Bastias, Alfonso Gonzalo

Research

research overview

I created a Decision Support System (Strategic Decisions Method Comparing Risks, Performance Outcomes, and Scenarios - Patent pending) that offers a tool for creating and evaluating management strategies for business ventures or capital expenditure decisions. More particularly, it relates to decision-making logic using a computer-based platform, data, expert judgment, structure, and simulation analysis to support a strategic decision process.

keywords

Artificial Intelligence, Machine Learning, Decision Support Systems, Decision Making, Project Management/Project Control, Construction Management, Lean Construction, Software Development, Cloud Technology, Knowledge Management, Innovation, Education, and Leadership.

Publications

selected publications

chapter
- Decision Models to Support the Selection and Implementation of Lean Construction 2022
conference proceeding
journal article
- Timeline and outcomes of viral and fungal infections after chimeric antigen receptor T-cell therapy: a large database analysis. Clinical Microbiology and Infection. 466-472. 2025
- Construction Project Peer Reviews as an Early Indicator of Project Success. Journal of Management in Engineering. 327-333. 2013
- Modelo de aprendizaje para la selección de un proyecto diseño-construcción (llave en mano) en el sector público. Revista de Ingeniería de Construcción. 2010
- Measuring achievement of learning organizations in construction. Engineering, Construction and Architectural Management. 215-+. 2007

Teaching

courses taught

AREN 4317 - Architectural Engineering Design
Secondary Instructor - Spring 2020
Provides a capstone experience to AREN students. Students design a modest commercial building and complete an integrated engineering design of the building systems executed for the conceptual, schematic, and design development phases. Students' teams work on structural, mechanical, electrical/lighting, and construction engineering management design. Each stage produce a professional-quality design document. Faculty and industry mentors participate in the teaching and evaluation of designs.
COEN 1830 - Special Topics
Primary Instructor - Fall 2024
Explores topics of interest in engineering. Content varies by instructor and semester. May be repeated up to 9 total credit hours.
CSCI 3002 - Fundamentals of Human Computer Interaction
Primary Instructor - Spring 2024
Introduces the practice and research of human-computer interaction, including its history, theories, the techniques of user-centered design, and the development of interactive technologies. Covers computing in society at large with respect to domains such as health, education, assistive technology, ethics, environment, and more.
CSCI 5502 - Data Mining
Primary Instructor - Spring 2024 / Fall 2024
Introduces basic data mining concepts and techniques for discovering interesting patterns hidden in large-scale data sets, focusing on issues relating to effectiveness and efficiency. Topics covered include data preprocessing, data warehouse, association, classification, clustering, and mining specific data types such as time-series, social networks, multimedia, and Web data. Same as CSCI 4502.
CVEN 3246 - Introduction to Construction
Primary Instructor - Summer 2020
Provides a broad view of concerns, activities, and objectives of people involved in construction: the owner, architect/engineer, contractor, labor and inspector. Interactive gaming situation relates these people to the construction contract, plans/specifications, estimates/bids, scheduling, law and financial management. Students with a Business School Real Estate emphasis may be considered for this course.

CVEN 3256 - Construction Equipment and Methods
Primary Instructor - Spring 2020
Integrated study of construction equipment, methods, and economics. Topics include equipment productivity, equipment selection, and construction engineering design within economic constraints. Examples include earthmoving, concrete formwork, and temporary construction.

DTSC 5301 - Data Science as a Field
Primary Instructor - Fall 2024
This course provides a general introduction to the field of Data Science. It has been designed for aspiring data scientists, content experts who work with data scientists, or anyone interested in learning about what Data Science is and what it�s used for. Weekly topics include the past, present, and future of the field; examination of the process and pitfalls of data science; the academic disciplines that both practice and make use of Data Science; collaboration between data scientists and content experts; and the practice of Data Science in the professional world. This course is part of CU Boulder�s Master�s of Science in Data Science and was collaboratively designed by both academics and industry professionals to provide learners with an insider�s perspective on this exciting, evolving, and increasingly vital discipline.

DTSC 5501 - Data Structures and Algorithms
Primary Instructor - Fall 2023 / Spring 2024 / Fall 2024
This course provides students with a fundamental introduction to data structures and the design and analysis of algorithms. It covers a range of data structures such as priority queues, hash functions, and trees alongside algorithmic design techniques such as divide and conquer, dynamic programming, and greedy algorithms. The course demonstrates applications of these concepts in a number of contexts such as the sorting of arrays, and the use of hash-tables for approximate counting. Some advanced topics, such as the data structures and algorithms used to represent and analyze spatial data, are also covered. The course ends with a brief introduction to intractability (NP-completeness) and using linear/integer programming solvers for solving optimization problems. This course cannot be applied for credit towards a graduate degree in Computer Science.

DTSC 5930 - Professional Internship
Primary Instructor - Fall 2023 / Spring 2024 / Fall 2024
This class provides a structure for DS graduate students to receive academic credit for internships with industry partners that have an academic component to them suitable for graduate-level work. Participation in the program will consist of an internship agreement between a student and an industry partner who will employ the student in a role that supports the academic goals of the internship. Instructor participation will include facilitation of mid-term and final assessments of student performance as well as support for any academic-related issues that may arise during the internship period. Recommended prerequisite: may be taken during any term following initial enrollment and participation in DS graduate programs. May be repeated up to 6 total credit hours.

VIVO

Positions

Research Areas

Research

research overview

keywords

Publications

selected publications

chapter

conference proceeding

journal article

Teaching

courses taught

Background

education and training

International Activities

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