   Shubha U. Nabar, Bhaskara Marthi, Krishnaram Kenthapadi, Nina Mishra, and Rajeev Motwani, Towards Robustness in Query Auditing, in VLDB, Very Large Data Bases Endowment Inc., 2006

o   Nina Mishra, Rajeev Motwani, and Sergei Vassilvitskii, Sublinear Projective Clustering with Outliers, in 15th Annual Fall Workshop on Computational Geometry and Visualization, 2005

o   Krishnaram Kenthapadi, Nina Mishra, and Kobbi Nissim, Simulatable Auditing, in PODS, Association for Computing Machinery, Inc., 2005

o   Gagan Aggarwal, Nina Mishra, and Benny Pinkas, Secure Computation of the k th-Ranked Element, in EUROCRYPT, 2004

o   Nina Mishra, Dana Ron, and Ram Swaminathan, A New Conceptual Clustering Framework, in Machine Learning, vol. 56, no. 1-3, pp. 115-151, 2004

o   Haym Hirsh, Nina Mishra, and Leonard Pitt, Version Spaces and the Consistency Problem, in Artificial Intelligence, vol. 156, no. 2, pp. 115-138, 2004

o   Gagan Aggarwal, Mayank Bawa, Prasanna Ganesan, Hector Garcia-Molina, Krishnaram Kenthapadi, Nina Mishra, Rajeev Motwani, Utkarsh Srivastava, Dilys Thomas, Jennifer Widom, and Ying Xu, Vision Paper: Enabling Privacy for the Paranoids, in VLDB, Very Large Data Bases Endowment Inc., 2004

o   Nina Mishra and Rajeev Motwani, Introduction: Special Issue on Theoretical Advances in Data Clustering, in Machine Learning, vol. 56, no. 1-3, pp. 5-7, 2004

o   Gagan Aggarwal, Mayur Datar, Nina Mishra, and Rajeev Motwani, On Identifying Stable Ways to Configure Systems, in ICAC, 2004

o   Nina Mishra, Dana Ron, and Ram Swaminathan, On Finding Large Conjunctive Clusters, in COLT, Springer, 2003

o   Sudipto Guha, Adam Meyerson, Nina Mishra, Rajeev Motwani, Liadan O'Callaghan. Clustering Data Streams: Theory and Practice. IEEE TKDE, 2003.

o   Nina Mishra, Dana Ron, Ram Swaminathan, Large Clusters of Web Pages, in WAW, 2002

o   Liadan O'Callaghan, Nina Mishra, Adam Meyerson, Sudipto Guha, Nina Mishra. Streaming-Data Algorithms for High-Quality Clustering. ICDE, 2002.

o   Nina Mishra, Daniel Oblinger, and Leonard Pitt, Sublinear time approximate clustering, in SODA, 2001

o   Sudipto Guha, Nina Mishra, Rajeev Motwani, and Liadan O'Callaghan, Clustering Data Streams, in FOCS, 2000

o   Data Stream Clustering in Wikipedia

o   Carlos Domingo, Nina Mishra, and Leonard Pitt, Efficient Read-Restricted Monotone CNF/DNF Dualization by Learning with Membership Queries, in Machine Learning, vol. 37, pp. 89, 1999

o   Originally invited as one of the best papers from COLT'97.

o   Haym Hirsh, Nina Mishra, and Leonard Pitt, Version Spaces Without Boundary Sets, in Proceedings of the 14th National Conference on Artificial Intelligence and 9th Innovative Applications of Artificial Intelligence Conference (AAAI-97/IAAI-97), 1997

o   Nina Mishra, Learning from a monotonous, ignorant teacher, no. 2023, 1997

o   Nina Mishra and Leonard Pitt, Generating all Maximal Independent Sets of Bounded-degree Hypergraphs, in Proceedings of the Tenth Annual Conference on Computational Learning Theory, 1997

o   Michael Frazier, Sally Goldman, Nina Mishra, and Leonard Pitt, Learning from a consistently ignorant teacher, in J. of Comput. Syst. Sci., vol. 52, no. 3, pp. 471-492, 1996

o   Invited as one of the best papers from COLT'94.

Professional Activities

Editorial Boards

o   Machine Learning journal, 2002-present

o   IEEE TKDE (Transactions on Knowledge and Data Engineering), 2005-2007.

o   IEEE Intelligent Systems, 2005-2008.

o   Journal of Privacy and Confidentiality, 2006-present

Program Chair

o   ICML'03, with Tom Fawcett

Program Committees

o   ICML'16: International Conference on Machine Learning

o   IJCAI'16: International Joint Conference on Artificial Intelligence, AI and the Web Track

o   KDD'16: Applied Data Science Track

o   WSDM'15: Web Search and Data Mining

o   PODS'13: Principles of Database Systems

o   WSDM'12: Web Search and Data Mining

o   WSDM'11: Web Search and Data Mining

o   WSDM'10: Web Search and Data Mining

o   PODS'09: Principles of Database Systems

o   AAAI'08: Conference on Artificial Intelligence

o   KDD'08: Knowledge Discovery and Data Mining

o   KDD'07: Knowledge Discovery and Data Mining

o   KDD'06: Knowledge Discovery and Data Mining

o   ICML'06: International Conference on Machine Learning

o   ICML'05: International Conference on Machine Learning

o   KDD'05: Knowledge Discovery and Data Mining

o   SDM'05: SIAM International Conference on Data Mining

o   KDD'04: Knowledge Discovery and Data Mining

o   SDM'03: SIAM International Conference on Data Mining

o   ICDM'02: IEEE International Conference on Data Mining

o   SDM'02: SIAM International Conference on Data Mining

o   KDD'01: Knowledge Discovery and Data Mining

o   IJCAI'01: International Joint Conference on Artificial Intelligence

o   ICML'00: International Conference on Machine Learning

NSF Panelist: 2002, 2004, 2007.

Advisory Board, ICML'04

Teaching

o   CS302: Theory of Computation. University of Virginia. Spring 2007.

o   CS651: Internet Algorithms. University of Virginia. Fall, 2006.

o   CS851: Data Mining Algorithms. University of Virginia. Spring, 2006.

o   CS369C: Clustering Algorithms. Stanford University. Spring, 2005.

o   CS369: A Study of Perturbation Techniques for Data Privacy.With Cynthia Dwork and Kobbi Nissim. Stanford University. Spring, 2004.

o   CS361A: Advanced Algorithms for Internet Applications. With Rajeev Motwani. Stanford University. Autumn, 2002.

Patents Granted (from uspto.gov)

 

 

Patent Number

Title

14

9,171,045

Recommending queries according to mapping of query communities

13

8,738,387

System and method for determining an element value in private datasets

12

8,601,024

Synopsis of a search log that respects user privacy

11

8,219,539

Search queries with shifting intent

10

7,904,517

Challenge response systems

9

7,818,272

Method for discovery of clusters of objects in an arbitrary undirected graph using a difference between a fraction of internal connections and maximum fraction of connections by an outside object

8

7,739,313

Method and system for finding conjunctive clusters

7

7,707,058

Predicting parts needed for an onsite repair using expected waste derived from repair history

6

7,380,177

Method and system for comparing individual computers to cluster representations of their peers

5

7,225,118

Global data placement

4

7,203,864

Method and system for clustering computers into peer groups and comparing individual computers to their peers

3

6,907,380

Computer implemented scalable, incremental and parallel clustering based on weighted divide and conquer

2

6,684,177

Computer implemented scalable, incremental and parallel clustering based on weighted divide and conquer

1

6,466,946

Computer implemented scalable, incremental and parallel clustering based on divide and conquer