Peter Fontana

ORCID: 0000-0002-1101-2010
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About
Contact & Profiles
Research Areas
  • Formal Methods in Verification
  • Big Data and Business Intelligence
  • Logic, programming, and type systems
  • Species Distribution and Climate Change
  • Scientific Computing and Data Management
  • Research Data Management Practices
  • semigroups and automata theory
  • Software Testing and Debugging Techniques
  • Remote Sensing in Agriculture
  • Data Quality and Management
  • Chromosomal and Genetic Variations
  • Model-Driven Software Engineering Techniques
  • Explainable Artificial Intelligence (XAI)
  • Genetic and Clinical Aspects of Sex Determination and Chromosomal Abnormalities
  • Adversarial Robustness in Machine Learning
  • Data Visualization and Analytics
  • Data Analysis with R
  • Ecology and Vegetation Dynamics Studies
  • Multi-Agent Systems and Negotiation
  • Occupational Health and Safety Research
  • Face recognition and analysis
  • Radio, Podcasts, and Digital Media
  • Neural Networks and Applications
  • Speech and dialogue systems
  • Petri Nets in System Modeling

National Institute of Standards and Technology
2015-2025

Information Technology Laboratory
2021-2025

National Institute of Standards
2015-2021

Access to Wholistic and Productive Living Institute
2021

University of Maryland, College Park
2011-2017

Population Reference Bureau
2016

We introduce four principles for explainable artificial intelligence (AI) that comprise the fundamental properties AI systems.They were developed to encompass multidisciplinary nature of AI, including fields computer science, engineering, and psychology.Because one size fits all explanations do not exist, different users will require types explanations.We present five categories explanation summarize theories AI.We give an overview algorithms in field cover major classes algorithms.As a...

10.6028/nist.ir.8312-draft preprint EN 2020-08-17

Abstract The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To enable technology developers along with research clinical laboratories to evaluate variant detection on male X Y, we create a small benchmark set 111,725 variants for Genome Bottle HG002 reference material. We develop an active evaluation approach demonstrate reliably identifies errors challenging genomic regions across...

10.1038/s41467-024-55710-z article EN cc-by Nature Communications 2025-01-08

Ecology has reached the point where data science competitions, in which multiple groups solve same problem using by different methods, will be productive for advancing quantitative methods tasks such as species identification from remote sensing images. We ran a competition to help improve three that are central converting images into information on individual trees: (1) crown segmentation, identifying location and size of trees; (2) alignment, match ground truthed trees with sensing; (3)...

10.7717/peerj.5843 article EN cc-by PeerJ 2019-02-28

Ecology has reached the point where data science competitions, in which multiple groups solve same problem using by different methods, will be productive for advancing quantitative methods tasks such as species identification from remote sensing images. We ran a competition to help improve three that are central converting images into information on individual trees: 1) crown segmentation, identifying location and size of trees; 2) alignment, match ground truthed trees with sensing; 3)...

10.7287/peerj.preprints.26966v1 preprint EN 2018-05-29

We examine foundational issues in data science including current challenges, basic research questions, and expected advances, as the basis for a new Data Science Initiative evaluation series, introduced by National Institute of Standards Technology (NIST) fall 2015. The evaluations will facilitate efforts, collaboration, leverage shared infrastructure, effectively address cross-cutting challenges faced diverse communities. have multiple tracks championed members community, enable rigorous...

10.1109/dsaa.2015.7344805 article EN 2015-10-01

While prior evaluation methodologies for data-science research have focused on efficient and effective teamwork independent data science problems within given fields [1], this paper argues that an enriched notion of evaluation-driven (EDR) supports solutions to across multiple fields. We adopt the view progress in is through examination a range many different areas (traffic, healthcare, finance, sports, etc.) development paradigms span diverse disciplines, domains, problems, tasks. A number...

10.1109/bigdata.2016.7840934 article EN 2021 IEEE International Conference on Big Data (Big Data) 2016-12-01

This paper establishes relative expressiveness results for several modal mu-calculi interpreted over timed automata. These combine modalities expressing passage of (real) time with a general framework defining formulas recursively; variants have been proposed in the literature. We show that one logic, which we call $L^{rel}_{ν,μ}$, is strictly more expressive than other considered. It also temporal logic TCTL, while are incomparable TCTL setting

10.48550/arxiv.2310.04100 preprint EN other-oa arXiv (Cornell University) 2023-01-01

Abstract The sex chromosomes contain complex, important genes impacting medical phenotypes, but differ from the autosomes in their ploidy and large repetitive regions. To evaluate variant detection on X Y, we created an 111,725 benchmark for Genome a Bottle HG002 reference material. We show how complete assemblies can expand benchmarks to difficult regions, highlight remaining challenges benchmarking complex gene conversions, copy number variable arrays, human satellites.

10.1101/2023.10.31.564997 preprint EN bioRxiv (Cold Spring Harbor Laboratory) 2023-11-01

Ecology has reached the point where data science competitions, in which multiple groups solve same problem using by different methods, will be productive for advancing quantitative methods tasks such as species identification from remote sensing images. We ran a competition to help improve three that are central converting images into information on individual trees: 1) crown segmentation, identifying location and size of trees; 2) alignment, match ground truthed trees with sensing; 3)...

10.7287/peerj.preprints.26966 preprint EN 2018-05-29

The Information Access Division (IAD) of the National Institute Standards and Technology (NIST) launched a new Data Science Initiative in fall 2015. This initiative focuses on evaluation-driven research will establish Evaluation series to facilitate collaboration, leverage shared technology infrastructure, further build strengthen data science community. evaluation consist pre-pilot be 2015, pilot 2016, full-scale multiple-track 2017. In addition these evaluations, this aims address several...

10.1109/bigdata.2015.7364096 article EN 2021 IEEE International Conference on Big Data (Big Data) 2015-10-01
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