Remote Ph.D. Dissertation Defense: Heidi Komkov

Friday, May 14, 2021
1:00 p.m.
https://zoom.us/j/6179028404
Maria Hoo
301 405 3681
mch@umd.edu

ANNOUNCEMENT:  Remote Ph.D. Dissertation Defense

 

Name: Heidi Komkov

 

Committee members: 

Professor Daniel Lathrop (Chair)

Professor Timothy Horiuchi  

Professor Pamela Abshire

Professor Brian Beaudoin

Professor Timothy Koeth 

Professor Vedran Lekic  (Dean's representative) 

 

Date/Time: Friday, May 14th, 2021 at 1PM

 

Location: https://zoom.us/j/6179028404

 

Title:  Reservoir Computing with Boolean Logic Network Circuits 

 

Abstract: To push the frontiers of machine learning, completely new computing architectures must be explored which efficiently use hardware resources. We test an unconventional use of digital logic gate circuits for reservoir computing, a machine learning algorithm that is used for rapid time series processing. In our approach, logic gates are configured into networks that can exhibit complex dynamics. Rather than the gates explicitly computing pre-programmed instructions, they are used collectively as a dynamical system that transforms input data into a higher dimensional representation. We probe the dynamics of such circuits using discrete components on a circuit board as well as an FPGA implementation. We show favorable machine learning performance, including radiofrequency classification accuracy comparable to a state of the art convolutional neural network with a fraction of the trainable parameters. Finally, we discuss the design and fabrication of a reservoir computing ASIC for high-speed time series processing.


 

 

Audience: Graduate  Faculty 

remind we with google calendar

 

May 2021

SU MO TU WE TH FR SA
25 26 27 28 29 30 1
2 3 4 5 6 7 8
9 10 11 12 13 14 15
16 17 18 19 20 21 22
23 24 25 26 27 28 29
30 31 1 2 3 4 5
Submit an Event