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Michael G. Monticino

Title: Professor

Department: ADA - Advanced Data Analytics

College: University of North Texas

Curriculum Vitae

Curriculum Vitae Link

Education

  • PhD, University of Miami, 1987
    Major: Mathematics
    Dissertation: The Adequacy of Measurable and of Stationary Strategies for Approximating Optimal Returns
  • BS, University of Florida, 1982
    Major: Mathematics

Current Scheduled Teaching

ADTA 5610.001Applied Probability Modeling for Data AnalyticsFall 2024 Syllabus

Previous Scheduled Teaching

ADTA 5920.001ADTA InternshipSpring 2024 SPOT
ADTA 5610.001Applied Probability Modeling for Data AnalyticsFall 2023 SPOT
ADTA 5620.001Applied and Computational Statistics for Data AnalyticsSpring 2023 SPOT
ADTA 5620.501Applied and Computational Statistics for Data AnalyticsSpring 2022 SPOT
ADTA 5610.501Applied Probability Modeling for Data AnalyticsFall 2021 SPOT
MATH 5820.501Probability and StatisticsSpring 2021 SPOT
MATH 5810.501Probability and StatisticsFall 2020 SPOT
MATH 5820.501Probability and StatisticsSpring 2020
MATH 5810.501Probability and StatisticsFall 2019 SPOT
CSCE 5300.501Introduction to Big Data and Data ScienceSpring 2019 SPOT
ADTA 5120.501Introduction to Data AnalyticsSpring 2019 SPOT
MATH 5810.501Probability and StatisticsFall 2018 SPOT
INSD 5120.501Introduction to Data ScienceSpring 2018 SPOT
INSD 5120.501Introduction to Data ScienceFall 2017 SPOT
MATH 3680.003Applied StatisticsSpring 2016 Syllabus SPOT
MATH 3680.004Applied StatisticsFall 2015 Syllabus SPOT
MATH 1710.020Calculus ISummer 5W1 2015 SPOT
MATH 6950.716Doctoral DissertationFall 2010
MATH 6950.716Doctoral DissertationSummer 5W1 2010
MATH 6950.716Doctoral DissertationSpring 2010
MATH 6900.707Special ProblemsSpring 2010
MATH 6950.716Doctoral DissertationFall 2009
MATH 6900.716Special ProblemsFall 2009
MATH 6950.716Doctoral DissertationSpring 2009
MATH 5900.719Special ProblemsSpring 2009
MATH 6900.707Special ProblemsSpring 2009
MATH 6950.716Doctoral DissertationFall 2008
MATH 6900.716Special ProblemsFall 2008
MATH 6950.716Doctoral DissertationSummer 5W2 2008
MATH 5900.703Special ProblemsSummer 5W2 2008
MATH 6950.716Doctoral DissertationSpring 2008
MATH 5820.001Probability and StatisticsSpring 2008
MATH 5900.756Special ProblemsSpring 2008
MATH 6900.707Special ProblemsSpring 2008
MATH 6910.717Special ProblemsSpring 2008
MATH 4650.001StatisticsSpring 2008
MATH 6950.716Doctoral DissertationFall 2007
MATH 4610.001ProbabilityFall 2007
MATH 5810.001Probability and StatisticsFall 2007
MATH 5900.766Special ProblemsFall 2007
MATH 6900.716Special ProblemsFall 2007
MATH 6950.716Doctoral DissertationSummer 5W2 2007
MATH 6950.716Doctoral DissertationSpring 2007
MATH 1680.007Elementary Probability and StatisticsSpring 2007
MATH 5950.717Master's ThesisSpring 2007
MATH 5950.716Master's ThesisFall 2006
MATH 1780.001Probability ModelsFall 2006
MATH 4900.702Special ProblemsFall 2006
MATH 5900.766Special ProblemsFall 2006
MATH 5820.001Probability and StatisticsSpring 2006
MATH 4900.709Special ProblemsSpring 2006
MATH 4900.712Special ProblemsSpring 2006
MATH 5900.719Special ProblemsSpring 2006
MATH 4650.001StatisticsSpring 2006
MATH 4610.001ProbabilityFall 2005
MATH 5810.001Probability and StatisticsFall 2005
MATH 4900.702Special ProblemsFall 2005
MATH 5900.721Special ProblemsFall 2005
MATH 4900.709Special ProblemsSpring 2005
MATH 5900.723Special ProblemsSpring 2005
MATH 6900.723Special ProblemsSpring 2005
MATH 4900.702Special ProblemsFall 2004
MATH 6900.723Special ProblemsFall 2004

Published Intellectual Contributions

    Abstracts and Proceedings

  • Gregory Hill, Michael Monticino, Eric T. Jones, Steven Kolmes, and Rebecca McLain. (2008). "Aspirational Goals and Incremental Tools: Does forecasting exclude other frameworks for strategic planning?". Computer Professionals for Social Responsibility Directions and Implications of Advanced Computing Conference Proceedings.
  • M. Monticino, E. Brooks, T. Cogdill, M. Acevedo and B. Callicott. (2006). "Applying a Multi-Agent Model to Evaluate Effects of Development Proposals and Growth Management Policies on Suburban Sprawl". Proceedings of the iEMSs Third Biennial Meeting: Summit on Environmental Modelling and Software; Voinov, A., Jakeman, A., Rizzoli, A. (eds.)..
  • Michael Monticino, Miguel Acevedo, Baird Callicott and Travis Cogdill. (2005). Multi-agent model of human values and land-use change.
  • Michael Monticino, Miguel Acevedo, Baird Callicott, Travis Cogdill, and Christopher Lindquist. (Pahl-Wostl, C., Schmidt, S., Rizzoli, A.E. and Jakeman, A.J. (eds.)). (2004). Coupled Human and Natural Systems:  A Multi-Agent Based Approach.
  • Michael Monticino, Miguel Acevedo and Travis Cogdill. (2002). "Cell interaction in semi-Markov forest landscape models" In Rizzoli, A.E. and Jakeman, A.J. (eds.), Integrated Assessment and Decision Support.
  • Book Chapter

  • Burggren, W.W., , Chapman, K.D., Monticino, M.G., Torday, J. (2017). Interdisciplinarity In The Biological Sciences.. (2) Oxford University Press.
  • Warren Burggren, Kent Chapman, Bradley Keller, Michael Monticino and John Torday. (2010). "Interdisciplinarity in the Biological Sciences". Handbook of Interdisciplinarity. Oxford University Press.
  • McIntosh, Giupponi, Voinov, Smith, Matthews, Monticino, Kolkman, Crossman, van Ittersum, Haase, Haase, Mysiak, Groot, Sieber, Verweij, Quinn, Waeger, Gaber, Hepting, Scholten, Sulis, van Delden, Gaddis, Assaf. (2009). "Bridging the gaps between design and use: developing tools to support environmental management and policy". Environmental Modelling & Software. State of the Art and Futures in Environmental Modelling and Software, Jakeman, T., Rizzoli, A., Voinov, A. & Chen (eds.). Elsevier.
  • Conference Proceeding

  • Mikler, A.R., Monticino, M.G., Callicott, B., Khalil, S. (2003). Agent based modeling of human and natural systems and their interactions. In Proceedings of 7th Annual Swarm Researchers/Users Conference (SwarmFest 2003), Notre Dame, IN.
  • Journal Article

  • McConnell, Millington, Reo, Alberti, Asbjornsen, Baker, Brozović, Drinkwater, Drzyzga, Fragoso, Holland, Jantz, Kohler, Maschner, Monticino, Podestá, Pontius, Redman, Sailor, Urquhart, Liu.. (2011). Research on Coupled Human and Natural Systems (CHANS): Approach, Challenges and Strategies. Bulletin of the Ecological Society of America. 92 218-228.
  • Miguel F. Acevedo, Baird Callicott, Michael Monticino, Donald Lyons, Jenny Palomino, Judith Rosales, Luz Delgado, Magdiel Ablan, Jacinto Davila, Hirma Ramírez, Emilio Vilanova, Giorgio Tonella. (2008). "Models of Natural and Human Dynamics in Forest Landscapes: cross-site and cross-cultural synthesis". Geoforum. 39 846-866.
  • Travis Cogdill and Michael Monticino. (2007). "Analysis of Teller Service Times in Retail Banks".
  • J. Baird Callicott, Ricardo Rozzi, Luz Delgado, Michael Monticino, Miguel Acevedo and Paul Harcombe. (2007). "Biocomplexity and Conservation of Biodiversity Hotspots: Three Case Studies from the Americas".
  • Michael Monticino, Miguel Acevedo, Baird Callicott, Travis Cogdill and Christopher Lindquist. (2007). "Coupled Human and Natural Systems:  A Multi-Agent Based Approach".
  • Baird Callicott, Miguel Acevedo, Pete Gunter, Paul Harcombe, Christopher Lindquist and Michael Monticino. (2006). "Biocomplexity in the Big Thicket". Ethics, Place & Environment. 9 21-45.
  • W. Burggren and M. Monticino. (2005). "Assessing physiological complexity". Journal of Experimental Biology. 208 3221-3232.
  • Kathleen Swigger, Ferda Alpaslan, Robert Brazile, and Michael Monticino. (2004). Effects of Culture on Computer-Supported International Collaborations.
  • Pieter Allaart and Michael Monticino. (2003). Pseudo-prophet inequalities in average-optimal stopping.
  • M.G. Monticino. (2001). How to a construct random probability measure.
  • Pieter Allaart and Michael Monticino. (2001). Optimal stopping rules for directionally reinforced processes.
  • M.G. Monticino. (1998). Constructing prior distributions with trees of exchangeable processes.
  • Theodore Hill and Michael Monticino. (1998). Constructions of random distributions via sequential barycenters.
  • M.G. Monticino. (1998). Web-Analysis: Stripping away the hype.
  • R. D. Mauldin, M.G. Monticino and H. von Weizsacker. (1996). Directionally reinforced random walks.
  • M.G. Monticino and J. R. Weisinger. (1995). Optimal cut-off strategies in capacity expansion problems.
  • R. D. Mauldin and M.G. Monticino. (1995). Randomly generated distributions.
  • S. J. Benkoski, M.G. Monticino and J. R. Weisinger. (1992). A survey of the search theory literature.
  • M.G. Monticino. (1991). The adequacy of universal strategies in analytic gambling problems.
  • M.G. Monticino. (1991). Utility functions which ensure the adequacy of stationary strategies.
  • Other

  • J. Dau, E. Lightfoot, H. D. Schwark, M. Monticino and J. Fuchs. (2008). "Application of Mathematical Models to Classify and Characterize Cell Types Derived from Neural Progenitor Cells".
  • Popular Press Article

  • M.G. Monticino and J. R. Weisinger. (1989). The feasibility of applying search theory to the Korean tunnel problem.
  • M.G. Monticino and S. J. Benkoski. (1988). The effects of non-homogenous environments on passive sonobuoy search for a submerged target.

Contracts, Grants and Sponsored Research

    Contract

  • Fite, J.T. (Supporting), Monticino, M.G. (Principal), "Lockheed Martin Supply Chain Analytics Program," sponsored by Lockheed Martin, International, $50000 Funded. (2018 - 2018).
  • Fite, J. (Supporting), Monticino, M. (Principal), "Lockheed Martin Supply Chain Analytics Program," sponsored by Lockheed Martin, International, Funded. (2018 - 2018).
  • Grant - Research

  • Monticino, M. (Principal), "Transportation Resource Study," sponsored by Capital One/Boys & Girls Club, National, $15000 Funded. (2019 - 2020).
  • Monticino, M. (Principal), "Transportation Resource Study," sponsored by Capital One/Boys & Girls Club, National, Funded. (2019 - 2020).
  • Grant - Teaching

  • Monticino, M., "Stackable Micro-Courses – A Pathway to UNT Data Analytics Certificates," sponsored by Texas Higher Education Coordinating Board: Accelerating Credentials of Purpose and Value Grant Program, State, $325321 Funded. (2022).
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Overall
Summative Rating
Challenge and
Engagement Index
Response Rate

out of 5

out of 7
%
of
students responded
  • Overall Summative Rating (median):
    This rating represents the combined responses of students to the four global summative items and is presented to provide an overall index of the class’s quality. Overall summative statements include the following (response options include a Likert scale ranging from 5 = Excellent, 3 = Good, and 1= Very poor):
    • The course as a whole was
    • The course content was
    • The instructor’s contribution to the course was
    • The instructor’s effectiveness in teaching the subject matter was
  • Challenge and Engagement Index:
    This rating combines student responses to several SPOT items relating to how academically challenging students found the course to be and how engaged they were. Challenge and Engagement Index items include the following (response options include a Likert scale ranging from 7 = Much higher, 4 = Average, and 1 = Much lower):
    • Do you expect your grade in this course to be
    • The intellectual challenge presented was
    • The amount of effort you put into this course was
    • The amount of effort to succeed in this course was
    • Your involvement in course (doing assignments, attending classes, etc.) was
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