IEEE Senior Member Grade Elevation Information Night, Networking Event with Dinner Sponsored by the IEEE Seattle Section

#tech #talk #Senior #Member #seattle #WIE





You are invited to an important event – an opportunity to attend the information session & apply for the IEEE Senior Member grade elevation and network with industry experts, IEEE Members, and Seattle Section Officers.

IEEE Senior Members are not only highly regarded within our own organization, but by technological industries and companies around the world. Senior Membership is a mark of career achievement and distinction.

You’ll also need three references from qualified IEEE Senior Members, Fellows, or Honorary Members. Your nomination by this Section/Society counts as one reference when endorsed by a qualified Senior Member, Fellow, or Honorary Member.

All IEEE members who meet the qualifications below are encouraged to attend and meet with Senior Members, Fellows, and Honorary Members. Understand the application process, obtain Senior Member references by networking, and learn more about Senior Membership. Refreshments are complimentary.

Do you qualify as a Senior Member?

1)    Candidates shall be an engineer, scientist, educator, technical executive, or originator in IEEE-designated fields (Bylaw 1-104.11)

2)    Candidates shall have been in professional practice for at least ten years

3)    Candidates shall have shown “significant performance” over a period of at least five of those years in professional practice.


For all information and the application form


Please bring copies of your detailed resume or CV, complete with full details and a strict timeline of dates, to the Event.


IEEE Senior Members Make a Difference!


  Date and Time




  • Date: 09 Apr 2024
  • Time: 05:30 PM to 06:30 PM
  • All times are (UTC-07:00) Pacific Time (US & Canada)
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  • Seattle University
  • 901 12th Ave, Seattle, WA 98122
  • Seattle, Washington
  • United States 98122
  • Building: Student Center
  • Room Number: Room #: 210

  • Contact Event Hosts
  • Co-sponsored by Seattle University Student Chapter
  • Starts 04 April 2024 12:00 AM
  • Ends 09 April 2024 06:00 PM
  • All times are (UTC-07:00) Pacific Time (US & Canada)
  • No Admission Charge


Dragos Margineantu, PhD of Boeing


Robust AI Systems: a story of unknowns


The ultimate goal of AI research is to provide the tools, techniques, and methods for building usable systems that make decisions or assist in making decisions that model and "understand" the world, gather relevant knowledge, and act responsibly. In many cases, the decisions and actions are associated with high risks, and certain assurance or robustness is required from the system that uses AI components. What are the ultimate questions that we need to answer in order to build the required runtime robustness for our systems?

We'll explore the central role that three types of unknowns play in our quest for robustness. These are the unobserved entities that need our research attention to make any assurance guarantees. First, we'll analyze the unknown observations that we need to deal with at runtime. Next, we'll explore the unknown features – the additional dimensions along which we need to reason and that are needed to rely upon at decision time. Finally, we'll discuss the unknown constraints – the unknown functions that we need to optimize against.



Dragos Margineantu is a Boeing Senior Technical Fellow and AI Chief Technologist who is the technical lead of AI research and engineering at Boeing. His interests include autonomous commercial flight, robust machine learning and decision systems, anomaly detection, modeling & reasoning under uncertainty, validation and testing of learning and decision systems, cost-sensitive, active, ensemble learning, and inverse reinforcement learning.

Dragos Margineantu was one of the pioneers in research on ensemble learning and cost-sensitive learning, and on statistical testing of learned models. At Boeing, he developed machine learning-based solutions for autonomous flight, manufacturing, airplane maintenance, airplane performance, surveillance, and security. Dragos serves and served as the Boeing principal investigator (PI) of multiple DARPA projects and chaired major AI and data science conferences. Dragos serves as the Action Editor for Special Issues for the Machine Learning Journal (MLj), edited by Springer. He co-advised graduate students at MIT and KU Leuven in Belgium, served on Canada Research Chair committees, and on NSF review panels.

In his free time, Dragos is coaching middle schoolers for Mathematics Competitions, and I am a passionate outdoor photographer. Dragos obtained his Ph.D. in Machine Learning in 2001 at Oregon State University, where his thesis advisor was Tom Dietterich.


Date:  April 9th 2024

Time:  5.30 P.M. to 6.30 P.M.
Where: Seattle University,

 Room # 210 Student Center.

  901 12th Ave, Seattle, WA 98122

             (This is an In Person Event only)

Who:  All IEEE Members who qualify for Senior Membership

Please Register for the Event