Yi Ding

Assistant Professor at UT Dallas

Course Info

Instructor: Yi Ding

Office: ECSS 4.703

Office hours: 4:30 pm - 5:30 pm, Tuesday

Email: yi.ding@utdallas.edu

Lecture: 5:30 pm - 6:45 pm, Tuesday/Thursday

Location: FN 2.102

Course Description

Empowered by rich data collected from various infrastructures in our cities and machine learning techniques, our cities are becoming “smarter”. In this course, we discuss how data science and other computer science technologies are used to innovate our cities. We cover topics such as urban sensing, data-driven modeling and analytics for smart city services, data-driven decision-making, and also some speical and novel topics like environment, LLM, privacy, and computational social science. We will also use Singapore as an example to show how these technologies are adopted in a modern city. Students are expected to (i) read and present research papers from top conferences, (ii) participate in discussions of the papers, and (iii) design, implement, and present their ideas for the final class project.

Course Learning Objectives

By the end of this course, you will be able to

  1. Understand the basic principle underlying data science and related computer science technologies (e.g., IoT, Cyber-Physical Systems) for smart cities;
  2. Explain the state-of-the-art research in this area;
  3. Demonstrate ideas for smart cities;
  4. Implement ideas based on real-world data using tools including but not limited to data analytics, machine learning, statistics, data visualization, etc.

Prerequisites

CS 1336 and (STAT 3355 or CS 4375) OR other equivalent courses.

Required Texts

No books are required. All the materials will be online.

Grading (Tentative)

Participation: 10%
Reading summary: 25%
Topic presentations: 15%
Class projects: 50% (10% for Proposal Reports, 10% for Proposal Presentation, 20% for Final Reports, 10% for Final Presentation)

Course Schedule (Tentative)

W1: Course Introduction & Guidance on Paper Reading and Presentation (08/22, 08/24)
  • Smart cities study in general
  • Smart cities under the framework of Cyber-Physical Systems
  • IoT and CPS
W2: Data-Driven Smart Cities: Sensing (08/29, 08/31)


W3: Data-Driven Smart Cities: Prediction & Introduction on Final Project (09/05, 09/07)


W4: Data-Driven Smart Cities: Decision-Making (09/12, 09/14)


W5: Proposal Presentation (9/19, 9/21)
W6: Fundamental Topic: Localization and Navigation (09/26, 09/28)


W7: Fundamental Topic: Transportation (10/03, 10/05)


W8: Fundamental Topic: Privacy and Security (10/10, 10/12)


W9: Special Topic: Climate and Environment (10/17, 10/19)


W10: Special Topic: LLM for Smart Cities (10/24, 10/26)


W11: Special Topic: Human System Synergy (10/31, 11/02)


W12: Special Topic: Computational Social Science (11/07, 11/09)


W13: Smart City in the Real World: Singapore (11/14, 11/16)


W14 (No Classes): Fall Break and Thanksgiving (11/21, 11/23)
W15: Emerging Technologies and Applications (11/28, 11/30)
W16: Project Presentation (12/05, 12/07)

Additional Readings