個人檔案
學歷
- Ph.D. Statistics (1990) University of Minnesota, Minneapolis-St.Paul
研究專長
My current research is to develop more realistic optimal designs for practical applications in the big data era. This invariably means the models are high-dimensional and current algorithms do not work well. Nature-inspired metaheuristic algorithms are essentially assumptions free and have been shown to be able to solve many different types of complex high-dimensional optimization problems in engineering and computer science, even when rigorous proofs of convergence and their theoretical properties remain quite elusive. My recent work has shown that unlike current algorithms used in statistics, metaheuristics can solve different types of optimal designs for virtually any model and under any criterion for small to moderate sized problems. In 2018, I co-organized a workshop “Particle Swarm Optimization and Evolutionary Computation” at IMS. A probabilist and a mathematician from NUS and Prof. T. L. Lai from Stanford University were motivated by the workshop and we are now working on theoretical aspects of evolutionary algorithms. Our initial work seems to have gotten some attention in the engineering community as I was pleasantly surprised to be invited to be a guest coeditor of a special theoretical issue for the journal “IEEE Emerging Topics and Computational Intelligence”. I view this as a distinct honor given that I am an ‘outsider’. Additionally, I am the lead organizer of a 1-week workshop on Metaheuristics, Machine Learning and AI at the Statistical and Applied Mathematical Sciences Institute (SAMSI) at Durham, NC from March 8-12th 2021.
In 1997, I won the First Independent Research Support and Transition Award from the National Institute of Arthritis and Musculoskeletal and Skin Diseases. I participated in several rheumatoid arthritis (RA) studies, including "High versus Low Dose Pencillamine in Systemic Sclerosis" and "Long Term Observational Study of Early Severe RA Patients". Earlier on, I also served as the director of the "Multipurpose Arthritis Center Data Analysis Core" from 1995-1998. Currently, I am the biostatistician for the "Multi-Center Phase II Trial of Oral Type I Bovine Collagen in Scleroderma" supported by the National Institutes of Health (NIH). I have also participated in NIH-supported research work in dentistry and environment health science.
與 UN SDG 相關的專業知識
聯合國會員國於 2015 年同意 17 項全球永續發展目標 (SDG),以終結貧困、保護地球並確保全體的興盛繁榮。此人的作品有助於以下永續發展目標:
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SDG 3 良好的健康和福祉
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SDG 7 經濟實惠的清潔能源
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SDG 9 產業、創新與基礎設施
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SDG 17 為永續目標構建夥伴關係
指紋
查看啟用 Weng Kee Wong 的研究主題。這些主題標籤來自此人的作品。共同形成了獨特的指紋。
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過去五年中的合作和熱門研究領域
國家/地區層面的近期外部共同作業。按一下圓點深入探索詳細資料,或
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Adaptive Parameter Tuning of Evolutionary Computation Algorithms
Choi, K. P., Lai, T. L., Tong, X. T., Tsang, K. W., Wong, W. K. & Zhang, H., 2025, (Accepted/In press) 於: Statistics in Biosciences.研究成果: Article › 同行評審
開啟存取1 !!Link opens in a new tab 引文 斯高帕斯(Scopus) -
Design optimization of longitudinal studies using metaheuristics: Application to lithium pharmacokinetics
Schepps, M. A., Seurat, J., Mentré, F. & Wong, W. K., 2025 8月, 於: Statistical Methods in Medical Research. 34, 8, p. 1633-1645 13 p.研究成果: Article › 同行評審
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Model Parameters Estimation for the Biosciences Using Particle Swarm Optimization
Park, J., Shao, S. & Wong, W. K., 2025, (Accepted/In press) 於: Statistics in Biosciences. 103577.研究成果: Article › 同行評審
1 !!Link opens in a new tab 引文 斯高帕斯(Scopus) -
Nature-inspired metaheuristics for optimizing dose-finding and computationally challenging clinical trial designs
Wong, W. K., Ryeznik, Y., Sverdlov, O., Chen, P. Y., Fang, X., Chen, R.-B., Zhou, S. & Lee, J. J., 2025 8月, 於: Clinical Trials. 22, 4, p. 422-429 8 p.研究成果: Article › 同行評審
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Optimal experimental designs for big and small experiments in toxicology with applications to studying hormesis via metaheuristics
Wu, B. P. H., Chen, R. B. & Wong, W. K., 2025 6月, 於: Computational Toxicology. 34, 100345.研究成果: Article › 同行評審
3 !!Link opens in a new tab 引文 斯高帕斯(Scopus)