SPRING 2024 Senior Design Topics
Professor: Erik Grimmelmann (Section L)
This course provides a theoretical and hands-on introduction to the modeling and analysis of complex systems. We’ll be considering both analytical and stochastic approaches to modeling.
Among the topics we’ll cover will be: brief reviews of the relevant topics in math and numerical analysis, discrete time models, continuous time models, bifurcations, chaos theory. We will examine the modeling of a number of complex systems including: the Game of Life, turing patterns in animal skins, Covid-19 epidemiology, forest fire propagation, stock and option pricing, vehicular traffic jams, housing segregation, protein synthesis.
This course is the first in a two-course sequence. In the following semester, students enroll in CSc 59867 – Senior Project II – in which they will implement small group projects related to the modeling and analysis of complex systems.
Instructor: Seta Bogosyan (Section 3BC)
Many applications and services in future societies will depend more and more on autonomous vehicles (AVs) for different applications, from transportation, factory automation, and urban logistics, to smart farming/agriculture and disaster management.
1. First part of this senior design course will equip students with a general and practice-oriented foundation in autonomous vehicle (AV) control, focusing on the three layers: perception & localization, motion & behavioral planning, trajectory tracking control.
2. Students will be introduced to general modeling and computer-control basics, as well as, algorithms that are most commonly used in the practice of AV control for each layer of autonomy, with practical examples in-class and weekly assignments.
3. Students will also learn about the most popular AV control, simulation, and animation platforms; i.e. ROS2, Carla, Gazebo&RViz through lectures, examples, and assignments.
The senior design projects will target a single layer of AV control, or may combine multiple or all layers. Students will develop algorithms relevant for the aimed performance at a given layer for ROS2, and use Python or C languages for the programming. The performance of the algorithm will be demonstrated on an animation platform (Carla, Gazebo etc.).
Instructor: Christian Lim (Section E)
Conversational AI = This Capstone section will introduce students to a conversational AI that is enabled through the recent development of ChatGPT. Topics include (1) a brief introduction to Deep Learning (DL), (2) popular DL algorithms such as CNN, GNN, and Transformer, and (3) DL systems (e.g., ChatGPT) with a focus on PyTorch/TensorFlow. After inspecting these DL frameworks, students are expected to propose, design and implement conversational AI of their choice in the second semester (CSc59867).
Last Updated: 10/19/2023 09:55