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Efficient, Explainable AI for Practical Use-cases

An Electronic Design-hosted webinar sponsored by Renesas

Originally broadcast on October 25, 2023. Now available On Demand.

Sponsor: Renesas

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AI is very real and transforming every aspect of our lives and designers are already building AI / ML capabilities into a broad range of industrial, consumer and automotive systems. We’re going to talk about efficient, explainable AI for practical use-cases that will really add value when you think about adding AI and machine learning to an application. AI is often equated to a model but for most practical applications, AI is a lot more than building a model and generally, only about 5% of project costs are devoted to model development. So what else should is there to consider?

This presentation will cover:

  • The 3 key considerations to pick the right tool
    • Data sensitivity and sensor(s) with optimal mounting location(s)
    • Managing resource-constrained devices for cost optimization
    • Deterministic or black box approach, need to determine how your model will behave in the field
  • The many faces of Edge AI
  • Why Deep Learning isn't always the right answer
  • Deployment examples in a variety of non-visual applications


Mo Dogar | Vice President, MCU Business Development | Renesas Electronics

Mr. Dogar is head of Global Business Development and Technology Ecosystem for Renesas Electronics, responsible for promotion and business expansion of the complete Microcontroller & Microprocessor portfolio and other key products. Mohammed is instrumental in driving the ‘Embedded Processing’ portfolio's multi-billion dollar business growth including ecosystem partnerships, and devising effective GTM strategies worldwide. Mr. Dogar helps provide the vision and thought leadership behind product and solution roadmap for smart society and the evolving AIoT economy. Additionally, responsible for the global ‘AIOT Centre of Excellence’, leading the SW, tools and new AI/ML solution developments related to ‘Voice’, ‘Machine Vision’ and ‘Real-time Analytics’.

Mr. Dogar studied Electronics & Information Engineering at the University of Huddersfield, UK and received Project Management qualifications linked to an MBA from the Open University in the UK. He has worked for a number of semiconductor, industrial and technology companies including NEC Electronics and Rockwell Automation.  He subsequently joined Renesas and has worked in various roles including Engineering, Applications, Marketing and Business Development. 

Jeff Sieracki | Director of Engineering, AI Center of Excellence | Renesas Electronics

Dr. Jeff Sieracki is an extremely applied mathematician who has focused his career on the intersection of modern signal processing and machine learning. Former co-founder and CTO of Reality AI, he joined Renesas as part of an acquisition in 2022 and is now Head of AI Engineering at the Renesas AIoT Center of Excellence. His work spans signal and sensing problems in commercial industry, medical devices, and DoD applications. He has started, built, and exited three companies, one in each of those application areas.

Jeff has been awarded over 50 technology patents. He holds a PhD in Applied Mathematics and Scientific Computing and was a founding member of the Norbert Weiner Center for Harmonic Analysis and Applications at the University of Maryland, College Park.

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