Episode
Quantum Architecture, QAOA, and Cancer Biomarkers | Fred Chong
- Podcast
- 632nm
- Published
- May 19, 2026
- Duration seconds
- 7179
- Processing state
not_requested- Canonical source
- https://share.transistor.fm/s/3af711d1
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Summary
Are quantum computers changing the way we discover cancer treatments? In this episode, Misha and Yudong spoke with Fred Chong, Seymour Goodman Professor at the University of Chicago, about the future of quantum computer architecture and how quantum algorithms could eventually help solve real-world problems in medicine, optimization, and scientific computing. Chong explains the transition from the NISQ era toward fault-tolerant quantum computing, why hardware-aware software design remains essential, and how compiler architectures, error correction, and quantum system design all interact across the full computing stack. The conversation explores the challenges of building scalable quantum machines, the tradeoffs between superconducting qubits, trapped ions, and neutral atoms, and why many quantum systems may ultimately function as specialized accelerators alongside classical computers. We also discuss quantum optimization algorithms like QAOA and how Chong’s group is applying them to cancer biomarker discovery and treatment prediction. By analyzing complex multimodal biological data, including DNA, mRNA, and pathology imaging, these methods aim to uncover patterns that are difficult for conventional machine learning systems to identify without overfitting. Along the way, Fred shares stories from the early days of supercomputing at Thinking Machines, the origins of his quantum research career, the founding of Super.tech, and his perspective on where quantum computing is genuinely making progress versus where hype still dominates the conversation. Topics include quantum computing, QAOA, fault-tolerant quantum computing, quantum error correction, quantum compilers, NISQ systems, neutral atoms, superconducting qubits, quantum architecture, cancer biomarkers, biomedical optim…