2014 - IEEE Fellow For contributions to the fields of multimedia, geospatial and distributed databases
2009 - ACM Distinguished Member
The scientist’s investigation covers issues in Data mining, Artificial intelligence, k-nearest neighbors algorithm, Machine learning and Mobile device. His Data mining study combines topics from a wide range of disciplines, such as Spatial database, Spatial analysis, Geospatial analysis, Personalization and Data set. His Artificial intelligence research integrates issues from Graph and Pattern recognition.
His work carried out in the field of k-nearest neighbors algorithm brings together such families of science as Spatial network and Nearest neighbor search. His Machine learning study combines topics from a wide range of disciplines, such as Intelligent transportation system and Scalability. His Mobile device research is multidisciplinary, relying on both Crowdsourcing, Focus and Computer security.
Cyrus Shahabi mostly deals with Data mining, Artificial intelligence, Information retrieval, Scalability and Crowdsourcing. The various areas that Cyrus Shahabi examines in his Data mining study include Spatial query, Spatial analysis, Geospatial analysis and k-nearest neighbors algorithm. His study in Spatial query is interdisciplinary in nature, drawing from both Query optimization and Database.
His Artificial intelligence study incorporates themes from Machine learning, Computer vision and Pattern recognition. He combines subjects such as Mobile device and Data science with his study of Crowdsourcing. His study connects Computer security and Mobile device.
Cyrus Shahabi mainly focuses on Artificial intelligence, Data mining, Crowdsourcing, Machine learning and Data science. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Graph, Computer vision and Pattern recognition. His Data mining research includes themes of Entropy and Baseline.
His Crowdsourcing study integrates concerns from other disciplines, such as Budget constraint, Heuristics and Mobile device. The concepts of his Data science study are interwoven with issues in World Wide Web and Crowdsource. His biological study spans a wide range of topics, including Recurrent neural network and Traffic flow.
His primary areas of study are Artificial intelligence, Data mining, Machine learning, Crowdsourcing and Deep learning. As part of one scientific family, he deals mainly with the area of Artificial intelligence, narrowing it down to issues related to the Graph, and often Road networks. His Data mining research includes elements of Entropy, Boundary and Degree.
His work on Multivariate statistics as part of his general Machine learning study is frequently connected to Multi-task learning, thereby bridging the divide between different branches of science. Cyrus Shahabi has included themes like Budget constraint, Overhead, Heuristics, Mobile device and Data science in his Crowdsourcing study. His research integrates issues of Recurrent neural network, Moving average, Computer vision and Time series in his study of Deep learning.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Big data and its technical challenges
H. V. Jagadish;Johannes Gehrke;Alexandros Labrinidis;Yannis Papakonstantinou.
Communications of The ACM (2014)
Private queries in location based services: anonymizers are not necessary
Gabriel Ghinita;Panos Kalnis;Ali Khoshgozaran;Cyrus Shahabi.
international conference on management of data (2008)
Diffusion Convolutional Recurrent Neural Network: Data-Driven Traffic Forecasting
Yaguang Li;Rose Yu;Cyrus Shahabi;Yan Liu.
international conference on learning representations (2018)
Voronoi-based K nearest neighbor search for spatial network databases
Mohammad Kolahdouzan;Cyrus Shahabi.
very large data bases (2004)
Knowledge discovery from users Web-page navigation
C. Shahabi;A.M. Zarkesh;J. Adibi;V. Shah.
international workshop on research issues in data engineering (1997)
GeoCrowd: enabling query answering with spatial crowdsourcing
Leyla Kazemi;Cyrus Shahabi.
advances in geographic information systems (2012)
Crowd sensing of traffic anomalies based on human mobility and social media
Bei Pan;Yu Zheng;David Wilkie;Cyrus Shahabi.
advances in geographic information systems (2013)
The spatial skyline queries
Mehdi Sharifzadeh;Cyrus Shahabi.
very large data bases (2006)
Blind evaluation of nearest neighbor queries using space transformation to preserve location privacy
Ali Khoshgozaran;Cyrus Shahabi.
symposium on large spatial databases (2007)
A Road Network Embedding Technique for K-Nearest Neighbor Search in Moving Object Databases
Cyrus Shahabi;Mohammad R. Kolahdouzan;Mehdi Sharifzadeh.
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