Latifur R. Khan, Ph.D.

Affiliations: 
2000 University of Southern California, Los Angeles, CA, United States 
Area:
Computer Science, Biomechanics
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"Latifur Khan"

Parents

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Dennis McLeod grad student 2000 USC
 (Ontology -based information selection.)

Children

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Pracheta Sahoo grad student 2019- University of Texas - Dallas (Computer Science Tree)
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Publications

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Sahoo P, Roy I, Ahlawat R, et al. (2021) Potential diagnosis of COVID-19 from chest X-ray and CT findings using semi-supervised learning. Physical and Engineering Sciences in Medicine
Sahoo P, Roy I, Wang Z, et al. (2020) MultiCon: A Semi-Supervised Approach for Predicting Drug Function from Chemical Structure Analysis. Journal of Chemical Information and Modeling
Gao Y, Chandra S, Li Y, et al. (2020) SACCOS: A Semi-Supervised Framework for Emerging Class Detection and Concept Drift Adaption over Data Streams Ieee Transactions On Knowledge and Data Engineering. 1-1
Islam S, Dong B, Chandra S, et al. (2020) GCI: A GPU Based Transfer Learning Approach for Detecting Cheats of Computer Game Ieee Transactions On Dependable and Secure Computing. 1-1
Huang H, Khan L, Zhou S. (2020) Classified enhancement model for big data storage reliability based on Boolean satisfiability problem Cluster Computing. 23: 483-492
Eirinaki M, Gao J, Khan L, et al. (2019) Editorial for Special Issue on “Big Data and Smart Cities” Big Data Research. 17: 33-34
Ayoade G, El-Ghamry A, Karande V, et al. (2019) Secure data processing for IoT middleware systems The Journal of Supercomputing. 75: 4684-4709
Al-Khateeb T, Masud MM, Al-Naami KM, et al. (2016) Recurring and Novel Class Detection Using Class-Based Ensemble for Evolving Data Stream Ieee Transactions On Knowledge and Data Engineering. 28: 2752-2764
Al-Naami KM, Seker SE, Khan L. (2016) GISQAF: MapReduce guided spatial query processing and analytics system Software - Practice and Experience. 46: 1329-1349
Ismail L, Khan L. (2015) Implementation and performance evaluation of a scheduling algorithm for divisible load parallel applications in a cloud computing environment Software - Practice and Experience. 45: 765-781
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