Quantum Readiness and Investment Signaling in Early-Stage Startups Using NLP and Evidence Scoring

This project builds a reproducible Python framework to evaluate how quantum startups signal technical readiness and commercialization viability to investors. Using NLP and structured evidence extraction from pitch decks/websites/press releases, the intern will classify claims (hardware, error correction, benchmarking, partnerships, IP, talent) and generate an interpretable “Quantum Readiness / Signal Quality” score. Outputs support due diligence research and sector policy analysis.

Faculty Supervisor:

Sidney Shapiro

Student:

Partner:

National University of Sciences and Technology

Discipline:

Computer science

Sector:

Technology; Quantum Science; Finance and Insurance

University:

University of Lethbridge

Program:

Globalink Research Award

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