Thomas Gyeera
Assistant Teaching Professor
Computer & Information Science
Contact
508-910-6697
508-999-9144
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Dion 303B
Education
| 2019 | The University of Sheffield | PhD in Computer Science |
| 2014 | Sheffield Hallam University | MS in Computer & Network Engineering |
| 2005 | University of Duisburg | BSc in Computer Science & Communications Engine |
Teaching
- Advanced Data Mining and Knowledge Discovery
- Objected Oriented Programming
- Artificial Intelligence, Machine Learning, and Deep Learning
- Computer Networks
- Cloud Computing
Teaching
Programs
Programs
Teaching
Online and Continuing Education Courses
Coverage of advanced topics of data mining and its applications. The course will review related mathematics and then focus on data mining core algorithms and advanced modeling including regression, dimensionality reduction, support vector machines, clustering, graph theory, and frequent pattern mining. The course will also explore several real-world problems and discuss strategies for large-scale data.
Register for this course.
Coverage of advanced topics of data mining and its applications. The course will review related mathematics and then focus on data mining core algorithms and advanced modeling including regression, dimensionality reduction, support vector machines, clustering, graph theory, and frequent pattern mining. The course will also explore several real-world problems and discuss strategies for large-scale data.
Register for this course.
Research
Research activities
- Artificial intelligence, machine learning, and deep learning
- Cloud/fog/edge computing
- Transformers, transfer learning, meta-learning, recurrent independent mechanisms
- Adaptive Filtering
Research
Research interests
- Artificial intelligence, machine learning, and deep learning
- Cybersecurity
- Cloud/fog/edge computing/IoT and autonomous computing
- Transformers, transfer learning, meta-learning, recurrent independent mechanisms
Select publications
- T. W. Gyeera, A. J. H. Simons, and M. Stannett (2022).
Kalman filter based prediction and forecasting of cloud server KPIs
IEEE Transactions on Services Computing, 0, 1 - 14. - T. W. Gyeera, A. J. H. Simons, and M. Stannett (2022).
Regression Analysis of Predictions and Forecasts of Cloud Data Center KPIs Using the Boosted Decision Tree Algorithm
IEEE Transactions on Big Data, 0, 1 -16. - T. W. Gyeera (2019).
Monitoring and Adaptation of Pooled Cloud Computing Resources
White Rose eTheses Online, 1 - 215.
Thomas Weripuo Gyeera is an Assistant Professor at the University of Massachusetts Dartmouth. He received a PhD degree in computer science from the University of Sheffield UK in 2019 and an MS in computer and network engineering with distinction from Sheffield Hallam University, UK in 2014. He received a BSc degree in computer science and communications engineering from the University of Duisburg in 2005. He has worked for Thales Group and Ford motor company as an application development engineer. He has been working on using machine learning and adaptive algorithms for proactive cloud computing resources monitoring and adaptation. His major interests and work are in AI, Deep and Machine learning, cloud computing, application development, network engineering and Big Data.