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Ashish Sanil
Ashish Sanil
Organization:
Berry Consultants
Professional Title:
Director and Senior Statistical Scientist
NISS Research Projects
Bayesian Models Linking Web Site Structure and Usage
Collaborative Research: Acquiring Accurate Dynamic Field Data Using Lightweight Instrumentation
Digital Government (1)
Digital Government II: Data Confidentiality, Data Quality and Data Integration For Federal Databases: Foundations to Software Prototypes
Education Statistics
Statistical Methodology for Measuring and Improving Data Quality
Technical Reports
Workshop Report: Workshop on Statistics and Information Technology (2001) -
Workshop Report: Affiliates Workshop on Data Quality (2001) -
Title IX Data Collection: Technical Manual for Developing the User's Guide (2005) -
Table Servers: Protecting Confidentiality in Tabular Data Releases (2001) -
Software Systems for Tabular Data Releases (2002) -
Secure Statistical Analysis of Distributed Databases (2005) -
Secure Regression on Distributed Databases (2004) -
Secure Regression for Vertically Partitioned, Partially Overlapping Data (2004) -
Secure Analysis of Distributed Chemical Databases without Data Integration (2005) -
Privacy Preserving Regression Modelling via Distributed Computation (2004) -
Privacy Preserving Analysis of Vertically Partitioned Data Using Secure Matrix Products (2004) -
Preserving Confidentiality of High-dimensional Tabulated Data: Statistical and Computational Issues (2002) -
NISS WebSwap: A Web Service for Data Swapping (2002) -
Disseminating Information but Protecting Confidentiality (2000) -
Data Swapping: A Risk-Utility Framework and Web Service Implementation (2003) -
Data Swapping as a Decision Process (2004) -
Data Quality: A Statistical Perspective (2005) -
Data Quality: A Statistical Perspective (2002) -
Data Quality and Data Confidentiality for Microdata: Implications and Strategies (2004) -
Data Dissemination and Disclosure Limitation in a World Without Microdata: A Risk-Utility Framework for Remote Access Analysis Servers (2004) -
A Risk-Utility Framework for Categorical Data Swapping (2003) -
A Model for Relating Browser Behavior to Site Design on the World Wide Web (2004) -
A Framework for Evaluating the Utility of Data Altered to Protect Confidentiality (2006) -
Publications
Workshop Report: Workshop on Statistics and Information Technology
Workshop Report: Affiliates Workshop on Data Quality
Web-Based Systems that Disseminate Information but Protect Confidential Data
Title IX Data Collection: Technical Manual for Developing the User’s Guide
Techniques for classifying executions of deployed software to support software engineering tasks
Table servers protect confidentiality in tabular data releases
Software Systems for Tabular Data Releases
Secure regression for vertically partitioned, partially overlapping data
Secure analysis of distributed chemical databases without data integration
Regression on distributed databases via secure multi-party computation
Privacy-preserving analysis of vertically partitioned data using secure matrix products
Privacy preserving regression modelling via distributed computation
Preserving confidentiality of high-dimensional tabular data: Statistical and computational issues
PharmID: Pharmacophore identification using Gibbs sampling
Optimal tabular releases from confidential data
NISS WebSwap: A Web Service for Data Swapping
Disseminating information but protecting confidentiality
Data swapping: A risk–utility framework and Web service implementation
Data Swapping as a Decision Problem
Data quality: A statistical perspective
Data quality and data confidentiality for microdata: implications and strategies
Data dissemination and disclosure limitation in a world without microdata: A risk-utility framework for remote access analysis servers
Applying classification techniques to remotely-collected program execution data
Analysis of integrated data without data integration
Analysis of aggregated data in survey sampling with application to fertilizer/pesticide usage surveys
Advances in Digital Government
A framework for evaluating the utility of data altered to protect confidentiality