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The National Institute of Statistical Sciences (NISS) is a leading independent non-profit research institute specializing in Statistics and Data Science. Founded by the American Statistical Association, the International Biometric Society, and the Institute of Mathematical Statistics, NISS collaborates with federal agencies and private sector clients to tackle large-scale data challenges using cutting-edge methodologies and AI technologies. The Institute conducts both independent and targeted research focused on data acquisition design, analysis, and representation, emphasizing practical implementation. NISS advances the technical Statistics and Data Science community through webinars, conferences, and roundtables highlighting the latest developments in theory and methodology. As a neutral and objective technical expert, NISS rigorously reviews research findings, evaluates practices, assesses policy effectiveness, compares methodologies, and proposes best practices. It leverages expertise in statistical survey theory, AI applications, and heterogeneous data sources, tapping into a vast network of experts across various sciences. NISS has successfully collaborated with organizations like the National Center for Education Statistics, the Bureau of Labor Statistics, the Census Bureau, the Energy Information Agency, and the National Agricultural Statistics Service.
Major Services NISS Offers
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- Expert Panels, Forums, and Reports
- Expert Reviewing and Validation
- Targeted Research
- Task Force Implementation Teams
- Online Meeting & Webinar Organization
- Research Staff Contracting
- Training Courses & Workshops
Major Areas of Expertise & Experience
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- AI in Federal Government
- Bias Mitigation in AI Models
- Biomarkers
- Blended Data Methods & Analysis
- Causal Inference
- Clinical Medical Research
- Computer/Web
- Cross-Sector Research
- Cybersecurity
- Data Integration & Transfer Learning
- Data Science
- Data Visualization: Tools & Research
- Disease Surveillance
- Disseminate Data
- Educational Research
- Environmental Science
- Functional Data Analysis
- Internal Survey
- Statistical Machine Learning
- Methods Evaluation & Best Practice
- Missing Data; Imbalance & Fairness
- Omics
- Privacy Preserving Methods
- Psychometrics
- Quality Control
- Research Methodology
- Software Development
- SRS Data Sets
- Statistical Modeling
- Survey Error & Quality
- Survey Methodology
- Time Series & Forecasting