RESEARCH TOPICS

FOG COMPUTING
MACHINE LEARNING
BLOCKCHAIN
DATA SECURITY

FOG COMPUTING

Fog computing for real time monitoring and distributed microgrid resilience. We will study the role of fog computing for the smart energy system; and gain understanding on how fog computing can significantly improve the performance of the energy system.

MACHINE LEARNING

Machine learning and deep learning for energy forecasting. Precise forecasting is very important for the stability of the future energy systems. We will study predictive analytics techniques for power stability, including regression, neural networks and other machine learning approaches for real-time and historical analytics. In addition, the renewable energy forecasting will be an important problem in this topic.

BLOCKCHAIN

Blockchain solutions to created decentralized applications to allow local and community level energy trading. Creating systems to incentivize and improve adherence for households to participate in a smart community neighborhood.

DATA SECURITY

Data security and privacy measure using anonymization, differential privacy to protect sensitive information about households. Smart Meter, appliance usage, micro production and consumption data from each household could reveal detail lifestyle information about individuals and households. It is necessary that proper security mechanisms are maintained to in any form of data storage, transfer or communication. Additionally, privacy preserving mechanism also needs to be established to balance data utility and data privacy.