Dan Fu
microscopist and professor of chemistry
Facts
19 properties- Instance of
- human
- Date of birth
- 1982
- Occupation
- microscopist, chemistry teacher, chemist, university teacher
- Employer
- Harvard University (2010–2015), Massachusetts Institute of Technology (2009–2010), University of Washington (2015–present)[8]
- Field of work
- microscopy, chemical imaging[6][7]
- Educated at
- Princeton University (2004–2009), Peking University (1999–2003)
- Official website
- chem.washington.edu[18]
- Doctoral advisor
- Warren S. Warren[9]
- Doctoral student
- Kseniya S. Shin, Andrew T. Francis, Benjamin Figueroa, Jr[11][12][13]
- Academic appointment
- University of Washington Department of Chemistry (2015–present)[24]
- Academic degree
- Doctor of Philosophy, Bachelor of Science[14][15]
- On focus list of Wikimedia project
- WikiProject PCC Wikidata Pilot/University of Washington[22]
- Personal pronoun
- L485
🏷️ Also known as
en Dan Fu
🔖 Identifiers · 8
- ISNI
- 0000000047062664
- ORCID iD
- 0000-0001-9243-8306
- VIAF cluster ID
- 58915407
- Library of Congress Authorities ID
- no2009009765
- Google Scholar author ID
- vS2kXmEAAAAJ
- Prabook ID
- 1695169
- ScholarGPS scholar ID
- 25829726844094
- WorldCat Entities ID
- E39PBJqVY7kvkY7tQGXmRRKjmd
🔗 Connections
Author of 6
An area-based position and attitude estimation for unmanned aerial vehicle navigation,
A versatile deep learning architecture for classification and label-free prediction of hyperspectral images,
Characterizing Silicone Oil-Induced Protein Aggregation with Stimulated Raman Scattering Imaging,
Denoising of stimulated Raman scattering microscopy images via deep learning,
Label-Free Chemical Imaging of Latent Fingerprints with Stimulated Raman Scattering Microscopy,
Simultaneous Dual-Band Hyperspectral Stimulated Raman Scattering Microscopy with Femtosecond Optical Parametric Oscillators
← Authored by 6
An area-based position and attitude estimation for unmanned aerial vehicle navigation,
A versatile deep learning architecture for classification and label-free prediction of hyperspectral images,
Characterizing Silicone Oil-Induced Protein Aggregation with Stimulated Raman Scattering Imaging,
Denoising of stimulated Raman scattering microscopy images via deep learning,
Label-Free Chemical Imaging of Latent Fingerprints with Stimulated Raman Scattering Microscopy,
Simultaneous Dual-Band Hyperspectral Stimulated Raman Scattering Microscopy with Femtosecond Optical Parametric Oscillators
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