Monika Filipovska
University of Connecticut, CT·Engineering
Traffic delays and network disruptions cost the economy and the public a great deal, and they are hard to predict. Travel times change at random, and a slowdown in one place and time can spread to others.
- Fields
Engineering
Computer Science
Physics
- Topics
quantum computing
quantum algorithms
quantum optimization
- Grants
- 1 known grant, through Apr 2027
What they work on
- Develop quantum simulation algorithms that encode spatial and temporal dependencies of stochastic transportation networks into quantum states, using quantum amplitude estimation and dimensionality reduction to improve efficiency.
- Design tailored quantum optimization algorithms for pathfinding, finding reliable routes in transportation networks where travel conditions vary at random.
- Create a hybrid quantum-classical approach for route choice problems in stochastic transportation networks, splitting work between quantum and conventional computers.
- Evaluate the resource cost and solution quality of these algorithms on toy and benchmark transportation networks, using noisy intermediate-scale quantum devices and fault-tolerant quantum simulators.
More about the research
Modeling this uncertainty and planning reliable routes through it pushes ordinary computers to their limits. This exploratory project asks whether quantum computing can do better on two core problems: simulating uncertain (stochastic) transportation networks and finding routes that are reliable, not just fast on average.
Why it matters
Unreliable transportation networks cause financial and social costs, and weather events linked to climate change add to the disruptions. Quantum algorithms for simulating uncertain traffic and choosing reliable routes could eventually help transportation agencies and travelers make better decisions under uncertainty. The work may also lay groundwork for using quantum computing in other civil infrastructure systems.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Lei Fan
University of Houston, TX·Engineering·Early-career
Develop mixed-integer linear and convex optimization models that capture how data center computing load can shift across time and location, embedded within security-constrained unit commitment for scheduling generators under network limits.
Sonia Lopez Alarcon
Rochester Institute of Technology, NY·Computer Science
Train machine learning models to identify and synthesize qubit routing algorithms tailored to a specific quantum device and objective, including selection of optimal parameters and optimization functions.
Akimasa Miyake
University of New Mexico, NM·Physics
Determine how symmetry-protected topological order, a collective entanglement found in frustrated quantum spin systems, serves as a resource for quantum computation within measurement-based quantum computation.
The school
University of Connecticut: 31 labs on PI Pages, $434M a year on research, 360 research doctorates a year.
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