Demo Data from EDBT 2026 / reviewers in the wild / expert
Manish Prasad
dblp:78/1434
· DBLP profile ↗
5ranked-venue papers
1as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Systems, architecture and hardware · 3 · 1 first-authorArtificial intelligence and machine learning · 2Databases, data management, data science and information retrieval · 1Graphics, computer vision, multimedia, augmented reality and games · 1
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Computer architecture, parallel and distributed computing, and storage systems
1 paper |
Storage systems · 100% | |
| Artificial intelligence
2 papers |
Face, body and person analysis · 100% | |
| Network and information security
1 paper |
Systems and software security · 100% | |
| Computer graphics and multimedia
2 papers |
Computational photography and imaging · 100% | |
| Software engineering, system software, and programming languages
1 paper |
Compilers and program optimization · 100% |
Topics — the 7 heaviest of 7, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer vision › Face, body and person analysis
face recognition |
0.1 | 2 | 2003 | Face Recognition in Hyperspectral Images · IEEE Trans. Pattern Anal. Mach. Intell. 2003 Face Recognition in Hyperspectral Images · CVPR (1) 2003 |
Storage systems
distributed storage |
0.1 | 1 | 2005 | Ursa Minor: Versatile Cluster-based Storage · FAST 2005 |
Storage systems › distributed storage
storage cluster |
0.1 | 1 | 2005 | Ursa Minor: Versatile Cluster-based Storage · FAST 2005 |
Computational photography and imaging › spectral imaging
hyperspectral imaging |
0.1 | 2 | 2003 | Face Recognition in Hyperspectral Images · IEEE Trans. Pattern Anal. Mach. Intell. 2003 Face Recognition in Hyperspectral Images · CVPR (1) 2003 |
Systems and software security › memory safety › memory corruption defense
buffer overflow protection |
0.0 | 1 | 2003 | A Binary Rewriting Defense Against Stack based Buffer Overflow Attacks · USENIX ATC, General Track 2003 |
Systems and software security
memory safety |
0.0 | 1 | 2003 | A Binary Rewriting Defense Against Stack based Buffer Overflow Attacks · USENIX ATC, General Track 2003 |
Compilers and program optimization
binary rewriting |
0.0 | 1 | 2003 | A Binary Rewriting Defense Against Stack based Buffer Overflow Attacks · USENIX ATC, General Track 2003 |
Methods — techniques the papers use, named apart from their topics
spectral measurement · 0.2tissue-type discriminant · 0.1versatility · 0.1face recognition algorithms · 0.0face recognition algorithm · 0.0
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Ursa Minor: Versatile Cluster-based Storage
Michael Abd-El-Malek, William V. Courtright II, Chuck Cranor, Gregory R. Ganger, James Hendricks, Andrew J. Klosterman, Michael P. Mesnier, Manish Prasad, Brandon Salmon, Raja R. Sambasivan, Shafeeq Sinnamohideen, John D. Strunk, Eno Thereska, Matthew Wachs, Jay J. Wylie |
FAST | 8 |
| 2003 | Face Recognition in Hyperspectral ImagesabstractHyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. We examine the utility of using near-infrared hyperspectral images for the recognition of faces over a database of 200 subjects. The hyperspectral images were collected using a CCD camera equipped with a liquid crystal tunable filter. Spectral measurements over the near-infrared allow the sensing of subsurface tissue structure, which is significantly different from person to person but relatively stable over time. The local spectral properties of human tissue are nearly invariant to face orientation and expression, which allows hyperspectral discriminants to be used for recognition over a large range of poses and expressions. We describe a face recognition algorithm that exploits spectral measurements for multiple facial tissue types. We demonstrate experimentally that this algorithm can be used to recognize faces over time in the presence of changes in facial pose and expression. Zhihong Pan 0001, Glenn Healey, Manish Prasad, Bruce J. Tromberg |
CVPR (1) | 3 |
| 2003 | A Binary Rewriting Defense Against Stack based Buffer Overflow Attacks
Manish Prasad, Tzi-cker Chiueh |
USENIX ATC, General Track | 1 |
| 2003 | Face Recognition in Hyperspectral ImagesabstractHyperspectral cameras provide useful discriminants for human face recognition that cannot be obtained by other imaging methods. We examine the utility of using near-infrared hyperspectral images for the recognition of faces over a database of 200 subjects. The hyperspectral images were collected using a CCD camera equipped with a liquid crystal tunable filter to provide 31 bands over the near-infrared (0.7 /spl mu/m-1.0 /spl mu/m). Spectral measurements over the near-infrared allow the sensing of subsurface tissue structure which is significantly different from person to person, but relatively stable over time. The local spectral properties of human tissue are nearly invariant to face orientation and expression which allows hyperspectral discriminants to be used for recognition over a large range of poses and expressions. We describe a face recognition algorithm that exploits spectral measurements for multiple facial tissue types. We demonstrate experimentally that this algorithm can be used to recognize faces over time in the presence of changes in facial pose and expression. Zhihong Pan 0001, Glenn Healey, Manish Prasad, Bruce J. Tromberg |
IEEE Trans. Pattern Anal. Mach. Intell. | 3 |
| 2002 | LLM: A Low Latency Messaging Infrastructure for Linux Clusters
R. K. Shyamasundar, Basant Rajan, Manish Prasad |
HiPC | 3 |