Summary
David Demaris is a multidisciplinary engineer and consultant with over three decades of experience spanning microprocessor and VLSI design, electronic design automation, and a decade-plus applying machine learning to lithography and postprocessing. He now focuses on software development, NLP, AI and machine learning for startups and nonprofits, blending production-grade engineering with research insights from his Ph.D. in neurodynamics and machine vision. At IBM he led teams that brought data mining and signal processing into VLSI workflows and developed SMO-driven lithography optimization, and he continues to translate advanced information-theoretic methods (e.g., transfer/control entropy) into practical analysis and tooling. Equally at home in creative practice, he composes and designs audio/interactive theater work and built an open neural-field ML toolkit (oscilite) that modernizes his dissertation code. This combination of deep systems experience, applied research, and artistic practice gives him a rare ability to bridge noisy real-world data, human-centered interaction, and principled ML research.
12 years of coding experience
28 years of employment as a software developer
Ph.D., Engineering, Ph.D., Engineering at The University of Texas at Austin
University of Illinois Urbana-Champaign