Dr. Erik Blasch

Biography:

Respected international senior material leader and multimodal fusionist innovating design of systems using information processing, space-aware tracking, industrial avionics, and human factors designs as: 

(1) documented in 12 books, 62 patents, 61 tutorials, 164 journal, 600+ peer-reviewed, and 500+ conference papers; 

(2) recognized with 11 named awards, 50+ annual awards, and 21 medals; and 

(3) deployed techniques to two enterprise systems, with 8 licensed products, and 12 programs of record. 

Technical lead managing diverse teams of 10-50 people for over 26 years, influencing $3B in funding. 

Experienced engineer with a demonstrated history of working in government administration, military operations, academic settings, and industrial innovation. Known for developments and patents in "Level 5 information fusion" for human-machine teaming, "Multi-Attribute AI Scorecard Table (MAST)" to measure trust, evidential and information filtering tracking for "Pattern of Life" analysis, as well concepts in the books on image fusion, deep learning for synthetic aperture radar, blockchain, and data fusion systems. Other roles include military officer, academic professor, professional society president, and entrepreneur. 

Skilled in mathematical modeling, computer science, software development, systems engineering, and test/evaluation. 

Title:  Emerging Trends in Trusted AI/ML Edge-Based Fusion for the Metaverse 

Abstract:  This talk will focus on emerging trends, opportunities and concerns for AI/ML data fusion at scale for the metaverse. The metaverse will be inundated with sensors, signals, data, and models that need to be processed at scale. Emerging trends to reduce the complexity include AI/ML methods, decentralized architectures, and digital twins. The research opportunities include coordinated physics-based and human-derived information fusion (PHIF), enhanced situation awareness with digital engineering, and signal processing to orchestrate smart cities for a clean environment. The challenges and concerns among these emerging opportunities include measurement of trust for human-machine systems, security with interconnected wireless systems, privacy of data and models, and fairness of the real, augmented and generated data. The overview from the metaverse concepts will be discussed to encourage solutions to minimize the complexity, operate at scale, and foster engineering solutions for society enhancement.