Ever wonder how engineers tackle complex real-world challenges?
Dive into the exciting world of modern engineering in this innovative one-week course. You'll learn to solve fascinating problems in mechanics, thermodynamics, and fluid dynamics using Python and MATLAB, with cutting-edge AI tools as your coding companion. No advanced math is needed – just bring your curiosity and creativity! Work on hands-on projects that matter, from analyzing motion and forces to understanding energy systems, all while building valuable skills for your future STEM career. Perfect for students eager to explore engineering through a fresh, accessible approach that combines the power of artificial intelligence with your natural problem-solving abilities.
By the end of the course, students will:
- Understand the basics of coding with MATLAB and Python for engineering applications.
- Use generative AI tools to assist in problem formulation, coding, and debugging.
- Solve core engineering problems in areas like mechanics, thermodynamics, and fluid dynamics.
- Develop computational models to visualize and analyze engineering systems.
- Gain confidence in approaching complex problems using computational tools and basic math.
2025 Pre-College SummerDATES COSTS APPLICATION DEADLINES *Apply by the early action deadline and receive a $100 discount on the program fee. |
Experiential Learning
This course combines short lectures, tutorials, and immersive hands-on activities using AI-assisted problem formulation, coding, and analysis on the following topics:
- Engineering computing and AI tools
- Mechanics: motion and forces
- Thermodynamics: energy and efficiency
- Fluid dynamics: flow and pressure
- Capstone project: solve a real-world engineering problem
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Instructor
Carlos Colosqui, PhD
Associate Professor and Undergraduate Program Director, Department of Mechanical Engineering
Affiliated Faculty, Applied Mathematics & Statistics Department
Prof. Carlos Colosqui is the undergraduate program director in mechanical engineering and affiliated faculty in The Applied Mathematics & Statistics Department. His research work combines theoretical and computational modeling with experimental studies of transport processes in engineering applications ranging from advanced manufacturing of nanomaterials to electrochemical energy storage systems. He is the recipient of multiple awards from The National Science Foundation (NSF), The Department of Energy (DOE), Office of Naval Research (ONR), and The New York State Research and Development Authority (NYSERDA). He is a senior principal investigator in the DOE Energy Research Frontier Center for Mesoscale Transport Properties (EFRC m2M), which researches batteries and advanced energy storage systems.