PROVIDENCE, R.I. [Brown University] — Ilija Nikolov knows better than most that a quantum future is coming. In fact, he’s so certain of it that he’s helping one of the world’s largest investment firms prepare for it.
The Brown University Ph.D. student is completing an internship with the Fidelity Center for Applied Technology data science team at Fidelity Investments’ Boston headquarters this summer. As an intern at FCAT, which studies the frontiers of computing and how it can be used at Fidelity, Nikolov’s primary task is to evaluate and test whether quantum mechanics-inspired neural networks can enhance the company’s computer systems.
“Everything people have been hearing about how quantum mechanics will provide real-world breakthroughs across a range of disciplines is not all hype,” said Nikolov, who is spending his second summer with FCAT. “There’s some serious research and investment going on now. While we cannot really imagine all the applications that advancements in quantum will lead to yet, this is going to start becoming a reality for a lot of 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 Brown Professor of Physics Vesna Mitrović’s lab.
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 entanglement. These are the principles that allow quantum bits to exist in multiple states at once and instantaneously influence the state of another, regardless of distance. When applied to financial analysis, superposition and entanglement allow computations to be done simultaneously, providing an exponential speed-up over existing methods.
“Because we don’t know what these future systems will look like, what it all means is that my work is more of a feasibility project for now,” Nikolov said. “The main goal is to determine how useful this type of quantum system could 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 is based on both classical and quantum computing to evaluate some the firm’s security systems and analyze a range of financial data, such as stocks. Nikolov worked with existing neural network frameworks — which mimic how brain neurons communicate — and adapted them to for the company’s specific data needs.
Last summer, for instance, he designed a system to study past financial data for trends and patterns 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 it’s all very new, there are no paradigms or existing models to follow, so you’re basically inventing the wheel,” Nikolov said.
The full-time internship is hybrid, and Nikolov, who is from Macedonia, has taken full advantage of his time in the office to explore downtown Boston, including taking a duck boat tour and catching a Red Sox game at Fenway Park. He is no stranger to New England having completed his undergraduate degree in physics and mathematics at Amherst College. He started at Brown in Fall 2020 and earned his master’s in physics in 2021 and master’s in computer science in 2024. He is now a fifth year Ph.D. candidate in physics.
The internship at Fidelity has helped Nikolov balance his classroom and lab-based experience at Brown, where his focus has been exploring the exotic mysteries of a family of superconducting metals, with a more applicative scientific experience.
“This rounding out of my overall research background has been the whole idea behind this experience,” Nikolov said.