Dine and Learn: Machine Learning and Neural Networks


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The Denver Section would like to invite you to join us for the latest presentation in our Dine and Learn series!

Come join your fellow IEEE members and local engineers for a fun filled evening of appetizers, networking, and dinner, while we discover exciting new innovations in technology. Once a month one of your local Denver IEEE Societies will host the event and bring in a unique speaker related to their field to present. This provides you, our members, with a unique opportunity to explore and learn about exciting new technologies being developed around you. Early on in the evening you’ll also have ample opportunity to mingle with your fellow engineers and colleagues delving into a broad range of technical expertise.

We will provide the appetizers, but dinner is at your own expense. Dinner for students is free.

If there is a specific speaker or topic you find interesting please let us know and we will try to accommodate it in the schedule.

Upcoming presentations:

July - No Event

August - TBD 

  Date and Time




  • 10633 Westminster Blvd
  • #900
  • Westminster, Colorado
  • United States 80020
  • Building: Rock Bottom Brewery
  • Room Number: in the "Promenade Room"
  • Click here for Map

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  • Registration closed


Ron Kneusel of Harris Corporation


Machine Learning and Neural Networks

Artificial intelligence has finally arrived, or has it? Regardless of the ultimate answer to that question, it is clear that something has changed as is evident by the advent of systems like Siri, Cortana, and Alexa to say nothing of self-driving cars, automatic face and person identification from imagery and the thrashing of the world's best Go player.

So, what is behind all of these new systems? The answer is “deep learning” by which we really mean “'big' neural networks”. Of course, if your memory stretches back far enough, you will know that neural networks are really nothing new which begs the question: if neural networks are now the answer but were not in the past, what has changed? We will attempt to answer that question in this presentation while also giving an overview of the current state of the technology. Hopefully, some of the excitement of this rapidly growing field will rub off and inspire listeners to dig deeper. The number of potential applications for deep learning is truly vast and the more people know about it the easier it will be for those potential application areas to be uncovered.

Specifically, we will discuss the essence of what machine learning and neural networks are, what is exciting about new approaches to neural networks, particularly in the context of object detection in imagery, and what the networks are actually doing to make what was previously believed to be impossible possible.


Ronald Kneusel holds a PhD in Computer Science from the University of Colorado, Boulder and a Masters degree in Physics from Michigan State University.  Ron's dissertation research focused on the interface between machine learning and human perception of images developing an improved approach for presenting classifier output to human observers to minimize the negative effects of classifier errors.

Ron worked towards a PhD in Biophysics at the Medical College of Wisconsin where he conducted early research in functional magnetic resonance imaging (fMRI). Ron also participated in outcomes-based breast cancer research with the Dept of Internal Medicine at the Medical College of Wisconsin. Ron worked with Bolder Systems, Boulder, CO, to develop multiple medical device prototypes including the first commercial 3D breast ultrasound scanner. Ron was a co-founder of Imagen Technologies which applies advanced machine learning algorithms to medical imagery.

Ron is currently a Senior Data Scientist at Harris Corporation where he develops custom software and machine learning algorithms for remote sensing applications.

Ron Kneusel of Harris Corporation


Machine Learning and Neural Networks



6:00 - 6:15 Registration and Appetizers

6:00 - 7:15 Dinner and Networking

7:30 - 9:00 Presentation

IEEE ---- Denver Section