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/wp-content/uploads/2018/09/10.pdf

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.

Tom Jackson and Vehbi Calayir receive award at SONIC

Tom Jackson and Vehbi Calayir received the John Bardeen Award at the StarNET SONIC review for their collaborative project with researchers at Stanford: “A Cellular Neural Network using CMOS Neurons and RRAM/PCM Synapses.” The group of Thomas Jackson, Vehbi Calayir, S. Burc Eryilmaz, Joon Sohn, Zizhen Jiang, Clare Chen, Ethan Ahn, under the direction of Professors H.-S. Philip Wong and Larry Pileggi, designed and fabricated a Cellular Neural Network chip in 65nm CMOS with deposition of RRAM at Stanford for integration of artificial synapses.

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