Jingru Zhang
Cleveland State University, OH·Computer Science·Early-career
Where should you put hospitals, warehouses or cell towers so they serve people best? These are facility location problems: choose sites that minimize, say, the longest travel distance or the total distance to demand points.
- Fields
Computer Science
Mathematics & Statistics
- Topics
algorithms
facility location
uncertain data
- Grants
- 1 known grant, through Feb 2029
What they work on
- Develop efficient algorithms for fault-tolerant facility location, which places facilities so demand is still served if some facilities fail, with uncertain demand data.
- Design algorithms for chromatic facility location, which places multiple types of facilities at once, on graph networks and in the plane.
- Create algorithms for proximity-connected versions of minimax and minisum facility location models, with both certain and uncertain inputs.
- Apply tools from computational geometry, graph theory, probability and combinatorial optimization to find faster or first-known solutions to these optimization problems.
More about the research
Real demand data are often uncertain because of sensor error, measurement mistakes, sampling faults or errors when combining datasets. This project develops efficient algorithms for facility location when the input data are uncertain.
Why it matters
Many planning decisions depend on noisy data from sensors and other sources. Faster, more reliable algorithms for placing facilities under uncertainty could help planners decide where to locate services so they keep working when some fail and serve demand well despite imperfect data.
Known grants
From NIH and NSF research grants. Labs often have other funding we can't see.
Closest labs
Ryan O'Donnell
Carnegie Mellon University, PA·Computer Science
Find new elementary methods for constructing high-dimensional expanders, highly interconnected mathematical networks, that avoid the advanced algebra and number theory used in current constructions.
Shachar Lovett
University of California-San Diego, CA·Computer Science
Develop the theory of spreadness, a measure that no structured subset contains too many elements, into a general framework connecting existing structure-versus-randomness arguments.
Illya Hicks
Rice University, TX·Mathematics & Statistics
Develop polyhedral theory — representing discrete choices as geometric shapes amenable to linear methods — to formulate and solve optimization problems for battery storage in microgrids.
The school
Cleveland State University: 2 labs on PI Pages, $86M a year on research, 35 research doctorates a year.
Reach out
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