Education

Research Description

Professor Hoit's research is in structural engineering, data analytics, and IT security.

Publications

Constructing next generation academic cloud services

Vouk, M. A., Averitt, S. F., Dreher, P., Kekas, D. H., Kurth, A., Hoit, M. I., … others. (2013), International Journal of Cloud Computing 1, 2(2-3), 104–122.

Constructing next generation academic cloud services

Vouk, M. A., Averitt, S. F., Dreher, P., Kekas, D. H., Kurth, A., Hoit, M., … Wright, D. (2013), International Journal of Cloud Computing, 2(2/3), 104–122. https://doi.org/10.1504/ijcc.2013.055290

Integrated data for bio-preparedness: The national collaborative for bio-preparedness

Potenziani, D. (2013), 141st APHA Annual Meeting and Exposition (November 2-November 6, 2013). Presented at the APHA.

National Collaborative for Bio-Preparedness

Arasaratnam, M., Potenziani, D., Hoit, M., Jenkins, C., & Cairns, C. (2013), Online Journal of Public Health Informatics, 5(1).

Development of Geotechnical Data Schema in Transportation

Hoit, M., Turner, L., & Ponti, D. (2012). , .

International Society for Disease Surveillance Conference 2011: Building the Future of Public Health Surveillance: Building the Future of Public Health Surveillance

Neill, D. B., & Soetebier, K. A. (2011), Emerging Health Threats Journal, 4.

Novel approach to statewide biosurveillance using emergency medical services (EMS) information

Cairns, C., Potenziani, D., Hoit, M., Jenkins, C., & Edgemon, S. (2011), Emerg Health Threats J, 4.

Structures Congress 2011

Ames, D., Droessler, T. L., & Hoit, M. (2011). , . American Society of Civil Engineers.

2010 Structures Congress

Senapathi, S., Casey, K., & Hoit, M. (2010). , . ASCE.

Structures Congress 2010: 19th Analysis and Computation Specialty Conference

Senapathi, S., Casey, K., & Hoit, M. (2010), 2010 Structures Congress. Presented at the ASCE.

View all publications via NC State Libraries

Grants

Land Grant Universities and Data Science Workshop: Taking Data Science to America’s Emerging Workforce

Alfred P. Sloan Foundation(4/01/18 - 5/30/19)

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Land Grant Universities and Data Science Workshop: Taking Data Science to America’s Emerging Workforce

Sponsor: Alfred P. Sloan Foundation

Start Date: 4/01/18

End Date: 5/30/19

Abstract

The rapid growth and importance of data science in all sectors of society (business, government, education, and research) threatens to transform the future of jobs. Even more worrisome than this changing mix of jobs is the threat that this change will significantly increase the level of income polarization in our society as people struggle to obtain the skills necessary to participate in this new world of jobs. This income gap will be most pronounced in those segments of our society that do not have ready access to educational or community resources; this is especially the case with rural areas and small towns. Since data science is based on having access to data, geographic proximity is not essential, as people do not need to travel to the data. What is essential, however, is that people have access and use of modern cyberinfrastructure (networks, data, compute, local and virtual communities. This in turn also means that it is quite feasible for people in remote rural areas to participate in data science work and have well paying jobs. And the ability of people to 'telework' has significantly increased over the last decade, especially as people balance quality of life issues with job opportunities. This raises a question and opportunity: might the existing Land Grant College structure be augmented and used to provide some solutions to help address the huge issues associated with workforce shortages in data science as well as broaden the geographic base? Can the Land Grant Universities, along with their Cooperative Extension services, provide educational opportunities in data science and help people who live in rural areas and small towns prepare to become part of the workforce for the 21st Century? The proposed Workshop will explore the interest, issues, and feasibility of leveraging the significant resources and infrastructure of the Land Grant Universities and the data science community to help address the educational, community, and workforce needs of the nation in data science over the next two decades. The Taking Data Science to America's Emerging Workforce will bring together a broad array of people and organizations to address many of the issues and challenges. Lastly, the workshop will identify concrete next steps, follow-on efforts, and develop recommendations on how to establish data science communities of practice across the nation.

Close

Land Grant Universities and Data Science Workshop: Taking Data Science to America’s Emerging Workforce

National Science Foundation (NSF)(5/15/18 - 5/31/19)

×

Land Grant Universities and Data Science Workshop: Taking Data Science to America’s Emerging Workforce

Sponsor: National Science Foundation (NSF)

Start Date: 5/15/18

End Date: 5/31/19

Abstract

The rapid growth and importance of data science in all sectors of society (business, government, education, and research) threatens to transform the future of jobs. Even more worrisome than this changing mix of jobs is the threat that this change will significantly increase the level of income polarization in our society as people struggle to obtain the skills necessary to participate in this new world of jobs. This income gap will be most pronounced in those segments of our society that do not have ready access to educational or community resources; this is especially the case with rural areas and small towns. Since data science is based on having access to data, geographic proximity is not essential, as people do not need to travel to the data. What is essential, however, is that people have access and use of modern cyberinfrastructure (networks, data, compute, local and virtual communities. This in turn also means that it is quite feasible for people in remote rural areas to participate in data science work and have well paying jobs. And the ability of people to 'telework' has significantly increased over the last decade, especially as people balance quality of life issues with job opportunities. This raises a question and opportunity: might the existing Land Grant College structure be augmented and used to provide some solutions to help address the huge issues associated with workforce shortages in data science as well as broaden the geographic base? Can the Land Grant Universities, along with their Cooperative Extension services, provide educational opportunities in data science and help people who live in rural areas and small towns prepare to become part of the workforce for the 21st Century? The proposed Workshop will explore the interest, issues, and feasibility of leveraging the significant resources and infrastructure of the Land Grant Universities and the data science community to help address the educational, community, and workforce needs of the nation in data science over the next two decades. The Taking Data Science to America's Emerging Workforce will bring together a broad array of people and organizations to address many of the issues and challenges. Lastly, the workshop will identify concrete next steps, follow-on efforts, and develop recommendations on how to establish data science communities of practice across the nation.

Close

CC-NIE Networking Infrastructure: Data Intensive e-Science and SDN at NCSU

National Science Foundation (NSF)(9/01/13 - 8/31/16)

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CC-NIE Networking Infrastructure: Data Intensive e-Science and SDN at NCSU

Sponsor: National Science Foundation (NSF)

Start Date: 9/01/13

End Date: 8/31/16

Abstract

Networking Infrastructure, equipment and implementation grant

Close

North Carolina Bio-Preparedness Collaboration (NCB-Prepared)

US Dept. of Homeland Security (DHS)(5/01/10 - 2/28/15)

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North Carolina Bio-Preparedness Collaboration (NCB-Prepared)

Sponsor: US Dept. of Homeland Security (DHS)

Start Date: 5/01/10

End Date: 2/28/15

Abstract

NCSU will enhance the NCBP demonstration system produced in 2011 to provide high availability and an interface for mapping, graphing trends, and listing signals that enable reports via visualization.

Close