CONCEPT / 01
Simple rules, large-scale selection decisions
This work finds that simple greedy procedures achieve sample-optimal selection.
Read the paperDecision Intelligence,
Simulation, and
Healthcare Operations.
At DISH Lab, we study how to make better decisions in the era of big data and AI—with AI and for AI. Through simulation and digital twins, we model and optimize complex systems under ambiguity and uncertainty. In healthcare, we aim to address unmet needs in the design and delivery of care, connecting methodological advances with operational challenges.
Research Projects and Directions
Zaile Li (李在乐)
Assistant Professor
National University of Singapore
We are Hiring! Prospective PhD students, postdoctoral researchers, and research assistants are always welcome! Opportunities
Featured work
Selected work on how to learn, compare, and decide.
CONCEPT / 02
Learning across drug development portfolios
Response-adaptive pilot studies use emerging trial results to adjust investment across treatment-development projects to improve financial outcomes, incentivize drug development, and expand access to new treatments.
Read the paperCONCEPT / 03
Upper confidence bound approach for selection problems
Upper confidence bound algorithms help allocate experiments among many alternatives with heavy-tailed outcomes.
Read the paperJoin the lab
Curiosity meets
interesting, innovative,
important questions.
We welcome self-motivated prospective PhD students, postdoctoral researchers, and research assistants interested in decision intelligence, simulation, and healthcare operations.