Best Student Data Mining Paper Runner Up in ECML/PKDD
This recognition was received at the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, for the following paper:
GridWatch: Sensor Placement and Anomaly Detection in the Electrical Grid
Bryan Hooi (ML/Stat), Dhivya Eswaran (CSD), Hyun Ah Song (MLD), Amritanshu Pandey (ECE), Marko Jereminov (ECE), Larry Pileggi (ECE), Christos Faloutsos (CSD/MLD)
http://www.ecmlpkdd2018.org/
The paper solves two related problems: (a) it gives fast algorithms to detect anomalies in power-grid networks, for a given set of voltage and current sensors placed on some nodes and edges; and (b) it shows where to put such sensors, to maximize detection probability.
