Jeff Borggaard
Ph.D. Virginia Polytechnic Institute and State University 1994
Facts
10 properties- Instance of
- human
- Date of birth
- 1964[3]
- Occupation
- mathematician
- Employer
- Virginia Tech[4]
- Educated at
- Virginia Tech[5]
- Doctoral advisor
- John Allen Burns[6]
- Doctoral student
- Kay Ellen White Vugrin, Miroslav Stoyanov, Kevin Pond, Hans-Werner van Wyk, Vitor Manuel Leite dos Santos Nunes, Alan Martin Lattimer, Cristina Letona-Bolivar, Justin August Krometis[8][9][10][11][12][13][14][15]
- Family name
- Borggaard[16]
🏷️ Also known as
en Jeff Borggaard
en Jeffrey Todd Borggaard
🔖 Identifiers · 14
- ISNI
- 0000000081850445
- ORCID iD
- 0000-0002-4023-7841
- VIAF cluster ID
- 116254956
- Library of Congress Authorities ID
- n95019920
- GND ID
- 172879353
- DBLP author ID
- 81/4002
- DDB person (GND) ID
- 172879353
- Google Knowledge Graph ID
- /g/11gbhyytcg
- Google Scholar author ID
- Vjqk950AAAAJ
- J9U entity ID
- 987007424983005171
- MR Author ID
- 339592
- Mathematics Genealogy Project ID
- 36319
Show all 14 identifiers +2
- WorldCat Entities ID
- E39PCjBkBPtrbmgDHB4MDV7F4y
- Yale LUX ID
- person/f2233de2-eb34-4052-b023-5dd5310c7bb2
🔗 Connections
Author of 5
A goal-oriented reduced-order modeling approach for nonlinear systems,
Gradient-based estimation of uncertain parameters for elliptic partial differential equations,
Learning-based robust stabilization for reduced-order models of 2D and 3D Boussinesq equations,
Principal interval decomposition framework for POD reduced‐order modeling of convective Boussinesq flows,
Using functional gains for effective sensor location in flow control: a reduced-order modelling approach
← Authored by 5
A goal-oriented reduced-order modeling approach for nonlinear systems,
Gradient-based estimation of uncertain parameters for elliptic partial differential equations,
Learning-based robust stabilization for reduced-order models of 2D and 3D Boussinesq equations,
Principal interval decomposition framework for POD reduced‐order modeling of convective Boussinesq flows,
Using functional gains for effective sensor location in flow control: a reduced-order modelling approach
Affiliated with 1
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