About Us

Jacek Aleksander (pronounced 'Yatzek Alexander') graduated from the University of Gdansk in 2009 as a Master of Computer Science. A member of the Quantum Information group at the Institute of Theoretical Physics and Astrophysics, he wrote his masters dissertation under the supervision of Professor Marek Żukowski, a Prize of the Foundation for Polish Science laureate. Jacek investigated topics in Bell nonlocality and defended a thesis entitled "Nonclassical properties of multiqubit states applicable in quantum information science." This work required lots of Scientific Computing and it is then that Jacek took his first steps as a Computational Scientist.

Following this experience, Jacek joined an Irish software company Kainos and then a Belarusian-American software services company EPAM Systems. These were his core experiences in Software Development, where he took on numerous roles as a Software Engineer, Senior Software Engineer, Business Analyst, Scrum Master and Technical Support in Presales. His experience also involved short stints at Morgan Stanley, Citigroup and Bloomberg in London, where he worked in Infrastructure Departments on Financial Software.

Jacek founded Jagan Solutions in 2016. The company has since developed into an independent unit delivering solutions in AI, Machine Learning, Data Science and Analytics as well as Scientific Computing and Optimization. Jacek has recruited the best of the best in their trade, which typically evolves around Machine Learning, and makes sure that all projects are delivered up to the highest quality standards. It is his ambition to create a rewarding workplace for Jagan's employees, to provide innovative and reliable services for its clients, and to maintain a steady course on the state-of-the-art science applications in business.

Having worked on scientific problems with the Quantum Information team at University of Gdansk since graduation in 2009, Jacek returned to his alma mater to pursue a PhD in 2017. His dissertation entitled "Solving two-level optimization problems related to Bell's theorem" supervised by Professor Puchała and Professor Laskowski was defended successfully in September 2019. The dissertation was an advanced computational exercise in Mathematical Optimization as applied to Quantum Information. He subsequently completed a postdoc at University of Gdansk, which involved evolutions of Quantum Systems under various types of Schrödinger and Schrödinger-Newton equations. He is currently a Fulbright Senior Award Scholar at Columbia University in the City of New York, where he researches applications of Reinforcement Learning (an area of Artificial Intelligence) within Quantum Information Science.