The goal of SCAI lab is to boost smart city development with the power of artificial intelligence, and to train high-quality, world-class academic citizens.
Our comprehensive mission is to work on advanced and 🔥 projects with a leaning towards two of the major components of smart cities: intelligent transportation systems and smart energy systems (especially smart power grids) with deep learning techniques.
Recent years have witnessed the advent and prevalence of deep learning, which has provoked a storm in intelligent transportation systems. We work on data-driven intelligent transportation system applications, to name a few, traffic data analysis/cleaning/augmentation, traffic flow/speed/time estimation/prediction, traffic congestion/risk prediction, traffic sign control.
Due to the complexities and uncertainties of smart grids, deep learning techniques represent some of the enabling technologies for their future development and success with the high volume of information being collected. We work on demand forecasting/response, power stability assessment, fault/cyber-attack detections, and microgrid management.
We are always looking for hard-working, smart and driven students that are excited pushing forward smart city development with artificial intelligence. If you are a prospective postdoc, PhD student, or RA, read our application document. If you are affiliated with SUSTech, feel free to visit me or (junior and senior undergraduates) collaborate with me on your innovation projects. If you are an undergraduate, master, or PhD student from other institutes, I welcome you to visit the lab and exchange knowledge.
Ms. Xiexin Zou; Research Assistant 2019-2020; Next hop: PhD at PolyU, Hong Kong.
Ms. Ziwei Wang; Research Assistant 2019-2020; Next hop: PhD at UTS, Australia.