Dr. Isack E. Bulugu earned his B.Sc. in Electronics Science and Communication from the University of Dar es Salaam, Tanzania (2008), an M.Eng. in Signal and Information Processing from Tianjin University of Technology, China (2014), and a Ph.D. in Information and Communication Engineering from the University of Science and Technology of China, Hefei (2018). His research interests focus on advanced topics in Artificial Intelligence, including Computer Vision, Human-Computer Interaction (HCI), Image and Video Processing, Pattern Recognition, and Gesture/Sign Language Recognition. He currently serves as a Senior Lecturer in the Department of Electronics and Telecommunication Engineering, College of Information and Communication Technologies, at the University of Dar es Salaam, Tanzania.
Computer Vision
Application of vision systems in robotics, healthcare, and surveillance.
Human-Computer Interaction (HCI)
Investigating multimodal interfaces combining visual, auditory, and tactile feedback.
Digital Image and Video Processing
Application of deep learning for image segmentation and classification tasks.
Pattern Recognition and Machine Learning
Exploring transfer learning and domain adaptation for cross-disciplinary applications.
Gesture and Sign Language Recognition
Application of gesture recognition in assistive technologies and human-robot collaboration.
Assistive Technologies and Ubiquitous Computing
Email:
1. Bulugu, I., (2024). “Adaptive Shift Graph Convolutional Neural Network for Hand Gesture Recognition Based on 3D Skeletal Similarity” Signal, Image and Video Processing, Springer Nature. (SCI journal, IF=1.583)
2. Bulugu, I. (2024). Evaluation of the Quality of Online Education Based on a Learning Interactive Network. University of Dar es Salaam Library Journal, 19(1), 42-56.
3. Bulugu, I., (2023). “Gesture Recognition System Based on Cross-domain CSI Extracted from WiFi devices Combined with the 3D CNN” Signal, Image and Video Processing, Springer Nature. (SCI journal, IF=1.583)
4. Xiang, Q., Huang, T., Zhang, Q., Li, Y., Tolba, A., Bulugu, I. (2023). A Novel Sentiment Analysis Method based on Multi-scale Deep Learning. Mathematical Biosciences and Engineering, AIMS, 20(5),766–8781. (SCI journal, IF=2.194)
5. Zhou, Y., Zhang, Q., Zhang, H., Yang, J., Guo, Z., Bulugu, I. and Shen, Y. (2023). A deep vision sensing-based fuzzy control scheme for smart feeding in the industrial recirculating aquaculture systems. IET Electronics Letters, 59(2). (SCI journal, IF=1.202)
6. Bulugu, I. (2022). Real-time Complex Hand Gestures Recognition Based on Multi-Dimensional Features. Tanzania Journal of Engineering and Technology, 40(2), 45-57.
7. Bulugu, I. (2021). Sign language recognition using Kinect sensor based on color stream and skeleton points. Tanzania Journal of Science, 47(2), 769-778..
8. Banzi, J., Bulugu, I., Ye, Z., Naqvi,N. (2020). Learning a deep predictive coding network for a semi-supervised 3D hand pose estimation. IEEE/CAA Journal of Automatica Sinica, 7(5),1371-1379. (SCI journal, IF=7.847)
9. Bulugu, I., Banzi, J., Ye, Z. (2017). Higher-order Local Autocorrelation Feature Extraction Methodology
for Hand Gestures Recognition. IEEE International Conference on Multimedia and Image Processing (ICMIP),Wuhan,China.
10. Banzi, J., Bulugu, I., Ye, Z.(2016). A Novel Hand Pose Estimation Using Discriminative Deep Model and Transductive Learning Approach for Occlusion Handling and Reduced Discrepancy. IEEE International Conference on Computer and Communication, Chengdu, China