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Isack Emmanuel Bulugu

College of Information and Communication Technologies

Electronics and Telecommunications Engineering

Biography

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.

Research Interest

Computer Vision

  • Development of advanced algorithms for object detection, tracking, and scene understanding.
  • Human activity recognition and gesture-based interaction for intelligent systems.
  • Application of vision systems in robotics, healthcare, and surveillance.

    Human-Computer Interaction (HCI)

  • Designing intuitive, user-centered interaction models for immersive technologies.
  • Development of accessible technologies to support individuals with disabilities.
  • Investigating multimodal interfaces combining visual, auditory, and tactile feedback.

    Digital Image and Video Processing

  • Real-time image enhancement, restoration, and feature extraction techniques.
  • Video analytics for smart surveillance and automated content recognition.
  • Application of deep learning for image segmentation and classification tasks.

    Pattern Recognition and Machine Learning

  • Building robust models for gesture and facial recognition using deep learning.
  • Development of adaptive algorithms for real-world, noisy environments.
  • Exploring transfer learning and domain adaptation for cross-disciplinary applications.

    Gesture and Sign Language Recognition

  • Creation of efficient systems for real-time sign language interpretation.
  • Integration of 3D skeletal data and sensor-based inputs for improved recognition accuracy.
  • Application of gesture recognition in assistive technologies and human-robot collaboration.

    Assistive Technologies and Ubiquitous Computing

  • Development of cost-effective assistive devices for people with sensory impairments.
  • Smart environments leveraging IoT and wearable technologies for context-aware computing.
  • Enhancing e-learning platforms with inclusive design principles for diverse user groups.

Contacts

Email:

Projects

  • Human Activity Recognition for Human-Robot Collaboration (2024–2026)
    Role: Project Team Member
    Program: SPARX Program, Chalmers University of Technology, Sweden
    Contribution: Focused on developing AI models for improving human-robot interaction in collaborative environments.
  • Cloud Platform Construction for Environmental Awareness of IoT (2022–2023)
    Role: Project Team Member
    Institution: Chongqing Technology and Business University, China
    Contribution: Worked on designing cloud-based IoT systems for environmental data analysis and smart monitoring.
  • Manufacturing and Commercialization of Assistive Technology Tools (2022–2023)
    Role: Principal Investigator
    Institution: University of Dar es Salaam, Tanzania
    Contribution: Led the development of affordable assistive technology and e-learning interfaces for students with hearing impairments.
  • iLabs Africa Project (2009–2011)
    Role: Project Team Member
    Institution: University of Dar es Salaam, Tanzania
    Contribution: Contributed to advancing online laboratory platforms for remote scientific experiments across Africa.

Publications

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