Teaching

My job is to help students build the ability to think critically, and then to prove they can apply that thinking to a real problem. Every course teaches a usable technical skill, such as coding an optimization model in Python, statistical analysis or energy-system modeling, and then has students apply it to real data in a team project written to the standard of an IISE conference paper.

I chair the IMSE Undergraduate Curriculum Committee and serve on the College of Engineering and REE curriculum committees. That work centers on ABET accreditation and on preparing students for the FE exam and professional licensure, while making sure they also leave with modern skills: programming, working with data, and using AI honestly. As a licensed Professional Engineer, I hold students to the standard the profession will: engineers are trusted with systems that, when they fail, fail people.

Courses

Each course page lists its key concepts and the free tools and readings it uses, open to anyone.

• Energy Systems Modeling

  REE 4301 / IE 5300 · 2026–

  Building mathematical models of real energy systems, from demand and generation to networks, storage and material supply chains.

  4 interactive models

• Operations Research I

  IE 3315 · 2023–

  The major deterministic techniques of operations research, and how to use them to make better decisions.

  3 worked examples

• Advanced Operations Research

  IE 5301 · 2023–

  A graduate survey of deterministic and stochastic methods for modeling and decision-making.

  5 worked examples

  1 interactive models

• Engineering Probability

  IE 3301 · 2021–

  Probability and statistics applied to problems in engineering, operations and everyday life.

  3 worked examples

Programs

• Engineering for One Planet (EOP) Institutionalization Program — PI on a Lemelson Foundation grant through which more than 100 UTA faculty have built sustainability outcomes into the engineering courses they already teach. Published at ASEE each year since 2023.
• DOD next-generation power systems workforce — Co-PI on a DOD-funded effort preparing engineers to design advanced electrical power systems that combine multiple sources, storage, intelligent control and transient loads.
• NSF Research Experiences for Teachers (RET) Sites — Faculty mentor on both of UTA's RET Sites, which bring college-level engineering research into K–12 classrooms, and Co-PI on the 2025–2030 Site.
• Lean manufacturing with Lego — A classroom module in which students learn industrial engineering concepts by assembling Lego workstations.
• Planet Texas 2050 — Developed curriculum for UT Austin's grand-challenge initiative as a Scientist in Residence.

How I teach

• Set expectations with total clarity. Students know exactly which concepts each class covers, and how the slides, textbook, homework and exams fit together.
• Teach a hard skill, then make them use it. Each course builds a technical skill and applies it to a real dataset or a real client through a team project.
• Assess for growth. The project runs in graded milestones, so feedback arrives while it can still change the outcome.
• Teach what is current. High-impact practices, chiefly project-based learning, built on real-world examples and applications, and on the latest knowledge from my open textbook and from systems actually built and run.
• Build people skills deliberately. Team projects require communication, scheduling and playing to each other's strengths, which are the actual conditions of engineering work.

Earlier materials

Worked examples from before UT Arlington, written for students and still free to use:

• Monocentric city modeling
• Light rail in a model city
• Austin land use
• Selective laser sintering: wind-powered tops