Faculty Profile

Michael Monticino

Title
Professor
Department
Toulouse Graduate School
College
University of North Texas
Professor
Mathematics
College of Science

    

Education

PhD, University of Miami, 1987.
Major: Mathematics
BS, University of Florida, 1982.
Major: Mathematics

Current Scheduled Teaching*

ADTA 5620.001, Applied and Computational Statistics for Data Analytics, Spring 2023

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Previous Scheduled Teaching*

ADTA 5620.501, Applied and Computational Statistics for Data Analytics, Spring 2022 SPOT
ADTA 5610.501, Applied Probability Modeling for Data Analytics, Fall 2021 SPOT
MATH 5820.501, Probability and Statistics, Spring 2021 Syllabus SPOT
MATH 5810.501, Probability and Statistics, Fall 2020 Syllabus SPOT
MATH 5820.501, Probability and Statistics, Spring 2020 Syllabus
MATH 5810.501, Probability and Statistics, Fall 2019 Syllabus SPOT
CSCE 5300.501, Introduction to Big Data and Data Science, Spring 2019 SPOT
ADTA 5120.501, Introduction to Data Analytics, Spring 2019 SPOT
MATH 5810.501, Probability and Statistics, Fall 2018 SPOT
INSD 5120.501, Introduction to Data Science, Spring 2018 SPOT
INSD 5120.501, Introduction to Data Science, Fall 2017 SPOT
MATH 3680.003, Applied Statistics, Spring 2016 Syllabus SPOT
MATH 3680.004, Applied Statistics, Fall 2015 Syllabus SPOT
MATH 1710.020, Calculus I, Summer 5W1 2015 SPOT
MATH 6950.716, Doctoral Dissertation, Fall 2010
MATH 6950.716, Doctoral Dissertation, Summer 5W1 2010
MATH 6950.716, Doctoral Dissertation, Spring 2010
MATH 6900.707, Special Problems, Spring 2010
MATH 6950.716, Doctoral Dissertation, Fall 2009
MATH 6900.716, Special Problems, Fall 2009
MATH 6950.716, Doctoral Dissertation, Spring 2009
MATH 5900.719, Special Problems, Spring 2009
MATH 6900.707, Special Problems, Spring 2009
MATH 6950.716, Doctoral Dissertation, Fall 2008
MATH 6900.716, Special Problems, Fall 2008
MATH 6950.716, Doctoral Dissertation, Summer 5W2 2008
MATH 5900.703, Special Problems, Summer 5W2 2008
MATH 6950.716, Doctoral Dissertation, Spring 2008
MATH 5820.001, Probability and Statistics, Spring 2008
MATH 5900.756, Special Problems, Spring 2008
MATH 6900.707, Special Problems, Spring 2008
MATH 6910.717, Special Problems, Spring 2008
MATH 4650.001, Statistics, Spring 2008
MATH 6950.716, Doctoral Dissertation, Fall 2007
MATH 4610.001, Probability, Fall 2007
MATH 5810.001, Probability and Statistics, Fall 2007
MATH 5900.766, Special Problems, Fall 2007
MATH 6900.716, Special Problems, Fall 2007
MATH 6950.716, Doctoral Dissertation, Summer 5W2 2007
MATH 6950.716, Doctoral Dissertation, Spring 2007
MATH 1680.007, Elementary Probability and Statistics, Spring 2007
MATH 5950.717, Master's Thesis, Spring 2007
MATH 5950.716, Master's Thesis, Fall 2006
MATH 1780.001, Probability Models, Fall 2006
MATH 4900.702, Special Problems, Fall 2006
MATH 5900.766, Special Problems, Fall 2006
MATH 5820.001, Probability and Statistics, Spring 2006
MATH 4900.709, Special Problems, Spring 2006
MATH 4900.712, Special Problems, Spring 2006
MATH 5900.719, Special Problems, Spring 2006
MATH 4650.001, Statistics, Spring 2006
MATH 4610.001, Probability, Fall 2005
MATH 5810.001, Probability and Statistics, Fall 2005
MATH 4900.702, Special Problems, Fall 2005
MATH 5900.721, Special Problems, Fall 2005
MATH 4900.709, Special Problems, Spring 2005
MATH 5900.723, Special Problems, Spring 2005
MATH 6900.723, Special Problems, Spring 2005
MATH 4900.702, Special Problems, Fall 2004
MATH 6900.723, Special Problems, Fall 2004

* Texas Education Code 51.974 (HB 2504) requires each institution of higher education to make available to the public, a syllabus for undergraduate lecture courses offered for credit by the institution.

Published Publications

Published Intellectual Contributions

Abstracts and Proceedings
Monticino, M. G. (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.
Monticino, M. G. (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.)..
Monticino, M. G. (2005). Multi-agent model of human values and land-use change.
Monticino, M. G. (2004). Coupled Human and Natural Systems:  A Multi-Agent Based Approach.
Monticino, M. G. (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.
Monticino, M. G. (2010). "Interdisciplinarity in the Biological Sciences". Handbook of Interdisciplinarity. Oxford University Press.
Monticino, M. G. (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
Monticino, M. G. (2011). Research on Coupled Human and Natural Systems (CHANS): Approach, Challenges and Strategies. Bulletin of the Ecological Society of America. 92, 218-228.
Monticino, M. G. (2008). "Models of Natural and Human Dynamics in Forest Landscapes: cross-site and cross-cultural synthesis". Geoforum. 39, 846-866.
Monticino, M. G. (2007). "Analysis of Teller Service Times in Retail Banks".
Monticino, M. G. (2007). "Biocomplexity and Conservation of Biodiversity Hotspots: Three Case Studies from the Americas".
Monticino, M. G. (2007). "Coupled Human and Natural Systems:  A Multi-Agent Based Approach".
Monticino, M. G. (2006). "Biocomplexity in the Big Thicket". Ethics, Place & Environment. 9, 21-45.
Monticino, M. G. (2005). "Assessing physiological complexity". Journal of Experimental Biology. 208, 3221-3232.
Monticino, M. G. (2004). Effects of Culture on Computer-Supported International Collaborations.
Monticino, M. G. (2003). Pseudo-prophet inequalities in average-optimal stopping.
Monticino, M. G. (2001). How to a construct random probability measure.
Monticino, M. G. (2001). Optimal stopping rules for directionally reinforced processes.
Monticino, M. G. (1998). Constructing prior distributions with trees of exchangeable processes.
Monticino, M. G. (1998). Constructions of random distributions via sequential barycenters.
Monticino, M. G. (1998). Web-Analysis: Stripping away the hype.
Monticino, M. G. (1996). Directionally reinforced random walks.
Monticino, M. G. (1995). Optimal cut-off strategies in capacity expansion problems.
Monticino, M. G. (1995). Randomly generated distributions.
Monticino, M. G. (1992). A survey of the search theory literature.
Monticino, M. G. (1991). The adequacy of universal strategies in analytic gambling problems.
Monticino, M. G. (1991). Utility functions which ensure the adequacy of stationary strategies.
Other
Monticino, M. G. (2008). "Application of Mathematical Models to Classify and Characterize Cell Types Derived from Neural Progenitor Cells".
Popular Press Article
Monticino, M. G. (1989). The feasibility of applying search theory to the Korean tunnel problem.
Monticino, M. G. (1988). The effects of non-homogenous environments on passive sonobuoy search for a submerged target.

Awarded Grants

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. (June 1, 2018October 31, 2018).
Grant - Research
Monticino, M. (Principal), "Transportation Resource Study," Sponsored by Capital One/Boys & Girls Club, National, $15000 Funded. (November 2019September 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. (February 2022 – Present).
,
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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