Mohamed Abouelenien

Assistant Professor, Computer and Information Science

College of Engineering & Computer Science

Mohamed Abouelenien

Assistant Professor, Computer and Information Science

My Portrait

Mohamed Abouelenien

Assistant Professor

University of Michigan - Dearborn
Computer & Information Science
244 CIS
Dearborn, MI 48128
Tel: 313-593-3963
Email:

Teaching

CIS 5570 - Introduction to Big Data

Fall 2017, 2018, 2019, 2020
Winter 2020, 2021

This course provides an overview of what big data is and explores its characteristics. It introduces the fundamental technologies, platforms, and methods that enable Big Data analysis, and covers how to acquire, store, and analyze very large amounts of information to complete Big Data analysis tasks. Students will gain hands-on experience in real-world applications of Big Data such as in cyber-physical systems and health informatics. Most of the work in this course will be team-based and task-oriented.

CIS 511 - Natural Language Processing

Fall 2019, 2020
Winter 2019, 2020

This graduate-level course provides an introduction to the theory and practice of natural language processing (NLP), as well as the approaches that allow understanding, generating, and analyzing natural language. The course will cover the three major areas in NLP: syntax, semantics, and pragmatics. The course will introduce both knowledge-based and statistical approaches to NLP, illustrate the use of NLP techniques and tools in a variety of application areas, and provide insight into many open research problems.

CIS 5700 - Advanced Data Mining

Winter 2018

This course provides an in-depth study of advanced data mining, data analysis and pattern recognition concepts and algorithms. Course content builds upon a first data mining course and explores advanced machine learning algorithms, high-dimensional data, graph and temporal data, and advanced methods and applications to deal with dynamic stream data. Various applications will be considered, including social networks and health informatics. Students will be able to understand the research methods applied in the field and conduct an end-to-end data mining project and document and present the results.

CIS 3200 - Data Science II

Winter 2021

This undergraduate course provides an overview of what Big Data is and explores its characteristics. It introduces the fundamental technologies, platforms, and methods that enable Big Data analysis, and covers how to acquire, store, and analyze very large amounts of information to complete Big Data analysis tasks. Topics include MapReduce, similarity search, mining real-time data streams, link analysis, clustering, recommender systems, social network graph mining, and large scale data mining tasks.

CIS 411 - Natural Language Processing

Fall 2019, 2020
Winter 2019, 2020

This undergraduate course provides an introduction to the theory and practice of natural language processing (NLP), as well as the approaches that allow understanding, generating, and analyzing natural language. The course will cover the three major areas in NLP: syntax, semantics, and pragmatics. The course will introduce both knowledge-based and statistical approaches to NLP, illustrate the use of NLP techniques and tools in a variety of application areas, and provide insight into many open research problems.