Haoming Shen Data-verified

OverviewAI-generated summary

Haoming Shen's research focuses on the theoretical and algorithmic aspects of optimization, particularly in the context of stochastic and chance-constrained programming. His work investigates methods for solving complex optimization problems that involve uncertainty, where outcomes are not precisely known. Shen has published on topics including convex chance-constrained programs with Wasserstein ambiguity, and sequential quadratic optimization for expectation equality constrained stochastic optimization problems. He also contributes to the theoretical understanding of robust chance constraints. His scholarship metrics include an h-index of 2 with 4 total publications and 12 citations.

Metrics

• h-index: 2
• Publications: 4
• Citations: 14