Meeting Thursday, March 23, 2017 at Hotel Roanoke. (Note new location)
A Broad Overview of Deep Learning and its Applications.
by David L. Livingston, Ph.D., P.E.
Professor of Electrical and Computer Engineering
Virginia Military Institute
Deep neural networks (DNNs) trained using deep learning methods are considered the state-of-the-art in current artificial intelligence research and development. DNNs are the bases of many applications including the voice recognition systems on Android phones and face recognition on Facebook. Google, Facebook, Microsoft, Amazon, ... all have active research programs in deep learning.
In this presentation, we’ll discuss the history of deep learning, the basic methods used to train deep neural networks, and show that there are a number of easily-learned tools that make the process of designing, training, and applying deep networks accessible to engineers and computer scientists. We’ll also examine a sample of the many interesting applications of deep learning to solving difficult problems in weak artificial intelligence and discuss its potential in the development of strong artificial intelligence.
Dave Livingston was born and raised in Hampton Roads and earned a B.S.E., M.E., and Ph.D. in electrical engineering from Old Dominion University in Norfolk, Virginia. He started his professional career at IBM Endicott where he worked as a staff engineer participating in the design of the IBM PC-XT/370 and IBM PC-AT/370. Dave went back to academics as an Assistant Professor of Electrical and Computer Engineering at Old Dominion University and as a Professor and Department Head of Electrical and Electronics Engineering Technology at Virginia Western Community College. He joined the Electrical and Computer Engineering Department at Virginia Military Institute in 1999, where he is currently a Professor of ECE. His research interests include computational intelligence−particularly neural networks and reinforcement learning, embedded systems, and robotics.
Dave, currently a Senior Member, joined the Virginia Mountain Section of the IEEE in the early 90’s and has served in every officer position in the VMS and the VMS Computer, Controls, and Industrial Electronics Society. He is a member of Eta Kappa Nu, Tau Beta Pi, and Phi Kappa Phi; and was awarded the IEEE Millennium Medal in 2000.
To satisfy his artistic needs, Dave plays bass guitar in the VMI Jurassic-rock quintet: The Coprolite Band.
Thursday, March 23, 2017
Social: 6:30 PM
Dinner: 6:45 PM
Presentation: 7:30 PM
Members and Guests: $20, Students $10
Dinner will be a buffet so dietary restrictions will not be needed for this meeting.
110 Shenandoah Ave
Roanoke VA 24016
Directions to Hotel Roanoke:
Take Exit 143 0nto I-581 South
Take Downtown Exit #5
Stay in right lane of exit
At stop sign, turn right onto Wells Ave,
make first left at flags into Semi-circle to unload passengers to enter Convention Center glass doors,
drive back to bus parking,
Traveling West on 460:
460 West becomes Orange Ave.
Make left turn onto Williamson Road.
Make right onto Wells Ave past Civic Center.
Make first left to park or second left at flags into Semi-circle to unload passengers.
Reservations: Please RSVP by noon, Monday March 20, 2017. Please specify the number of attendees. Please RSVP to George Williams, Vice-Chairman, at email@example.com.
Credit: One continuing education credit will be awarded for attending this presentation.
Virginia Mountain Section (VMS) of the IEEE has been serving
members in the Southwest corner of the Commonwealth of Virginia
currently have two Student Branches in local universities
the VMS Consultants Network Affinity Group.
The purpose of this Affinity Group is to share information concerning
consulting opportunities, and to make a list of consultants
and their areas of expertise available to potential employers.
Anyone wishing to be added to this group, or desiring more information
should contact David Livingston, firstname.lastname@example.org.
about our Section, the Chapters, and material of interest
to our members may be found by selecting items in the left
column of this page.