Fingerprint Fingerprint is based on mining the text of the persons scientific documents to create an index of weighted terms, which defines the key subjects of each individual researcher.

  • 1 Similar Profiles
Vector quantization Engineering & Materials Science
Neural networks Engineering & Materials Science
Image compression Engineering & Materials Science
Radar Engineering & Materials Science
Automatic target recognition Engineering & Materials Science
Classifiers Engineering & Materials Science
Feature extraction Engineering & Materials Science
MATLAB Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Projects 2008 2018

Research Output 1979 2017

1 Citations

Scientific training in the era of big data: A new pedagogy for graduate education

Aikat, J., Carsey, T. M., Fecho, K., Jeffay, K., Krishnamurthy, A., Mucha, P. J., Rajasekar, A. & Ahalt, S. C. Mar 1 2017 In : Big Data. 5, 1, p. 12-18 7 p.

Research output: Contribution to journalReview article

Education
Curricula
Students
Medicine
Data mining
16 Citations

Privacy preserving interactive record linkage (PPIRL)

Kum, H. C., Krishnamurthy, A., Machanavajjhala, A., Reiter, M. K. & Ahalt, S. 2014 In : Journal of the American Medical Informatics Association. 21, 2, p. 212-220 9 p.

Research output: Contribution to journalArticle

Privacy
Medicine in Literature
Computer Security
Information Storage and Retrieval
Disclosure
6 Citations

Social genome: Putting big data to work for population informatics

Kum, H. C., Krishnamurthy, A., Machanavajjhala, A. & Ahalt, S. C. 2014 Computer, 47, 1, p. 56-63 8 p.

Research output: Contribution to specialist publicationArticle

Data integration
Genes
Health
Economics
Big data
4 Citations

Water science software institute: Agile and open source scientific software development

Ahalt, S., Band, L., Christopherson, L., Idaszak, R., Lenhardt, C., Minsker, B., Palmer, M., Shelley, M., Tiemann, M. & Zimmerman, A. 2014 In : Computing in Science and Engineering. 16, 3, p. 18-26 9 p., 6728937

Research output: Contribution to journalArticle

Software engineering
Water
Amplification
Mechanics
11 Citations

Predicting survival in patients with brain metastases treated with radiosurgery using artificial neural networks

Oermann, E. K., Kress, M. A. S., Collins, B. T., Collins, S. P., Morris, D., Ahalt, S. C. & Ewend, M. G. Jun 2013 In : Neurosurgery. 72, 6, p. 944-951 8 p.

Research output: Contribution to journalArticle

Radiosurgery
Neoplasm Metastasis
Survival
Brain
Logistic Models