Oct 29th, 2025 NYC Quantum Computing In Person Meetup (w/teams option)

Title: Beyond the Black Box: Transparent, Efficient AI with Tensor Networks
Abstract:
The journey of Multiverse Computing began with applying quantum computing methods to finance, where tensor networks emerged as a natural bridge between quantum physics and data-driven modeling. We soon discovered that the same tensor network formalisms could be repurposed to address key challenges in machine learning. In this talk, we’ll explore how these methods enable neural network compression via low-rank tensor factorizations, improve interpretability through structured representations, and support the design of more scalable and efficient AI architectures, highlighting how techniques rooted in quantum science translate into practical breakthroughs for modern AI.
Bios:
Samuel Palmer is a leading expert at the intersection of quantitative finance, quantum computing, and artificial intelligence. As Director of Financial Engineering at Multiverse Computing, he has spearheaded the design and delivery of quantum and quantum-inspired solutions for leading financial institutions, helping bridge advanced research with real-world financial applications.
Samuel has published widely on quantum portfolio optimization, tensor neural networks, and payment network algorithms. His recent work includes patents and papers on quantum algorithms for finance, explainable AI with tensor networks, and differentially private synthetic data. He is a frequent speaker and advocate for making quantum computing practical today and enhancing machine learning with tensor networks.

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