Selamawet Workalemahu Atnafu (Ph.D.)

Assistant Professor

Wselame7@gmail.com/selamawet.workalemahu@bdu.edu.et

Ghion Building N.307                                           

Education

University of Bologna (November, 2018 – November, 2022)

https://www.unibo.it/en

Ph.D. in Bioengineering

Research topic: “Development and characterization of deep learning techniques for neuroimaging data”

Supervisors: Prof. Stefano Diciotti and Prof. Mauro Orsinio

University of Trento (September, 2012 – July, 2015)

https://www.unitn.it/en

M.Sc. in Mechatronics Engineering

Master’s thesis: “Vision based skeleton tracking for humanoid action imitation”

Supervisor: Prof. Nicola Conci

Jimma University (September, 2006 – June, 2010)

https://ju.edu.et/

Bsc. In Electrical Engineering

Final thesis: “Computer typing using Eyes”

Work Experience

Bahir Dar Institute of Technology

• Assistant Professor Since November 1, 2023
  • Teaching courses like: Advanced Neural Networks, Advanced Biomedical Image Analysis, Advanced Research Methodology
  • Advising postgraduate students on AI based biomedical image processing
  • Participating on research activities with postgraduate students
  • Reviewing conference papers
• BIT Ethical Clearance Review Board member, since May, 2023
• Promotion committee for the Faculty of Electrical and Computer Engineering, since February, 2024.
• Committee for reviewing a curriculum on Masters of science in Biomedical Engineering.

• Lecturer September 2015 – October 2018
• Lecturing courses like: Instrumentation systems, 
• Advising undergraduate students in Electrical Engineering
• Course chair of Control Engineering department, September – February 2016

• Assistant Lecturer 
• Teaching courses: Fundamentals of Electrical Engineering, Basic Electricity and Installation, Electrical Workshop Practice 

Publications

1. Yagis, E., Citi, L., Diciotti, S., Marzi, C., Atnafu, S.W. and De Herrera, A.G.S., 2020, July. 3d Convolutional neural networks for diagnosis of alzheimer's disease via structural mri. In 2020 IEEE 33rd International Symposium on Computer-Based Medical Systems (CBMS) (pp. 65-70). IEEE.
2. Yagis, E., Atnafu, S.W., García Seco de Herrera, A., Marzi, C., Scheda, R., Giannelli, M., Tessa, C., Citi, L. and Diciotti, S., 2021. Effect of data leakage in brain MRI classification using 2D convolutional neural networks. Scientific reports, 11(1), p.22544.
3. Atnafu, S.W. and Diciotti, S., 2023. Development of an interpretable deep learning system for the identification of patients with Alzheimer’s disease. In Advancement of Science and Technology in Sustainable Manufacturing and Process Engineering (pp. 27-37). Cham: Springer Nature Switzerland.
4. Atnafu, S. and Nicola, C., 2018. Synchronized Video and Motion Capture Dataset and Quantitative Evaluation of Vision Based Skeleton Tracking Methods for Robotic Action Imitation. In Information and Communication Technology for Development for Africa: First International Conference, ICT4DA 2017, Bahir Dar, Ethiopia, September 25–27, 2017, Proceedings 1 (pp. 150-158). Springer International Publishing.
5. S Atnafu, C Marzi, E Salvadori, A Poggesi, A Giorgio, N De, M Stefano, Computer Assisted Radiology and Surgery 16, 70-71. A deep learning scheme for predicting the cognitive status of patients with small vessel disease and mild cognitive impairment.