Our Faculty

Belgacem Raggad

Professor

Seidenberg School of CSIS

Information Technology NY

Location
  • @New York City
    Goldstein Academic Center 320
Office Hours
New York City

Spring 2021

Thu 1:00pm-6:00pm(by appointment)

Office Hours

Spring 2021

Office Hours

Spring 2021

Education


PhD, Pennsylvania State University at University Park, 1989
Information Management

MS, University of Tunis, 1979
Computer Information Systems

A.D., University of Tunis, 1975
Mathematics and Physics

Awards and Honors


The Country of Tunisia, November 1, 2001 - Gold Medal for Great Contributions in IS Security
Pace University, School of Computer Science and Information System, December 31, 1998 - CSIS Excellence in Research Award
NULL, June 6, 1998 - Award in Excellence in Research & Scholarship, Pace University
Data Processing Management Association, December 31, 1989 - Data Processing Management Award
NULL, December 31, 1982 - Fulbright Scholarship
CII-Honeywell Bull of Paris, December 31, 1979 - Scholarship


Publications


A Security-policy Driven Distributed Incident Response Generator
Raggad, B. (2012, August). International Scientific Survey Journal. Vol Vol 2 (Issue 6)

The State of Big Data
Raggad, B. (2020, January (1st Quarter/Winter) 01).

Sound Big Data Decision Support Despite its V's Article:Sound Big Data Decision Support Despite its V's
Raggad, B.

Security Risk Learning in Cybersecurity: Evidential Reasoning Model
Raggad, B. & Tappert, C. http://www.sedsi.org/
DOWNLOAD

Evidential Modeling for Telemedicine Continual Security
Mansouri, S., , . & , . (2018, February). International Journal of Computer Science and Network Security. Vol 6 (Issue 5) , pages 559-564. http://ijcsn.org/publications.html

Risk of Telemedicine Infeasibility: An Evidential Reasoning Approach
Mansouri, S. (2017, October (4th Quarter/Autumn) 1). International Journal of Medical Research & Health Sciences. Vol 6 (Issue 10) http://ijmrhs.com/abstract/risk-of-telemedicine-infeasibility-an-evidential-reasoning-approach-13146.html

Intelligent Decision Support Capabilities for a Law Enforcement GIS
Raggad, B. (2017, October (4th Quarter/Autumn) 1). http://aisel.aisnet.org/siggis2016/2/

Enforcing Patient Privacy Assurance Policy: A Privacy Violation Detection and Response System
Mansouri, S. Vol 2016 http://journals.indexcopernicus.com/

Telemedicine: Distributed Decision Support with Partial Compatibility Evidence
Mansouri, S. (2016, October (4th Quarter/Autumn) 30). Vol 2016 http://seinforms.org

Evidential Reasoning in Real-time Monitoring of Computing Systems
, . & Akermi, A. Vol 2016 http://cisse.info

Autonomic Computing and Policy Based Systems:
Raggad, B. INASE Journal. Vol 2015 (Issue 2015) http://www.inase.org
DOWNLOAD

Decision Support Treating Partial Compatibility Evidence in Telemedicine
Raggad, B. Vol 2015 http://inase.org

Towards a Science of Cyber Security: A Security Self-Security Generator
Raggad, B. Vol 2014

PRESENTATIONS


Raggad, B. (2018, March 24). Predictive Analytics in Big Data. International Conference on Technology, Engineering & Mathematics, Kenitra, Morocco.

Tappert, C. (2018, February 22). SEDSI. Security Risk Learning in Cybersecurity Model. DSI, Wilmington NC.

Raggad, B. (2017, October 4). Southeast INFORMS. Actioning Big Data. INFORMS, Myrtle Beach, SC.

Raggad, B. (2017, March 9). IIAB 2017. Risk-driven Corporate Security Defense. IIAB, Miami.

Raggad, B. (2016, December 9). GIS. Intelligent Decision Support Capabilities for a Law Enforcement GIS. AIS, Dublin, Ireland.

RESEARCH INTEREST


Management Information Systems (Decision Support Systems); Software Engineering (Information Systems Development); Artificial Intelligence (Approximate Reasoning);

Grants, Sponsored Research and Contracts


Deep Data: Invisible Analytics
Raggad, B. January 2017 - December 2019.Scholarly Research Papers,Pace University,$3,045.00.Funded.On Internet we only access about 1% of existing Internet data. The rest is called deep data. We need what we call Invisible Analytics to get to some of it. If we are successful in doing this, it is just unbelievable the gains we get. For example, a university can use Invisible Analytics to understand student retention problems and can make corrections to maintain and improve its retention rate. A company can understand the reasons behind its customer attrition and what is behind its business value retention deficiencies. Invisible analytics will be the tool set needed to maintain its customers and enhance their loyalty which will secure its business value generation capabilities. Another example would be to use Invisible Analytics to understand our healthcare deficiencies and act to correct it. Unfortunately, we still spending billions of dollars on data capture from the Internet or from business operational systems to create boundless big data depots that we cannot dig it to produce valuable decision support information. We still have no clear approach to design the platform needed to start designing the analytical tools to generate decision support information to enhance business value in our educational systems, our healthcare systems, and our economy. This research project intends to design a computing platform for the development of Invisible Analytics tools to get into deep data and to explore our big data depots to produce valuable decision support information. We have completed the quantitative analysis and we were successful in building the belief structures needed to construct the needed probabilistic framework for the purpose of building the analytical tools for expanded data analytics. We also have tested our models in telemedicine to detect e-patient attrition and mitigate its impacts. We are currently working to extend the testing to other areas including student retention.

PROFESSIONAL MEMBERSHIPS


BIOMETRICS

Computational Intelligence for Modelling, Control and Automation

CORS: Canadian Society of Operations Research

Decision Science Institute

E-commerce Security Society

Federal Information Systems Security Educators' Association (FISSEA)

FRANCORO - Francophones de Recherche Opérationnelle

FRANCORO II Conference[Member, Program Committee - 2000 Conference]

IATF: Information Assurance Technical Framework (National Security Agency)

INFORMS (TIMS/ORSA)

International Association of Business Disciplines

International Association of Computer Information Systems

JOPT - Des Journées de l'Optimisation (Optimization Days of Canada)

Literati Club, Great Britain

NE-DSI: Northeastern Decision Science Institute

SAM - Society for Advances in Management

Int Academy of Bus and Pub Adm Deciplines[Editor of Journal]

The National Colloquium for Information Systems Security Education[Reviewer]

Association of Information Systems[Member]

Information Systems Audit And Control Association[Member]

UNIVERSITY SERVICE


  • Seidenberg Dean Performance Evaluation Committee[Committee Member]
    Desc: Reconfirm the dean
    Committee's Key Accomplishments: Evaluate the performance of the dean. Collect evidence from surveying and interviewing student, faculty, and staff.

PUBLIC SERVICE


  • Pace University, Computer Science & Information Systems[Other]
    Desc: Travel to provide assistance to developing countries reviewing their Technology Management programs and develop effective strategies to protect against cyber terrorism: about 22 days of lectures, advising, and interventions.
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