Sequential Design Optimization
Sequential Design Optimization is a methodological framework within sequential testing that iteratively refines experimental or sampling designs by dynamically selecting subsequent observations or interventions to maximize statistical efficiency or information gain under uncertainty.
177
Publications
8.3K
Citations
492
Authors
223
Institutions
Publications per year
2017–2026
41
Parents
177
1–5 of 177
492
University of Electronic Science and Technology of China, China
6 publications · 288 citations
6
h-index
University of Electronic Science and Technology of China, China
6 publications · 204 citations
6
h-index
4
h-index
Missouri University of Science and Technology, United States
4 publications · 316 citations
4
h-index
University of Electronic Science and Technology of China, China
4 publications · 191 citations
4
h-index
1–5 of 492
223

University of Electronic Science and Technology of China
Chengdu, China
8 h-index
30 publications
1.2K citations

Huazhong University of Science and Technology
Wuhan, China
7 h-index
17 publications
599 citations
University of Michigan
Ann Arbor, United States
7 h-index
14 publications
295 citations
University of California, Berkeley
Berkeley, United States
5 h-index
9 publications
260 citations
Virginia Tech
Blacksburg, United States
5 h-index
7 publications
367 citations

Lawrence Berkeley National Laboratory
Berkeley, United States
5 h-index
6 publications
177 citations
University of Technology Sydney
Sydney, Australia
5 h-index
12 publications
534 citations

Oakland University
Rochester, United States
4 h-index
9 publications
582 citations
1–8 of 223
7 publications · 259 citations
7
h-index
7 publications · 474 citations
7
h-index
6 publications · 328 citations
6
h-index
5 publications · 1.7K citations
5
h-index
4 publications · 90 citations
4
h-index
1–5