Jacob L. Cybulski, PhD

Founder, researcher and consultant at Enquanted
Also, Honorary Assoc. Prof., School of IT, Deakin
In quantum computing and quantum machine learning

• Contact:
  Email: info(at)jacobcybulski.com
  Web: jacobcybulski.com
  LinkedIn: au.linkedin.com/in/jacobcybulski
  YouTube: youtube.com/ironfrown
  GitHub: github.com/ironfrown

• Additional info:
  Selected pubs: ICCS'2024, QINP, JIT, and CHB
  Selected YouTube video: Visual Analyst 3D
  Selected YouTube training: R and RapidMiner
  Teaching approach: Experiential Learning

• Related links:
  Company: Enquanted
  Profile: School of IT, Deakin
  Profile: Google Scholar
  Profile: ResearchGate
  Profile: Zotero
  Project: Enquanted Art Gallery
  

• Past associations:

  • Information Systems and Business Analytics, Deakin University
  • Information Systems, The University of Melbourne
  • Computer Science and Computer Engineering, La Trobe University
  • Amdahl Australian Intelligent Tools Programme, La Trobe University
  • AI Systems, Telecom Research Labs
  • Computer Science, RMIT University

• Education:

  • B.App.Sci. (RMIT)
  • M.App.Sci. (RMIT)
  • PhD (La Trobe)

• More here:
  Teaching, Projects, Research, Publications
  Awards, Presentations, Supervision, Media

Figure. Hilbert space vs. parameter space

Find more about the fundamental concepts of Quantum Machine Learning, by viewing my presentation slides on "Quantum Algorithms and Data Encoding for QML (in Qiskit)," delivered at QBronze-167, Quantum Computing and Programming Workshop, QIndia / QWorld, August 2025.

The Qiskit code used in the presentation can be found in "Quantum Machine Learning A-B-C in Qiskit", GitHub repository.

The paper which inspired the presentation was written by Jacob L. Cybulski and Sebastian Zając (2025): "Quantum Modelling of Time Series: Expressivity vs. Trainability." In review for journal submission. 20 August 2025, Preprint (Version 1) available at Research Square.