Profile image of Kien Do

Dr Kien Do



Research Fellow


Applied Artificial Intel Inst




Geelong Waurn Ponds Campus

Research interests

Adversarial Learning, Generative Models, Self-supervised Learning, Representation Learning, Causal Inference


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Unsupervised Image Segmentation with Robust Virtual Class Contrast

Khang Nguyen, Kien Do, Truong Vu, Khoat Than

(2023), Vol. 173, pp. 10-16, Pattern Recognition Letters, Amsterdam, The Netherlands, C1

journal article

Causal Inference via Style Transfer for Out-of-distribution Generalisation

Toan Nguyen, Kien Do, Duc Nguyen, Bao Duong, Thin Nguyen

(2023), pp. 1-19, KDD 2023 : Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Long Beach, California, E1


TrojanModel: A Practical Trojan Attack against Automatic Speech Recognition Systems

W Zong, Y Chow, W Susilo, K Do, S Venkatesh

(2023), Vol. 2023-May, pp. 1667-1683, Proceedings - IEEE Symposium on Security and Privacy, E1


Memory-Augmented Theory of Mind Network

D Nguyen, P Nguyen, H Le, K Do, S Venkatesh, T Tran

(2023), Vol. 37, pp. 11630-11637, Proceedings of the 37th AAAI Conference on Artificial Intelligence, AAAI 2023, E1


Towards Effective and Robust Neural Trojan Defenses via Input Filtering

K Do, H Harikumar, H Le, D Nguyen, T Tran, S Rana, D Nguyen, W Susilo, S Venkatesh

(2022), Vol. 13665 LNCS, pp. 283-300, ECCV 2022 : Proceedings of the 17th European Conference on Computer Vision, Tel Aviv, Israel, E1


Semi-Supervised Learning with Variational Bayesian Inference and Maximum Uncertainty Regularization

Kien Do, Truyen Tran, Svetha Venkatesh

(2021), Vol. 35, pp. 7236-7244, AAAI 2021 : Proceedings of the 35th AAAI Conference on Artificial Intelligence, Virtual Event, E1


DeepProcess: Supporting Business Process Execution Using a MANN-Based Recommender System

A Khan, H Le, K Do, T Tran, A Ghose, H Dam, R Sindhgatta

(2021), Vol. 13121, pp. 19-33, ICSOC 2021 : Proceedings of the 19th Service-Oriented Computing Iternational Computing, Virtual Event, E1


Unsupervised Anomaly Detection on Temporal Multiway Data

D Nguyen, P Nguyen, K Do, S Rana, S Gupta, T Tran

(2020), pp. 1059-1066, SSCI 2020 : Proceedings of the 2020 IEEE Symposium Series on Computational Intelligence, Canberra, Australian Capital Territory, E1


Attentional multilabel learning over graphs: a message passing approach

K Do, T Tran, T Nguyen, S Venkatesh

(2019), Vol. 108, pp. 1757-1781, Machine Learning, New York, N.Y., C1

journal article

Graph transformation policy network for chemical reaction prediction

K Do, T Tran, S Venkatesh

(2019), pp. 750-760, KDD 2019 : Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, Anchorage, Alaska, E1


Energy-based anomaly detection for mixed data

K Do, T Tran, S Venkatesh

(2018), Vol. 57, pp. 413-435, Knowledge and Information Systems, C1

journal article

Knowledge graph embedding with multiple relation projections

K Do, T Tran, S Venkatesh

(2018), pp. 332-337, ICPR 2018: Proceedings of the 24th International Conference on Pattern Recognition, Beijing, China, E1


Outlier detection on mixed-type data: an energy-based approach

D Do, D DO, T Tran, D Phung, S Venkatesh

(2016), Vol. 10086, pp. 111-125, ADMA 2016 : Proceedings of the 12th International Conference of Advanced Data Mining and Applications, Gold Coat, Queensland, E1


Funded Projects at Deakin

No Funded Projects at Deakin found


No completed student supervisions to report