Dr. William Wasswa is senior lecture in the department of Biomedical Sciences and Engineering at Mbarara University of Science and Technology. He holds a first-class Honors Bachelor’s degree in Computer Engineering (BCE) awarded by Mbarara University and a masters of medical science in Biomedical Engineering (MMedSc.BME) of University of Cape Town (UCT) completed with a distinction. His master’s research was to develop a tool for 3D approximation of a human scapula from 2D X-ray images. This research addressed the challenges associated with 3D medical imaging which include high costs and ionizations radiations from CT.
Dr William has a PhD in Biomedical Engineering. His research focused on developing a low-cost digital microscope slide scanner for automated Diagnosis and Classification of cervical cancer from Pap smear images. This research is a step in low-cost automated early diagnosis of cervical cancer and cervical cancer oncology towards digital oncology. This research plays a significant role to the research agenda of the department of Biomedical Engineering which include designing low-cost Labs on chips diagnostic kits.
He has valuable skills and experience in Research Design both for qualitative and quantitative research, proposal writing, monitoring and evaluation, sampling methods, statistics, community engagement, policy and knowledge translation, oral and poster presentation, data analysis and tools, telemedicine, eLearning, Medical Imaging, Medical Physics and applications of Machine Learning techniques in Automated Oncology and softwares design and development.
Due to his expertise in the field of Artificial intelligence, he is a technical member on the AU-NEPAD Technical team investigating the applicability and readiness of African states to adapt Emerging-technologies. Due to his contribution in the field of digital health in Africa, he is a member of the ITU/WHO Focus Group Discussion on Artificial Intelligence for Africa (AI4H) and the Machine Learning Expert for the FG-AI4H Trial Audits: TG-Malaria. He is a member of the Standardization Evaluation Expert Group (SEG12) on Bio-digital convergence and a co-convener of the SEG 12/WG 3: Life systems and Bioengineering. He is member of Mbarara University Research Ethics Committee
Dr William has expertise in the Application of Emerging Technologies especially AI, IoT, Robotics, Biometrics and Virtual Reality in Health, Agriculture, Business and Education to improve service delivery in Africa. His interests are in Microfluidics, Digital Oncology, Biomechanics, Artificial Intelligence, Bio risk Management, Medical imaging, Healthy informatics, Red biotechnology, Personal health information systems, Global healthy, Decision support systems, Data Analysis, and Biostatistics.
 W. William, A. Ware, A. H. Basaza-Ejiri, and J. Obungoloch, “Cervical cancer classification from Pap-smears using an enhanced fuzzy C-means algorithm,” Informatics Med. Unlocked, 2019. https://doi.org/10.1016/j.imu.2019.02.001
 W. William, A. Ware, A. H. Basaza-Ejiri, and J. Obungoloch, “A pap-smear analysis tool (PAT) for detection of cervical cancer from pap-smear images,” Biomed. Eng. Online, Dec. 2019. https://doi.org/10.1186/s12938-019-0634-5
 W. William, A. Ware, A. H. Basaza-Ejiri, and J. Obungoloch, “A review of image analysis and machine learning techniques for automated cervical cancer screening from pap-smear images,” Comput. Methods Programs Biomed., vol. 164, pp. 15–22, Oct. 2018.
 Wasswa William, Annabella Habinka Basaza-Ejiri, Johnes Obungoloch, and Andrew Ware, “A Review of Applications of Image Analysis and Machine Learning Techniques in Automated Diagnosis and Classification of Cervical Cancer from Pap-smear Images,” in 2018 IST-Africa Week Conference (IST-Africa), 2018. https://ieeexplore.ieee.org/document/8417373
 T. Mutsvangwa, W. Wasswa, V. Burdin, B. Borotikar, and T. S. Douglas, “Interactive patient-specific 3D approximation of scapula bone shape from 2D X-ray images using landmark-constrained statistical shape model fitting,” in Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, 2017. https://doi.org/10.1109/EMBC.2017.8037198
 W. William, K. de Jager, L. John, and S. Steiner, “ X-Ray Beam-Width Limiting Device 1 ,” J. Med. Device., 2016.
 Wasswa William, Annabella Habinka Basaza-Ejiri, Johnes Obungoloch, and Andrew Ware, Automated segmentation of the nucleus, cytoplasm, and background of pap-smear images using a Trainable Pixel Level Classifier. 15th International Congress on American Pathology and Oncology Research
- UK-Africa Investment Summit 2020. Presented PapsAI, a digital pathology platform for cervical cancer diagnosis and management in low and middle income countries. The innovation is among the 2020 African Engineering Innovations Recognized by the Royal Academy of Engineering.
- Commonwealth Health Ministers Meeting, Geneva, Switzerland, 19 May 2019. The annual Commonwealth Health Ministers gathered officials from 53 countries to discuss how to accelerate universal health coverage (UHC) in their countries. Presented my innovation; a digital pathology platform for automated cervical cancer screening from pap-smear images.
- Expert Consultations on Artificial Intelligence Workshop in Johannesburg, South Africa from May 29-31, 2019. This AI experts consultative meeting was to build up on the AI report to be presented to Heads of State at the African Union Summit. I presented a white paper: The availability of datasets for AI Research in Africa and a way forward. I am also on the technical team developing the AU-NEPAD Report on Artificial Intelligence for Africa.
- Second WHO Africa Health Forum 26-28 March 2019, Praia, Cabo Verde. The event deliberated on improving health security, progress towards equity and universal health coverage (UHC), and the unfinished agenda of communicable diseases, while exploring the new Sustainable Development Goal (SDG) targets, and tackling social and economic determinants of health on the African continent. My innovation; PapES: A digital pathology Platform for Automated Diagnosis and Classification of cervical cancer from pap-smear images was selected for show casing among the 30 WHO Africa top innovations.
- IST-Africa 2019 Conference, Laico Regency Hotel, Nairobi, 08 – 10 May 2019. Presented Paper: Wasswa William, Annabella Habinka Basaza-Ejiri, Johnes Obungoloch, and Andrew Ware, “Automated Diagnosis and Classification of Cervical Cancer from pap-smear Images” in 2019 IST-Africa Week Conference (IST-Africa), 2019. https://ieeexplore.ieee.org/document/8417373
- IST-Africa 2018 Conference, Gaborone International Conference Centre, Botswana, 09 – 11 May 2018. Presented Paper: Wasswa William, Annabella Habinka Basaza-Ejiri, Johnes Obungoloch, and Andrew Ware, “A Review of Applications of Image Analysis and Machine Learning Techniques in Automated Diagnosis and Classification of Cervical Cancer from Pap-smear Images,” in 2018 IST-Africa Week Conference (IST-Africa), 2018. https://ieeexplore.ieee.org/document/8417373
- The 6th East African Healthcare Engineering Regional Conference and Exhibition (EARC 2018) 28-29th November 2018 Kampala, Uganda.
- Health Innovations Conference, 19-20 March, 2019, Kampala Serena Hotel. Presenter. Automated Analysis of pap-smear images using Machine Learning.
- 15th International Congress on American Pathology and Oncology Research (2018). Presenter. Automated segmentation of cervical cell nucleus using a pixel level classifier.
- National Cancer Research Institute, UK. Partners in Cancer Research Conference Glasgow, 2018. Presenter. Policy belief: Digitization of cervical cancer workflows in LMIC.