Teaching

12-212: Statics (FA14-present)

This undergraduate course concerns forces acting on rigid bodies at rest. The subject of statics is your first full exposure to a required engineering mechanics course, in which you seek to develop expertise in solving these problems. It is a direct prerequisite for several required courses (Solid Mechanics, Fluid Mechanics, and Soil Mechanics) and for electives. The foundation provided in this course is important for your academic progress and for your career preparation, and the syllabus is designed to help you achieve that mastery. The topics include: introduction to vector mechanics; equivalent systems of forces; equilibrium of rigid bodies; free body diagram; reactions; distributed forces, hydrostatic forces, effective forces, centroids; applications to simple statically determinate trusses, beams, frames, cables, and other physical systems; friction.

 

12-761: Sensing and Data Mining for Smart Structures and Systems (SP16-present)

This course is a AIS graduate course where students will learn about smart monitoring system for applications in physical structures and systems. Such monitoring systems enable us to understand the performance of the physical systems and diagnose/prognose their critical status using the technologies in cyber systems, such as sensor network and data analytics. These cyber-physical systems ensure the safety and functionality of the monitored physical systems. Examples include but not limited to structural health monitoring, traffic monitoring, water/air quality sensing, occupant monitoring, etc. The course will include lectures that provide theoretical background on data acquisition and analysis using both empirical and analytical approaches for various physical systems with an emphasis on the underlying physical interpretations and their practical usage through examples and applications.

 

12-734: Structural Health Monitoring (SP13-SP15)

Structural health monitoring system, which enables us to automatically diagnose structural damage, is important to ensure safe and functional built environment. This graduate course provides theoretical background on damage diagnosis algorithms using model-based and data-based methods for civil structures with an emphasis on the underlying physical interpretations and their practical usage. The methods include modal analysis, time-series modeling, Gaussian mixture modeling, hypothesis testing, frequency analysis, and various classification techniques. The course is lecture-based with 3 assignments and a project. Students have an opportunity through a class project to explore various damage diagnosis algorithms, choose one to implement, present your work to the class, and be peer-reviewed.

 

12-742: Data Mining in Infrastructure (SP13-SP15)

Data mining is a process to extract patterns from large data sets to discover useful knowledge. With rapid developments in sensing, computation, and communication systems, we are constantly inundated by large amount of data, and the need to efficiently process them is growing in many fields including science, engineering, business, medicine, etc. Data mining uses tools from statistics, machine learning, artificial intelligence, and data management. This graduate course introduces fundamental concepts of data mining and provide an overview of various techniques. Students have an opportunity to apply these techniques to several engineering examples.

 

Back to Top