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Current Positions
Chief Technology Officer & Co-founder — First QFM
Associate Professor — BI Norwegian Business School
Quantum Research Scientist — CogniFrame
Quantum Research Fellow — Rethinc Labs, UNC Chapel Hill
Education & Professional Journey
Isaiah Hull graduated from Salem State University in 2008 before pursuing advanced graduate studies and earning his Ph.D. in Economics.
From 2013 to 2022, Dr. Hull worked at Sveriges Riksbank, Sweden’s central bank, where he served as an Economist and later Senior Economist in the Research Division. In 2022, he joined BI Norwegian Business School as an Associate Professor while also beginning research work with CogniFrame. In 2024, he became a Quantum Research Fellow with Rethinc Labs at the University of North Carolina at Chapel Hill. Most recently, he became Chief Technology Officer and Co-founder of First QFM, further expanding his leadership in the fields of financial technology and quantum computing.
Research & Professional Contributions
Dr. Hull’s work focuses on computational economics, machine learning, and quantum computing. He has published extensively in these emerging fields, with more than 50 scholarly works, including journal articles, book chapters, and research preprints, generating over 500 academic citations.
His accomplishments include:
- Authoring one of the first textbooks on machine learning applications in economics
- Publishing the first textbook on quantum computing applications in economics
- Leading workshops on computational economics for major public institutions, including the National Bank of Ukraine and the Dutch National Bank
- Teaching online machine learning courses that have reached more than 50,000 students worldwide
In recognition of his research impact, Dr. Hull was ranked among the top 8% of authors in economics over the last ten publication years by RePEc (August 2024).
Professional Impact
Through his teaching, research, entrepreneurship, and international collaborations, Dr. Hull continues to advance the intersection of economics, artificial intelligence, machine learning, and quantum computing. His career demonstrates how economics training can open pathways into cutting-edge technological innovation and interdisciplinary research.