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职业迁徙
个人简介
The primary focus of my research is on the design and analysis of effective data-driven models and efficient algorithms that leverage tools from discrete optimization problems, and in particular, on approximation algorithms for NP-hard and other computationally intractable problems. Linear programming relaxations have played a fundamental role in obtaining good solutions to hard optimization problems, and we continue to study their application to a range of problems in clustering, sequencing and scheduling, and inventory problems, in both deterministic and stochastic optimization settings. In addition to studying these problems with a theoretical lens, we have been involved in the practical application of these techniques in settings ranging from genomics to medical aircraft scheduling to the long-term planning for the preservation of the red-cockaded woodpecker to the operational logistics and design of bike-sharing systems. More recent application domains include COVID epidemiological modeling, congressional districting and IoT network design.
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ACM-SIAM Symposium on Discrete Algorithms (2023): 2793-2828
Dagstuhl Reportsno. 2 (2023): 1-19
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APPROXIMATION AND ONLINE ALGORITHMS, WAOA 2023 (2023): 160-174
PROCEEDINGS OF THE 54TH ACM TECHNICAL SYMPOSIUM ON COMPUTER SCIENCE EDUCATION, VOL 1, SIGCSE 2023pp.108-114, (2023)
CoRR (2023)
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arxiv(2023)
medRxiv (Cold Spring Harbor Laboratory) (2022)
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