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Opportunities

Opportunities

InfoCloud has openings for Faculty members, Research Scientists, Post Doctoral fellows, PhD students, Master students and interns. Post Doctoral Fellow positions in KAUST King Abdullah University of Science and Technology (KAUST) invites applications for PostDoc positions in all areas of Databases, Data Mining, Cloud Computing, Parallel / Distributed Systems and High-performance Computing. The PostDoc positions are for 1 to 3 years. Requirements An ideal candidate should have (or be expecting soon) a PhD in Computer Science or a related field, with strong publication record. The candidate

Research

Cloud

‌InfoCloud focuses on information management in very large infrastructures such as clusters, supercomputers, GPUs and the Cloud. Our research interests include: Extremely large databases; Cloud Computing; Scientific data; Graphs, including RDF; Very Long Strings; Parallel and Distributed systems; Data mining and Knowledge extraction; and Bioinformatics. Software MIZAN: A Pregel clone for large-scale graph processing SIGMOD programming contest InfoCloud, in collaboration with MIT CSAIL, is organizing the 2013 ACM-SIGMOD programming contest. Prize: $5,000 plus travel grant to New York. http:/

Collaborators

We are investigating in developing a parallel graph data management. Graph data management. We have developed a strong string processing tool. We are developing a graph and string processing engine.

Research

The KAUST InfoCloud Group focuses on Databases and Information management Specifically, we are working on: Database outsourcing and Cloud Computing Mobile Computing Parallel and Distributed systems Peer-to-Peer OLAP and Data Warehouses Graphs, RDF and String processing Spatial-Temporal and High-dimensional Databases Data Security - Privacy - Anonymity Bioinformatics & Machine learning

Software

Disclaimer: The software on this page is provided on an as is basis for research purposes. There is no additional support offered, nor are the author(s) or their institutions liable under any circumstances Suffix Tree Contraction ERA_Software: Efﬁcient Serial and Parallel Sufﬁx Tree Construction We developed a disk-based suffix tree construction method, called Elastic Range (ERA), which works efficiently with very long strings that are much larger than the available memory. ERA partitions the tree construction process horizontally and vertically and minimizes I/Os by dynamically adjusting the

Info

Contacts

Panagiotis Kalnis Professor, Computer Science Principal Investigator, InfoCloud Research Group InfoCloud Research Group Office: Building 1, Level 4, Room 4414 Computer, Electrical and Mathematical Sciences (CEMSE) PO Box #: 1193 4700 King Abdullah University of Science and Technology (KAUST) Thuwal, 23955 Saudi Arabia

Publications

Publications

Journal Articles 21. Sahli M., Mansour E., Kalnis P., "ACME: A Scalable Parallel System for Extracting Frequent Patterns from a Very Long Sequence", Very Large Data Base Journal (VLDB-J), 2014. 20. Zuhair Khayyat, Karim Awaraka, Amani Alonazi, Hani Jamjoom, Dan Williams and Panos Kalnis,”Mizan: A System for Dynamic Load Balancing in Large-scale Graph Processing,” In Proceedings of the 8th ACM European conference on Computer Systems (EuroSys), Prague, Czech Republic, April 2013. 19. Mansour E., Allam A., Skiadopoulos S., Kalnis P., "ERA: Efficient Serial and Parallel Suffix Tree Construction

Teaching

Teaching

Courses CS245 - Databases by Panos Kalnis CS221 - Artificial Intelligence by Xin Gao CS229 - Machine Learning by Xiangliang Zhang CS341 - Advanced Databases by Panos Kalnis CS 340 - Data Mining by Xiangliang Zhang Enrolled students can access course material through KAUST's Blackboard via http://blackboard.kaust.edu.sa

Front Page

InfoCloud Research Group

Professor Panagiotis Kalnis leads the so-called CLOUD research group, which stands for InfoCloud Research Group Led by Prof. Panagiotis Kalnis, InfoCloud specializes in advanced information management for expansive infrastructures like clusters, supercomputers, GPUs, and the Cloud. Our research spans extremely large databases, Cloud Computing, scientific data, graphs (including RDF), very long strings, parallel and distributed systems, data mining, knowledge extraction, and Bioinformatics. ‌InfoCloud focuses on information management in very large infrastructures such as clusters