Projects per year
Personal profile
Biography
A/Prof. Ehsan Abbasnejad is a leading researcher in machine learning, specialising in foundational AI for vision and language tasks. He is currently with the Department of Data Science and Artificial Intelligence and serves as an Affiliate Associate Professor at the Australian Institute for Machine Learning (AIML) at the University of Adelaide, where he was previously a Future Making Fellow. He also held the role of Principal Researcher at the Centre for Augmented Reasoning (CAR).
In 2024, he was recognised as a finalist for Researcher of the Year at the Australian AI Awards. His research has been instrumental in advancing AI, leading several major projects, including those funded by the Australian Research Council. With extensive industry collaborations across agriculture, energy, healthcare, and sports, his work has driven impactful, real-world AI solutions.
A/Prof. Abbasnejad has played a key role in globally recognised teams, winning multiple competitions in computer vision, mining, and manufacturing. His industry experience includes research roles with Microsoft Research, Xerox Research, and NEC Labs America, where he contributed to cutting-edge AI advancements.
Please visit https://ehsanabb.github.io for more details.
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
Education/Academic qualification
Computer Science, PhD, Australian National University (ANU)
Award Date: 16 Jul 2017
Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
Projects
- 1 Active
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Grid Guru: Grid Guru - Leveraging AI-Driven Grid Optimisation
Wagner, M. (Primary Chief Investigator (PCI)), Abbasnejad, E. (Chief Investigator (CI)), Mak, T. (Chief Investigator (CI)), Shareghi Nojehdeh, E. (Chief Investigator (CI)), Wang, H. (Chief Investigator (CI)), Cui, H. (Chief Investigator (CI)), Goodwin, S. (Chief Investigator (CI)) & Lipscombe, S. (Project Manager)
Monash University – Internal Faculty Contribution, GridGuru Solutions Pty Ltd, Electricity Transmission Ministerial Holding Corporation (trading as Transgrid)
16/07/25 → 15/07/26
Project: Research
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Bayesian Learned Models Can Detect Adversarial Malware for Free
Doan, B. G., Nguyen, D. Q., Montague, P., Abraham, T., De Vel, O., Camtepe, S., Kanhere, S. S., Abbasnejad, E. & Ranasinghe, D. C., 2024, Computer Security – ESORICS 2024 - 29th European Symposium on Research in Computer Security Bydgoszcz, Poland, September 16–20, 2024 Proceedings, Part I. Garcia-Alfaro, J., Kozik, R., Choraś, M. & Katsikas, S. (eds.). Cham Switzerland: Springer, p. 45-65 21 p. (Lecture Notes in Computer Science; vol. 14982).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
2 Citations (Scopus) -
BLURD: Benchmarking and Learning using a Unified Rendering and Diffusion Model
Repasky, B., Dick, A. & Abbasnejad, E., 2024, NeurIPS Proceedings - Advances in Neural Information Processing Systems 37 (NeurIPS 2024). Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J. & Zhang, C. (eds.). San Diego CA USA: Neural Information Processing Systems (NIPS), 16 p. (Advances in Neural Information Processing Systems; vol. 37).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access -
BRUSLEATTACK: A QUERY-EFFICIENT SCORE-BASED BLACK-BOX SPARSE ADVERSARIAL ATTACK
Vo, V. Q., Abbasnejad, E. & Ranasinghe, D. C., 2024, The Twelfth International Conference on Learning Representations. Fragkiadaki, K., Emtiyaz Khan, M., Chaudhuri, S. & Sun, Y. (eds.). USA: International Conference on Learning Representations (ICLR), 38 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access5 Citations (Scopus) -
Knowledge Composition using Task Vectors with Learned Anisotropic Scaling
Zhang, F. Z., Albert, P., Rodriguez-Opazo, C., van den Hengel, A. & Abbasnejad, E., 2024, NeurIPS Proceedings - Advances in Neural Information Processing Systems 37 (NeurIPS 2024). Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J. & Zhang, C. (eds.). San Diego CA USA: Neural Information Processing Systems (NIPS), 36 p. (Advances in Neural Information Processing Systems; vol. 37).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
Open Access2 Citations (Scopus) -
Modelling individual variation in human walking gait across populations and walking conditions via gait recognition
Duncanson, K. A., Horst, F., Abbasnejad, E., Hanly, G., Robertson, W. S. P. & Thewlis, D., 11 Dec 2024, In: Journal of the Royal Society, Interface. 21, 221, 15 p., 20240565.Research output: Contribution to journal › Article › Research › peer-review
Open AccessFile