Biography
Dr Alex Cummaudo is an Industry Fellow of the Applied Artificial Intelligence Institute. Between 2018 and 2021, he led research into machine learnt computer vision models, specifically those hosted via cloud computing platforms, and investigated downstream evolutionary impacts. His aim is to enable software engineers infuse AI into applications and democratise machine learning.
Read more on Alex's profileBiography summary
Dr Alex Cummaudo received his BSc degree in software development from Swinburne University of Technology, Australia in 2016 and his BIT(Hons) from Deakin University, Australia in 2017, where he developed an end-to-end computer vision prototype for detecting alphanumeric sequences in-the-wild. He currently specialises in AI-component integration, and explores ways to enhance DevX and developer productivity within AI-based software. His PhD thesis investigated the behavioural and evolutionary profiles of pre-trained machine learning models hosted on cloud platforms, where he proposed solutions to resolve issues around such 'plug-and-play' technology through a novel software architecture that enhances integration robustness and improved service documentation techniques. He completed his PhD under Deakin University's Applied Artificial Intelligence Institute (A²I²), having published in top A and A*-ranked software engineering conferences and journals. In 2020–2021, Alex was employed at the Institute as an Associate Research Fellow, and remains an associated Industry Fellow with the Institute. He is currently employed with REA Group.
Knowledge areas
Software Engineering, Machine Learning Engineering, API Development, Software Architecture, Software Quality, Software Evolution, Artificial Intelligence, Computer Vision, MLOps
Publications
Requirements of API Documentation: A Case Study into Computer Vision Services
A Cummaudo, R Vasa, J Grundy, M Abdelrazek
(2022), Vol. 48, pp. 2010-2027, IEEE Transactions on Software Engineering, C1
Emotions in Computer Vision Service QA
A Cummaudo, U Graetsch, M Curumsing, R Vasa, S Barnett, J Grundy
(2021), pp. 13-18, SEmotion 2021 : Proceedings of the IEEE/ACM 6th International Workshop on Emotion Awareness in Software Engineering, Madrid, Spain, E1
Interpreting cloud computer vision pain-points: a mining study of stack overflow
A Cummaudo, R Vasa, S Barnett, J Grundy, M Abdelrazek
(2020), pp. 1584-1596, ICSE 2020 : Proceedings of the 2020 ACM/IEEE 42nd International Conference on Software Engineering, Seoul, South Korea, E1
Threshy: Supporting Safe Usage of Intelligent Web Services
Alex Cummaudo, Scott Barnett, Rajesh Vasa, John Grundy
(2020), pp. 1645-1649, ESEC/FSE 2020 : Proceedings of the 28th ACM Joint Meeting on European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Online, E1
A Cummaudo, S Barnett, R Vasa, J Grundy, M Abdelrazek
(2020), pp. 269-280, ESEC/FSE 2020 : Proceedings of the 28th ACM Joint Meeting European Software Engineering Conference and Symposium on the Foundations of Software Engineering, Online from United States of America, E1
Merging intelligent API responses using a proportional representation approach
T Ohtake, A Cummaudo, M Abdelrazek, R Vasa, J Grundy
(2019), Vol. 11496, pp. 391-406, ICWE 2019 : Proceedings of the 19th International Conference on Web Engineering 2019, Daejeon, South Korea, E1
What should I document? A preliminary systematic mapping study into API documentation knowledge
A Cummaudo, R Vasa, J Grundy
(2019), Vol. 2019-Septemer, pp. 1-6, ESEM 2019 : Proceedings of the ACM/IEEE International Symposium on Empirical Software Engineering and Measurement (ESEM), Porto de Galinhas, Recife, Brazil, E1
Losing confidence in quality: unspoken evolution of computer vision services
A Cummaudo, R Vasa, J Grundy, M Abdelrazek, A Cain
(2019), pp. 333-342, ICSME 2019 : Proceedings of the 2019 IEEE International Conference on Software Maintenance and Evolution, Cleveland, Oh., E1
A proposal for integrating gamification into task-oriented portfolio assessment
J Meyers, A Cain, J Renzella, A Cummaudo
(2018), pp. 1022-1027, TALE 2018 : Engineering next-generation learning : Proceedings of the 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, Wollongong, N.S.W., E1
SplashKit: a development framework for motivating and engaging students in introductory programming
J Renzella, A Cummaudo, A Cain, J Grundy, J Meyers
(2018), pp. 40-47, IEEE TALE 2018 : Engineering next-generation learning : Proceedings of the 2018 IEEE International Conference on Teaching, Assessment, and Learning for Engineering, Wollongong, N.S.W., E1
C Law, J Grundy, A Cain, V Vasa, A Cummaudo
(2017), pp. 1-10, Proceedings of the Nineteenth Australiasian Computing Education Conference (ACE 2017), Geelong, Victoria, E1
Funded Projects at Deakin
Other Public Sector Funding
Context Aware Search
Dr Antonio Giardina, Prof Kon Mouzakis, Prof Rajesh Vasa, Dr Rena Logothetis, Dr Alex Cummaudo
DSTO Grant - Research - Defence Science & Technology Organisation
- 2022: $107,288
- 2021: $125,550
Supervisions
No completed student supervisions to report