Teaching

In this course, we study models for analyzing multimodal transportation systems. Every problem pertaining to transportation planning, operations, and design starts with creating a model that presents an abstraction of the real-world settings. We look at a broad view of different transportation models while focusing on some of those in detail.

• In-person component on Transportation Design:
  • Exposure to models and techniques for Transportation Design
  • Learning state-of-the-art software (Open Road Designer by Bentley) used in infrastructure design
  • Examining and solving typical transportation engineering problems
• Self-paced modules: Linear regression, discrete choice, traffic assignment, and traffic flow theory

Application areas include urban transportation planning, alternative evaluation, and optimization of traffic operations.

This course focuses on the major aspects of highway engineering including traffic operations and safety, transportation planning and economics, and geometric design and highway materials. It also addresses concepts of highway management and highway maintenance planning.

The course is broadly structured in three parts:

• Planning: Working on a large geographic scale, thinking up to 30 years in the future to develop general policies
• Operations: Working at the scale of individual roadways or corridors to quantify how easily people can travel
• Design: Addressing the specifics of how to implement a plan which is effective operationally

This course introduces the concepts of probability and statistics, and analytical methods for handling random phenomena. Topics covered include:

• Statistical inference from observational data
• Confidence intervals and hypothesis testing
• Regression and correlation analyses
• Quality assurance and acceptance testing

Upon successfully completing CAEE304, students will be familiar with the fundamentals of probabilistic modeling, including elementary combinatorics, facility with discrete and continuous distributions, and their application to engineering problems.

This course covers the basics of MATLAB programming language and its use in solving problems in:

• Linear algebra
• Matrix theory
• Manipulation of polynomials
• Interpolation, differentiation, and integration

Computational/numerical methods for the solution of mathematical problems are presented. The purpose of this course is to ensure proficiency in the application of math techniques in the solution of engineering problems commonly encountered by CAEE engineers.

This course introduces students to the transportation design process through a series of comprehensive transportation design principles and projects. Emphasis is placed on:

• Utilization of existing facilities
• Creation of efficient new facilities through transportation systems management techniques

Energy, environment, mobility and community impacts are considered as measures of effectiveness in the design process. Students also learn state-of-the-art software used in infrastructure design such as Open Road Designer.

This graduate-level course introduces emerging technologies within the broad scope of civil and architectural engineering systems. The core objective is to situate understanding of these technologies within the broad contexts of issues shaping the future of civil engineering systems.

We study topics under three different themes:

• Infrastructure and smart cities
• Modeling techniques for emerging technologies
• 21st century societal goals of sustainability, resiliency, and social justice

This course is organized as a hybrid lecture and seminar style course, structured around discussions, reading, writing and other critical engagement with the related topics.

This course focuses on advanced modeling techniques for transportation systems. It builds upon the concepts introduced in CIEN 785 and delves deeper into complex transportation modeling scenarios.