My research focuses on leveraging artificial intelligence (AI) to enhance teaching, learning, and assessment in STEM education. By integrating AI-driven tools such as sentiment analysis, grading assistants, and concept inventory analysis, my work aims to improve both student engagement and instructional efficiency. Recent projects include developing experiential learning activities in aerospace engineering and expanding AI applications in computer science education. I am particularly interested in the intersection of AI, pedagogy, and experiential learning to address challenges in education and foster innovation in academic environments.
keywords
Generative AI
Teaching
courses taught
ASEN 1030 - Introduction to Computing for Aerospace Engineering
Primary Instructor
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Fall 2025
Develop a foundational understanding of computational thinking required to approach engineering challenges with systematic problem-solving skills. By the end of this class, students will be able to apply computational thinking principles to design, implement, and debug programs using a high-level programming language. Additionally, students will demonstrate proficiency in fundamental programming concepts, including variables, control structures, arrays, and functions, while also showcasing the ability to analyze problems, decompose them into smaller tasks, and devise algorithmic solutions.
ASEN 2001 - Aerospace 1: Introduction to Statics, Structures, and Materials
Primary Instructor
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Fall 2018
Introduces models and analytical/numerical methods for statics and structural analysis. Topics include force/moment equilibrium, truss analysis, beam theory, stress/strain, failure criteria, and structural design. Matlab proficiency required.
ASEN 2002 - Aerospace 2: Introduction to Thermodynamics and Aerodynamics
Primary Instructor
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Fall 2018 / Fall 2019 / Fall 2020 / Fall 2021
Introduces the fundamental principles and concepts of thermodynamics and fluid dynamic systems. Emphasizes the synthesis of basic science (physics), mathematics and experimental methods that form the basis for quantitative and qualitative analyses of general aerospace technology systems. Proficiency in Matlab required.
ASEN 2003 - Aerospace 3: Introduction to Dynamics and Systems
Primary Instructor
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Spring 2019 / Spring 2020 / Spring 2021 / Spring 2022
Introduces the principles of particle and planar rigid body dynamics, systems, and controls. Topics include kinematics, kinetics, momentum and energy methods, system modeling, and simple feedback control. Class includes experimental and design laboratory exercises for aerospace applications of dynamic principles.
ASEN 2802 - Aerospace Sciences Lab I
Primary Instructor
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Fall 2022 / Spring 2023 / Fall 2023 / Fall 2024 / Spring 2025
Provides an introductory laboratory experience in aerospace sciences, with a focus on statics, structural mechanics, thermodynamics, and aerodynamics. Emphasizes model-based design, experimental data collection, and interpretation of experimental data.
ASEN 2803 - Dynamics and Controls Lab
Primary Instructor
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Spring 2023 / Summer 2023 / Summer 2024 / Summer 2025
Experimental and design laboratory exercises for aerospace applications of dynamics, systems, and controls principles.
ASEN 4018 - Senior Projects 1: Design Synthesis
Primary Instructor
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Fall 2023 / Fall 2025
Focuses on the synthesis of technical knowledge, project management, design process, leadership, and communications within a team environment. Students progress through the design process beginning with requirements development, then preliminary design and culminating with critical design. Offered fall only.
ASEN 4028 - Senior Projects 2: Design Practicum
Secondary Instructor
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Spring 2024 / Spring 2025 / Spring 2026
Focuses on the fabrication, integration, verification and validation of designs produced in ASEN 4018. Students work within the same teams from ASEN 4018. Offered spring only.
CSCA 5112 - Introduction to Generative AI
Primary Instructor
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Spring 2026
This course introduces the core concepts and architectures behind generative AI, including GANs, VAEs, diffusion models, and transformers. Students will explore how generative models produce text, images, and other outputs, and will gain foundational understanding of prompt design, and common limitations such as hallucinations. The course also includes an overview of AI literacy to support responsible use and prepares learners for applied work in generative AI systems.
GEEN 1400 - Engineering Projects
Primary Instructor
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Spring 2021 / Spring 2024
First-year students solve real-world engineering design problems in interdisciplinary teams. Design projects vary by section. Curriculum focuses on iterative design process, teamwork and team dynamics, supporting design with testing and analysis, and technical writing. Completed projects are exhibited at an end-of-semester design expo. Students responsible for contributing towards their design project budget (approximately $75). Degree credit not granted for this course and ASTR 2500, ASEN 1400, ASEN 1403 and ECEN 1400.
