PROVIDENCE, RI [Brown University] – Ilija Nikolov knows better than anyone that a quantum future is coming. In fact, he’s so sure of it that he’s helping one of the world’s biggest investment firms prepare for it.
Brown University Ph.D. student is completing an internship with the data science team of the Fidelity Center for Applied Technology at Fidelity Investments headquarters in Boston this summer. As an intern at FCAT, which studies the frontiers of computing and how it can be used at Fidelity, Nikolov’s main task is to evaluate and test whether neural networks inspired by quantum mechanics can improve the company’s computer systems.
“Everything people have heard about how quantum mechanics will provide real-world breakthroughs in a variety of disciplines is not all hype,” said Nikolov, who is in his second summer with FCAT. “There’s some serious research and investment going on right now. While we can’t envision all the applications that quantum advances will lead to, it will start to become a reality for many companies in perhaps the next 10 years.”
The FCAT data team recruited Nikolov because of his range of work at Brown, where he has used machine learning algorithms and also applied ideas from quantum computing to condensed matter in the lab of Brown physics professor Vesna Mitrović.
Theoretically, quantum-based hacking technologies will be able to compromise most, if not all, classical computer security systems, while quantum-based security systems will be virtually impossible to hack due to superposition and confusion. These are the principles that allow quantum bits to exist in several states at the same time and instantly affect the state of another, regardless of distance. When applied to financial analysis, overlap and entanglement allow calculations to be made simultaneously, providing an exponential speedup over existing methods.
“Because we don’t know what these future systems will look like, it all means that my work is more of a feasibility project for now,” Nikolov said. “The main goal is to determine how useful this kind of quantum system can be for the company.”
Much of Nikolov’s work over the past two summers with FCAT has involved building and implementing a neural network that draws on classical and quantum computing to evaluate several of the firm’s security systems and analyze a variety of financial data, including such as stocks. Nikolov worked with existing neural network frameworks—which mimic the way brain neurons communicate—and adapted them to the company’s specific data needs.
Last summer, for example, he created a system to study past financial data for trends and patterns that the company could apply to future data. This summer, Nikolov is using the system to produce high-quality synthetic data to train other machine learning models the company uses for its financial services.
“Because everything is so new, there are no existing paradigms or models to follow, so you’re basically reinventing the wheel,” Nikolov said.
The full-time practice is a hybrid, and Nikolov, who is from Macedonia, has taken full advantage of his time in the office to explore downtown Boston, including a duck boat tour and catching a Red Sox game at Fenway Park. He is no stranger to New England having completed his undergraduate degrees in physics and mathematics at Amherst College. He started at Brown in the fall of 2020 and received his master’s in physics in 2021 and master’s in computer science in 2024. He is now in his fifth year Ph.D. candidate in physics.
The Fidelity internship has helped Nikolov balance his classroom and lab experience at Brown, where his focus has been exploring the exotic mysteries of a family of superconducting metals, with a more hands-on science experience.
“This conclusion of my overall research history was the whole idea behind this experience,” said Nikolov.