Olfa Nasraoui

Professor, Endowed Chair for E-Commerce, Computer Engineering & Computer Science

About

Dr. Olfa Nasraoui is the endowed Chair of e-commerce and the founding director of the Knowledge Discovery & Web Mining Lab at the University of Louisville, where she is also Associate professor in Computer Engineering & Computer Science. She received her Ph.D in Computer Engineering and Computer Science from the University of Missouri-Columbia in 1999. She is the recipient of a National Science Foundation CAREER Award and a Best Paper Award for theoretical contributions in computational intelligence at the ANNIE conference.

Teaching Interests

Dr. Nasraoui teaches graduate courses related to data mining / machine learning, as well as optimization. This includes:

  • "CECS 621: Web Mining for e-commerce and Information Retrieval" which teaches the principles with hands on projects in data mining / machine learning in big, high dimensional and sparse data, including web clickstreams, text, social networks and media, and transactional data. The course also teaches latent semantic indexing and probabilistic topic modeling and classification, information retrieval, recommender systems, social network analysis and sentiment/opinion mining.
  • "CECS 620: Combinatorial Optimization" teaches classical and meta-heuristic techniques for optimization. Classical methods include linear programming, local search, dynamic programming, branch & bound, A*, alpha-beta pruning, and others. Meta-heuristics include tabu-search, simulated annealing, and advanced evolutionary optimization (multimodal, multi-objective, constrained, and coevolutionary), as well as particle swarm, ant-based, and artificial immune system optimization. The course also covers numerical optimization techniques such as Lagrangian Optimization. Example cases range from optimization in graph-related problems to game strategies and data analysis.

Research interests

Data mining, machine learning, mining high dimensional, sparse, heterogeneous or unstructured data and evolving data streams; Web personalization and profiling, intelligent user modeling, intelligent information retrieval and recommender systems.