PhD Student at University of New South Wales, Australia
Aziida Nanyonga is a multidisciplinary educator and researcher with expertise spanning aerospace engineering, bioinformatics, public health, and information technology. She has an extensive academic background complemented by strong analytical and research skills, particularly in artificial intelligence, machine learning, and data analytics. With a passion for fostering inclusive and innovative teaching methodologies, she actively engages in higher education, research, and industry collaborations. Her work has contributed to the advancement of STEM disciplines through publications, mentorship, and curriculum development.
Profile
Google Scholar
Education
Aziida Nanyonga is currently pursuing a Ph.D. in Aerospace Engineering at the University of New South Wales, Canberra, focusing on advanced modeling and data analytics in aviation. She holds an M.Sc. in Bioinformatics from the University of Malaya, where she earned a Certificate of Excellence for her thesis on survival prediction after acute coronary syndrome in the Malaysian population. Additionally, she obtained a Master of Public Health from Kampala University with a GPA of 4.6, conducting research on non-communicable disease awareness programs. Her academic journey also includes a B.Sc. in Information Technology from the Islamic University in Uganda, where she graduated with first-class honors. She further expanded her pedagogical expertise by completing a Graduate Certificate in Teaching and Training from the University of New South Wales.
Experience
Dr. Nanyonga has accumulated extensive teaching and research experience. She served as an Assistant Lecturer and Teaching Assistant at the University of New South Wales, where she played a pivotal role in curriculum development, student mentorship, and research guidance. She also worked as an Assistant Principal Investigator at the University of Malaya, contributing to data analysis and multidisciplinary research projects. Additionally, she has been a Research Assistant and Teaching Assistant at the same institution, where she facilitated lectures and tutorials while engaging in high-impact research. Her volunteer work, including leadership roles in STEM education programs, demonstrates her commitment to knowledge dissemination and community engagement.
Research Interests
Aziida Nanyonga’s research interests encompass artificial intelligence, deep learning, and data analytics, particularly their applications in aerospace safety, bioinformatics, and public health. She specializes in natural language processing and predictive modeling for aviation incident analysis. Her work also explores interdisciplinary applications of machine learning for clinical decision-making, sustainability challenges, and engineering problem-solving. Through her research, she aims to bridge gaps between technology and real-world challenges, enhancing the efficiency and safety of various sectors.
Awards
Throughout her academic and professional career, Dr. Nanyonga has received several prestigious awards. She was recognized as the Best Presenter at INOCON 2024 and won the Best Paper Award at the Tensymp 2023 IEEE conference. She also received a Ph.D. Tuition Fee Scholarship from the University of New South Wales in 2021. Earlier in her career, she was awarded the Best Presenter Award at the National Heart Association of Malaysia’s Annual Scientific Meeting in 2018 and the Best Poster Award at Chulalongkorn University in Bangkok. Additionally, she was a recipient of the Islamic Development Bank M.Sc. Scholarship Program in 2017.
Publications
Nanyonga, A., Wasswa, H., Molloy, O., Turhan, U., & Wild, G. (2023). Natural language processing and deep learning models to classify phase of flight in aviation safety occurrences. IEEE Region 10 Symposium (TENSYMP).
Nanyonga, A., Wasswa, H., & Wild, G. (2024). Comparative Study of Deep Learning Architectures for Textual Damage Level Classification. International Conference on Signal Processing and Integrated Networks (SPIN).
Nanyonga, A., & Wild, G. (2023). Impact of Dataset Size & Data Source on Aviation Safety Incident Prediction Models with NLP. Global Conference on Information Technologies and Communications (GCITC).
Nanyonga, A., Wasswa, H., & Wild, G. (2023). Aviation Safety Enhancement via NLP & Deep Learning: Classifying Flight Phases in ATSB Safety Reports. GCITC.
Aziida, N., Malek, S., Aziz, F., Ibrahim, K. S., & Kasim, S. (2021). Predicting 30-day mortality after an acute coronary syndrome using machine learning. Sains Malaysiana.
Nanyonga, A., Wasswa, H., & Wild, G. (2023). Phase of Flight Classification in Aviation Safety Using LSTM, GRU, and BiLSTM: A Case Study with ASN Dataset. International Conference on High Performance Big Data and Intelligent Systems (HDIS).
Nanyonga, A., Wasswa, H., Turhan, U., Joiner, K., & Wild, G. (2024). Exploring Aviation Incident Narratives Using Topic Modeling and Clustering Techniques. IEEE Region 10 Symposium (TENSYMP).
Conclusion
Aziida Nanyonga’s research demonstrates a high level of expertise in artificial intelligence applications in aviation safety. The Best Paper Award should recognize work that advances knowledge, provides practical applications, and demonstrates methodological excellence.
Based on these criteria, the paper “Natural Language Processing and Deep Learning Models to Classify Phase of Flight in Aviation Safety Occurrences” (IEEE TENSYMP 2023) is highly recommended for this award due to its impact, innovation, and recognition in the academic community.