On June 28th, Dr Fatos Xhafa, a professor with the Department of Computer Science, Technical University of Catalonia, Spain, was invited to visit USLab. Dr Xhafa gave a talk on Issues In Efficient and Scalable Data Mining Algorithms. USLab members, some faculty members of the School of ISE and students participated in the talk. Dr Xhafa discussed the main drivers behind big data and the life cycle of the big data along several real life use cases from businesses. Then, he focused on the challenges of various implementation approaches and issues of mining large data sets such as scalability and memory issues faced.

Professor Fatos Xhafa received his PhD in Computer Science in 1998 from the Department of Computer Science of the Technical University of Catalonia (UPC), Barcelona, Spain. His current research interest include parallel and distributed algorithms, combinatorial optimization, networking systems, distributed programming, Grid and P2P computing. Prof. Xhafa has widely published in peer reviewed international journals, conferences/workshops, book chapters and edited books and proceedings in the field (http://dblp.uni-trier.de/pers/hd/x/Xhafa:Fatos). His research is supported by Research Projects from Spain, EU and NSF/USA.

6月28日,USLab邀请西班牙加泰罗尼亚理工大学Fatos Xhafa教授来实验室进行学术交流。Xhafa教授做了题为《高效可拓展数据挖掘算法中的问题》的学术报告,USLab实验室及信息科学与工程学院部分师生参加了此次学术交流。Xhafa教授以商贸领域的真实案例为例,介绍了大数据的产生和应用,然后重点分析了面向可扩展的、并且需要解决存储问题的大数据挖掘算法中的挑战,以及典型算法。