Mr. Iko-Ojo Simon, BSc, MSc, is a PhD candidate researching Algorithm Debt in Machine Learning and Deep Learning Systems. He earned his Bachelor’s (Hons.) and Master of Science (MSc) degrees in Computer Science from the University of Jos, Nigeria.
Prior to starting his PhD, Iko-Ojo served as an Assistant Lecturer in the Department of Computer Science at the University of Jos, where he was involved in both research and teaching in the areas of Computer Science and Software Engineering.
He is currently a sessional academic at the Australian National University, where he tutors students in various Computer Science courses.
Master of Public Health - MPH, Reproductive and Child
BSc, Public Health
Experience:
Eskedar Mekonnen is a Digital Research Trainer at Intersect Australia. She is also a PhD candidate at the Robinson Research Institute, University of Adelaide. With a background in Epidemiology, Eskedar possesses extensive skills in research design and analysis. Eskedar has years of experience working with diverse data types and analysis methods, including Machine Learning and longitudinal data collection and analysis. She is skilled in various research software programs, including R, Qualtrics, and REDCap.
Leta holds a Bachelor’s degree in public health from Dilla University (2017) and a Master’s of Public Health in Epidemiology from Jimma University (2020), Ethiopia. He has served as a lecturer and researcher at Salale University, where he taught courses such as Epidemiology, Research Methods, and Data Management while also taking on various academic positions. Currently, Leta is pursuing a PhD in Genetic Epidemiology, focusing on the intriguing roles of human endogenous retroviruses in neurodegenerative diseases.
Philosophy and History of Science, Data science, Programming, Statistics, Data Visualization, Scientific Conversations, Knowledge Sharing, and research.
Experience:
Ali is currently a second year PhD student in Biomedical Engineering at UNSW with over 9 years of research experience through his PhD studies, and as a research assistant in various labs from 2013 till present. He has been programming using Excel, R and bash (Linux) for over 5 years and has a strong background in the analysis of health and biological data resulting in the publication of several bioinformatics papers. During the past 5 years he has been able to develop required specialised skills and gain lots of experience in both programming and data analytics (statistical and Artificial Intelligence-based approaches) which gave him a strong capability in teaching students how to start programming and how to design an efficient analysis pipeline in the Excel, R and bash environments. He has over 4 years of teaching data analytics in both R (statistical analysis, scripting and visualization) and Bash (package development) programing languages. He also has several hours teaching bioinformatics experience at University of Sydney and UNSW as casual tutor.
PhD, Applied and Plasma Physics (ongoing) BSc (Hons I ), Physics
Personal Interests:
Applied plasma physics for nanoparticle fabrication and implementation in biomedical applications. Passionate about conveying my knowledge to the scientific and public community.
Experience:
2+ years of research experience in plasma polymerised nanoparticle and their biomedical applications; 5+ years as a tutor for students at various academic levels.
PhD, Multidisciplinary Research on TB (ongoing) M Computer Science B Math/ B Science
Personal Interests:
Artificial Intelligence algorithms and application, Time series forecasting, Medical Informatics.
Experience:
Seng Hansun is a PhD candidate in South West Sydney, UNSW Medicine & Health, UNSW Sydney. His research focuses on the machine and deep learning area for Tuberculosis disease detection. He has extensive experience in learning and teaching programming languages, including Python and R, for more than 10 years. He is also an enthusiast in artificial intelligence and machine learning domain.
PhD (in progress), Distributed Machine Learning BEng (Hons.), Software Engineering
Experience:
Murtaza is a PhD candidate at the University of Melbourne researching privacy-preserving, secure and distributed machine learning paradigms. He completed his Bachelor of Engineering with First Class Honours from Monash University in 2022.
Prior to his PhD, Murtaza worked as a Software Engineering Analyst at Goldman Sachs, where he designed distributed systems and AI-driven automation for financial workflows.
He is currently a Sessional Academic at the University of Melbourne, where he tutors students in Distributed Systems and Cluster and Cloud Computing. He is also a Digital Research Trainer at Intersect, delivering training in digital and computational research tools to researchers across Australian universities.
Vu is a PhD candidate at the University of New South Wales (UNSW), where his research focuses on multimodal self-supervised learning for Earth observation using SAR and optical imagery. He completed a Master of Information Technology (AI, Data Science and Engineering) with Excellence at UNSW in 2023.
Alongside his research, Vu has experience in developing computational tools and delivering training in programming and digital workflows. Prior to pursuing his PhD, he worked as a Computational/Structural Engineer at Stantec, where he developed automation tools and delivered tutorials to support the adoption of digital workflows. He also mentored students at UNSW and led peer-learning Python sessions in industry.
Vu is currently a Digital Research Trainer at Intersect Australia and an intern in the 3AI team, where he delivers training in digital research tools and contributes to interdisciplinary applied AI research.
