Samuel Kakuba

Assistant Lecturer-Computer Engineering

Samuel Kakuba is an Assistant lecturer of Computer Engineering at the Faculty of Engineering, Technology, Applied Design and Fine Art of Kabale University.

He is currently a PhD student of Electronics and Electrical Engineering at Kyungpook National University, Republic of Korea. He holds a Master of Science in Data Communication & Software Engineering of Makerere University and a Bachelor of Science in Computer Engineering of Busitema University.  His research interest is in Communication Systems and Artificial Intelligence Applications in Electronics Engineering systems.   The goal that guides his academic work is “Integrating academic and industrial experiences with Artificial Intelligence techniques in Electronics, Communication and Computer Engineering in order to bring about new and affordable ways of solving problems in our communities ”.

In order to be part of the Academicians that foster the Fourth Industrial Revolution, he is interested in teaching and research in the fields of Communication Systems Engineering,  Internet of Things,  Artificial Intelligence Systems using Soft Computing, Machine Learning and Deep Learning. He is currently carrying out research in Speech Signal Processing, Human to Vehicle Interaction and Emotion Recognition using Computer Vision and Natural Language Processing techniques.

He has lectured and supervised students’ project research in the above areas in different universities in Uganda since 2011.

Qualifications

 

  • PhD student of Electronics and Electrical Engineering (2021 to date) Kyungpook National University, South Korea
  • MSc. Data Communication and Software Engineering (2018)- Makerere University, Uganda
  • Bachelor of Computer Engineering (2011)- Busitema University, Uganda

Research Interests

Communication Systems Engineering,  Internet of Things,  Artificial Intelligence Systems using Machine Learning and Deep Learning.

Current Research: Speech Signal Processing, Human to Vehicle Interaction and Emotion Recognition using Computer Vision and Natural Language Processing techniques.

Publications

Projects

No Projects found.

Supervision

No Supervisions yet. Try again later

Presentations

Inception-inspired local feature learning with attention mechanism for speech emotion recognition, Presented at the 32nd Joint Conference on Communication and Information (JCCI), April 27th to 29th, 2022.

Residual bidirectional LSTM with multi-head attention for speech emotion recognition, Presented at the Korean Institute of Communications and Information Sciences (KICS) Summer Conference 2022, June 22nd to 24th, 2022.

Performance comparison of raw speech signals and handcrafted features in deep learning-based emotion recognition models, presented at the 3rd Korean Artificial Intelligence Conference, September 28th to 29th, 2022.

Speech emotion recognition using context-aware dilated convolution network,  presented at the 27th Asia-Pacific International Conference on Communications (APCC), October 19th to 21st, 2022.

More Information