People

Max Li

Assistant Professor, Aerospace Engineering

Max’s research interests lies in the design, management, and optimization of large-scale infrastructure systems, focusing on the air transportation system and emerging aerial mobility systems. He is interested in the application of methods applicable to networked systems, especially with resource constraints (e.g., airspace and airport capacity), diverse stakeholders (e.g., passenger-centric, airline-centric), and complex dynamics (e.g., changing temporal behaviors). Max has worked on a variety of data-driven problems related to analyzing flight delays across airport networks, strategic/tactical air traffic management and delay assignments, privacy and routing in drone-based applications, and uncertainty-aware traffic management. He is interested in methods such as graph signal processing and signal processing over non-Euclidean domains, data-driven optimization, mixed-integer/integer/combinatorial programs, resilient network design, and stochastic optimization. Broadly, Max hopes to contribute to a safe, resilient, and efficient air transportation system (inclusive of intra- and inter-city modalities) within the context of a passenger’s (or cargo’s) door-to-door journey.

A flight delay assignment mechanism that does not rely on knowing the exact value of an airline's private per-flight valuation of flight delays. The mechanism requires the system capacities/demand per round, and computes an initial solution. This solution is adjusted by a Coordinating Airline using privatized information from Participating Airlines. The resultant solution is proposed, and any negative public delays incurred is recorded to a ledger. The role of Coordianting/Participating Airlines then rotate depending on the current ledger balance.
Image: A flight delay assignment mechanism that does not rely on knowing the exact value of an airline’s private per-flight valuation of flight delays. The mechanism requires the system capacities/demand per round, and computes an initial solution. This solution is adjusted by a Coordinating Airline using privatized information from Participating Airlines. The resultant solution is proposed, and any negative public delays incurred is recorded to a ledger. The role of Coordinating/Participating Airlines then rotate depending on the current ledger balance.

What is the most significant scientific contribution you would like to make?

Working with air traffic controllers and traffic flow managers to deploy/prototype a congestion management solution/model!

What makes you excited about your data science and AI research?

The potential positive impact on the air transportation system, and helping to make it more efficient and equitable in terms of access.

Accomplishments and Awards

COntact

2174195173

maxzli@umich.edu

Location

Ann Arbor

Methodologies

Data Integration / Data Mining / Data Visualization / Graph-Based Methods / Machine Learning / Mathematical and Statistical Modeling / Networks / Optimization / Security and Privacy / Statistics

Applications

Complex Systems / Engineering