Webinar – Strategies for Managing Complex AI Systems: From Development to Deployment
AI is transforming many industries. But addressing the full cycle, from development through deployment, requires key system engineering building blocks. Without these frameworks, efforts can be costly and unsuccessful. Learn how an AI systems engineering approach can avoid implementation pitfalls in this live webinar—a preview of the upcoming live virtual course AI Strategies and Roadmap: Systems Engineering Approach to AI Development and Deployment.
In this interactive one-hour discussion, led by David Martinez, Laboratory Fellow in the Cyber Security and Information Sciences Division at MIT Lincoln Laboratory, you will:
– Deepen your understanding of end-to-end AI architecture at the systems engineering level
– Discover how a systems engineering approach can increase confidence and reduce errors in your AI implementation
– Understand how a systems engineering mindset can provide a holistic approach to your AI investment
– Acquire an overview of the latest AI-based challenges and opportunities in AI design, implementation, and deployment
Following the session, you’ll have the opportunity to ask questions in a live Q&A session. Register here.
MEET DAVID MARTINEZ
David Martinez is a Laboratory Fellow in the Cyber Security and Information Sciences Division at MIT Lincoln Laboratory and MIT Instructor. He focuses on research and technical directions in the areas of artificial intelligence (AI) and high-performance computing. Previously, Mr. Martinez served as an Associate Head in the Cyber Security and Information Sciences Division. He was also a member of Lincoln Laboratory’s Steering Committee. Mr. Martinez has held many past technical leadership roles, including Leader of the Embedded Digital Systems Group and Head of the ISR Systems and Technology Division.
Mr. Martinez also served in a leadership role as President and Chairman of Mercury Federal Systems. Prior to joining Lincoln Laboratory, he was employed as a principal research engineer at ARCO Oil and Gas Company, specializing in adaptive seismic signal processing. He received the ARCO special achievement award. He holds three U.S. patents based on his work in signal processing for seismic applications. He was elected an IEEE Fellow “for technical leadership in the development of high-performance embedded computing for real-time defense systems.” In 2008, he and his co-authors released a successful book titled High Performance Embedded Computing Handbook, which is highly referenced within the embedded computing research community.
Mr. Martinez was awarded a bachelor’s degree from New Mexico State University, an MS degree from MIT, and the EE degree jointly from MIT and the Woods Hole Oceanographic Institution in Electrical Engineering and Oceanographic Engineering. He completed an MBA from the Southern Methodist University.