Biography
Dr Ye Zhu is a senior lecturer of computer science at the School of Information Technology at Deakin University. He is also the Data to Intelligence (D2i) Research Centre HDR coordinator and Master of Data Science Course CPL Officer. He received a PhD degree in Artificial Intelligence with a Mollie Holman Medal for the best doctoral thesis of the year from Monash University in 2017. Dr Zhu joined Deakin University as a post-doc research fellow in complex system data analytics in July 2017 and then became a lecturer in Feb 2019. Dr Zhu is an IEEE senior member and ACM member.
His research works focus on clustering analysis, anomaly detection, similarity learning and their applications for pattern recognition. He has secured several research grants of around AUD$640,000 in total for interdisciplinary and industrial research. Dr Zhu has published over 40 papers in top-tier conferences and journals, including SIGKDD, VLDB, ICML, IJCAI, AAAI, PAKDD, AIJ, ISJ, TKDE, PRJ, JAIR and MLJ. He has served as Program Chair and Program Committee for many top international conferences, such as SIGKDD, AAAI and IJCAI. In addition, he recently conducted several tutorials/workshops about anomaly detection at leading computer science conferences such as KDD22, IJCAI23, PAKDD23, ECML23 and WACV24. He obtained both an Early Career Researcher Award and a Teaching and Learning Award at the School of IT recently.
Read more on Ye's profileResearch interests
Clustering analysis
Anomaly detection
Similarity learning
Unsupervised learning
Units taught
SIT718: Real World Analytics
SIT741: Statistical Data Analysis
SIT742: Modern Data Science
Knowledge areas
Data Mining, Machine Learning, Pattern Recognition
Conferences
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
International Conference on Very Large Databases
International Joint Conference on Artificial Intelligence
AAAI Conference on Artificial Intelligence
International Conference on Machine Learning
Pacific-Asia Conference on Knowledge Discovery and Data Mining
Research groups
Data Analytics Research Lab (DARL)
https://blogs.deakin.edu.au/darl
Data to Intelligence Research Centre (D2I)
https://data2intelligence.deakin.edu.au/
Awards
Mollie Holman Medal for the best doctoral thesis of the year from Monash University in 2017.
School of Information Technology Research Award from Deakin University in 2020.
School of Information Technology Teaching and Learning Award from Deakin University in 2021.
School of Information Technology Leadership Award from Deakin University in 2022.
Publications
A multimodal fusion network with attention mechanisms for visual-textual sentiment analysis
C Gan, X Fu, Q Feng, Q Zhu, Y Cao, Y Zhu
(2024), Vol. 242, pp. 1-12, Expert Systems With Applications, Amsterdam, The Netherlands, C1
Ripple Knowledge Graph Convolutional Networks for Recommendation Systems
C Li, Y Cao, Y Zhu, D Cheng, C Li, Y Morimoto
(2024), Machine Intelligence Research, C1
Automation and Orchestration of Zero Trust Architecture: Potential Solutions and Challenges
Y Cao, S Pokhrel, Y Zhu, R Doss, G Li
(2024), pp. 1-24, Machine Intelligence Research, Berlin, Germany, C1
Detecting Change Intervals with Isolation Distributional Kernel
Y Cao, Y Zhu, K Ting, F Salim, H Li, L Yang, G Li
(2024), Vol. 79, pp. 273-306, Journal of Artificial Intelligence Research, C1
A new distributional treatment for time series anomaly detection
K Ting, Z Liu, L Gong, H Zhang, Y Zhu
(2024), The VLDB journal, Berlin, Germany, C1
Distribution-Based Trajectory Clustering
Z Wang, Y Zhu, K Ting
(2024), pp. 1379-1384, ICDM 2023 : Proceedings of the IEEE International Conference on Data Mining 2023, Shanghai, China, E1
A novel feature-based framework enabling multi-type DDoS attacks detection
L Zhou, Y Zhu, Y Xiang, T Zong
(2023), Vol. 26, pp. 163-185, World Wide Web, C1
Clustering-enhanced stock price prediction using deep learning
M Li, Y Zhu, Y Shen, M Angelova
(2023), Vol. 26, pp. 207-232, World Wide Web, Berlin, Germany, C1
Modelling host population support for combat adversaries
M Zuparic, S Shelyag, M Angelova, Y Zhu, A Kalloniatis
(2023), Vol. 74, pp. 928-943, Journal of the Operational Research Society, London, Eng., C1
`Friend or foe' and decision making initiative in complex conflict environments
Mathew Zuparic, Sergiy Shelyag, Maia Angelova, Ye Zhu, Alexander Kalloniatis
(2023), Vol. 18, pp. e0281169-e0281169, PLOS ONE, United States, C1
The Impact of Isolation Kernel on Agglomerative Hierarchical Clustering Algorithms
Xin Han, Ye Zhu, Kai Ting, Gang Li
(2023), Vol. 139, pp. 1-17, Pattern Recognition, Amsterdam, The Netherlands, C1
CFNet: Facial expression recognition via constraint fusion under multi-task joint learning network
Junhao Xiao, Chenquan Gan, Qingyi Zhu, Ye Zhu, Gang Liu
(2023), Vol. 141, pp. 1-12, Applied Soft Computing, Amsterdam, The Netherlands, C1
Convolutional autoencoder based on latent subspace projection for anomaly detection
Qien Yu, Chen Li, Ye Zhu, Takio Kurita
(2023), Vol. 214, pp. 48-59, Methods, Amsterdam, The Netherlands, C1
Anomaly detection of vectorized time series on aircraft battery data
Moting Su, Wenjie Zhao, Ye Zhu, Donglan Zha, Yushu Zhang, Peng Xu
(2023), Vol. 227, pp. 1-10, Expert Systems with Applications, Amsterdam, The Netherlands, C1
An overview of clustering methods with guidelines for application in mental health research
Caroline Gao, Dominic Dwyer, Ye Zhu, Catherine Smith, Lan Du, Kate Filia, Johanna Bayer, Jana Menssink, Teresa Wang, Christoph Bergmeir, Stephen Wood, Sue Cotton
(2023), Vol. 327, pp. 1-28, Psychiatry Research, Amsterdam, The Netherlands, C1
Kernel-based clustering via Isolation Distributional Kernel
Y Zhu, K Ting
(2023), Vol. 117, pp. 1-16, Information Systems, Amsterdam, The Netherlands, C1
Mitigating the Impact of a False Message Through Sequential Release of Clarifying Messages
K Huang, X Yang, L Yang, Y Zhu, G Li
(2023), pp. 1-14, IEEE Transactions on Network Science and Engineering, Piscataway, N.J., C1
C Gan, A Liu, Q Zhu, Y Zhu, Y Xiang, J Liu
(2023), Vol. 237, pp. 1-12, Computer Networks, Amsterdam, The Netherlands, C1
Image Anomaly Detection With Semantic- Enhanced Augmentation and Distributional Kernel
M Wang, Y Zhu, G Li, G Liu, B Yang
(2023), pp. 163-170, HPCC/DSS/SmartCity/DependSys 2022 : Proceedings of the 2022 IEEE 24th Int Conf on High Performance Computing & Communications; 8th Int Conf on Data Science & Systems; 20th Int Conf on Smart City; 8th Int Conf on Dependability in Sensor, Cloud & Big Data Systems & Application Combined Conference, Hainan, China, E1
An Improved Visual Assessment with Data-Dependent Kernel for Stream Clustering
Baojie Zhang, Yang Cao, Ye Zhu, Sutharshan Rajasegarar, Hong Li, Maia Angelova Turkedjieva, Gang Li
(2023), Vol. 13935, pp. 197-209, PAKDD 2023 : Advances in Knowledge Discovery and Data Mining: 27th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2023, Osaka, Japan, May 25–28, 2023, Proceedings, Part I, Osaka, Japan, E1
Kernel-Based Feature Extraction for Time Series Clustering
Yuhang Liu, Yi Zhang, Yang Cao, Ye Zhu, Nayyar Zaidi, Chathu Ranaweera, Gang Li, Zhu Qingyi
(2023), pp. 276-283, KSEM 2023 : Proceedings of the 16th International Conference on Knowledge Science, Engineering and Management, Guangzhou, China, E1
Towards a Persistence Diagram that is Robust to Noise and Varied Densities
Hang Zhang, Hang Zhang, Kaifeng Zhang, Kaifeng Zhang, Kai Ting, Kai Ting, Ye Zhu, Ye Zhu
(2023), pp. 1-21, ICML 2023 : Proceedings of the 40th International Conference on Machine Learning, Honolulu, Hawaii, E1
An Enhanced Distributed Algorithm for Area Skyline Computation Based on Apache Spark
C Li, Y Cao, Y Zhu, J Zhang, A Annisa, D Cheng, H Tang, S Jiang, K Maruyama, Y Morimoto
(2023), Vol. 14120 LNAI, pp. 35-43, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), E1
Hierarchical clustering that takes advantage of both density-peak and density-connectivity
Y Zhu, K Ting, Y Jin, M Angelova
(2022), Vol. 103, Information Systems, C1
Weighted dynamic time warping for traffic flow clustering
M Li, Y Zhu, T Zhao, M Angelova
(2022), Vol. 472, pp. 266-279, Neurocomputing, Amsterdam, The Netherlands, C1
K Ting, J Wells, Y Zhu
(2022), pp. 1-12, IEEE Transactions on Knowledge and Data Engineering, Piscataway, N.J., C1
A feature selection-based method for DDoS attack flow classification
Lu Zhou, Ye Zhu, Tianrui Zong, Yong Xiang
(2022), Vol. 132, pp. 67-79, Future Generation Computer Systems: the international journal of grid computing: theory, methods and applications, C1
K Ting, T Washio, J Wells, H Zhang, Y Zhu
(2022), Vol. 65, Knowledge and Information Systems, C1
Differentiating acute from chronic insomnia with machine learning from actigraphy time series data
S Rani, S Shelyag, C Karmakar, Ye Zhu, R Fossion, J Ellis, S Drummond, M Angelova
(2022), Vol. 2, pp. 1-15, Frontiers in Network Physiology, Lausanne, Switzerland, C1
A Comprehensive Feature Importance Evaluation for DDoS Attacks Detection
Lu Zhou, Ye Zhu, Yong Xiang
(2022), pp. 353-367, ADMA 2022 : Proceedings of the 17th Advanced Data Mining and Applications International Conference 2022, Sydney, N.S.W., E1
Identification of Stock Market Manipulation with Deep Learning
Jillian Tallboys, Ye Zhu, Sutharshan Rajasegarar
(2022), Vol. 13087, pp. 408-420, Advanced Data Mining and Applications, Sydney, Australia, E1
Streaming Hierarchical Clustering Based on Point-Set Kernel
X Han, Y Zhu, K Ting, D Zhan, G Li
(2022), pp. 525-533, KDD '22 : Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining 2022, Washington, D.C., E1
A New Distributional Treatment for Time Series and An Anomaly Detection Investigation
K Ting, Z Liu, H Zhang, Y Zhu
(2022), Vol. 15, pp. 2321-2333, VLDB 2022 : Proceedings of the International Conference on Very Large Databases Endowment 2022, Sydney, N.S.W., E1
Anomaly detection of aircraft lead-acid battery
W Zhao, Y Zhang, Y Zhu, P Xu
(2021), Vol. 37, pp. 1186-1197, Quality and Reliability Engineering International, C1
M Zuparic, M Angelova, Y Zhu, A Kalloniatis
(2021), Vol. 95, Communications in Nonlinear Science and Numerical Simulation, C1
CDF Transform-and-Shift: An effective way to deal with datasets of inhomogeneous cluster densities
Y Zhu, K Ting, M Carman, M Angelova
(2021), Vol. 117, Pattern Recognition, C1
S Kusmakar, C Karmakar, Y Zhu, S Shelyag, S Drummond, J Ellis, M Angelova
(2021), Vol. 8, Royal Society Open Science, England, C1
Improving the Effectiveness and Efficiency of Stochastic Neighbour Embedding with Isolation Kernel
Ye Zhu, Kai Ting
(2021), Vol. 71, pp. 667-695, Journal of Artificial Intelligence Research, Palo Alto, Calif., C1
Systematic evaluation of abnormal detection methods on gas well sensor data
Xichen Tang, Jinlong Wang, Ye Zhu, Robin Doss, Xin Han
(2021), pp. 1-6, ISCC 2021 : Proceedings of the 2021 IEEE Symposium on Computers and Communications, Athens, Greece, E1
Cloud-assisted privacy-conscious large-scale Markowitz portfolio
Y Zhang, J Jiang, Y Xiang, Y Zhu, L Wan, X Xie
(2020), Vol. 527, pp. 548-559, Information sciences, Amsterdam, The Netherlands, C1
Density estimates on the unit simplex and calculation of the mode of a sample
M Angelova, G Beliakov, S Shelyag, Y Zhu
(2020), Vol. 35, pp. 850-868, International Journal of Intelligent Systems, C1
Machine Learning Enabled Team Performance Analysis in the Dynamical Environment of Soccer
S Kusmakar, S Shelyag, Y Zhu, D Dwyer, P Gastin, M Angelova
(2020), Vol. 8, pp. 90266-90279, IEEE Access, C1
Automated Method for Detecting Acute Insomnia Using Multi-Night Actigraphy Data
M Angelova, C Karmakar, Y Zhu, S Drummond, J Ellis
(2020), Vol. 8, pp. 74413-74422, IEEE Access, C1
A technical survey on statistical modelling and design methods for crowdsourcing quality control
Y Jin, M Carman, Y Zhu, Y Xiang
(2020), Vol. 287, Artificial Intelligence, C1
K Ting, Y Zhu, M Carman, Y Zhu, T Washio, Z Zhou
(2019), Vol. 108, pp. 331-376, Machine learning, New York, N.Y., C1
Data-driven natural gas spot price forecasting with least squares regression boosting algorithm
M Su, Z Zhang, Y Zhu, D Zha
(2019), Vol. 12, Energies, C1
Commutative fragile zero-watermarking and encryption for image integrity protection
M Li, D Xiao, Y Zhu, Y Zhang, L Sun
(2019), Vol. 78, pp. 22727-22742, Multimedia tools and applications, New York, N.Y., C1
Data driven natural gas spot price prediction models using machine learning methods
M Su, Z Zhang, Y Zhu, D Zha, W Wen
(2019), Vol. 12, Energies, C1
Density-based clustering using approximate natural neighbours
Maia Angelova, Gleb Beliakov, Ye Zhu
(2019), Vol. 85, APPLIED SOFT COMPUTING, C1
Nearest-neighbour-induced isolation similarity and its impact on density-based clustering
Xiaoyu Qin, Kai Ting, Ye Zhu, Vincent Lee
(2019), Vol. 33, pp. 4755-4762, Proceedings of the Combined Conferences : 33rd AAAI Conference on Artificial Intelligence / 31st Innovative Applications of Artificial Intelligence Conference / 9th AAAI Symposium on Educational Advances in Artificial Intelligence, Honolulu, Hawaii, E1
Isolation-based anomaly detection using nearest-neighbor ensembles
T Bandaragoda, K Ting, D Albrecht, F Liu, Y Zhu, J Wells
(2018), Vol. 34, pp. 968-998, Computational intelligence, Chichester, Eng., C1
Local contrast as an effective means to robust clustering against varying densities
B Chen, K Ting, T Washio, Y Zhu
(2018), Vol. 107, pp. 1621-1645, Machine learning, New York, N.Y., C1
Grouping points by shared subspaces for effective subspace clustering
Y Zhu, K Ting, M Carman
(2018), Vol. 83, pp. 230-244, Pattern recognition, Amsterdam, The Netherlands, C1
User Activity Pattern Analysis in Telecare Data
M Angelova, J Ellman, H Gibson, P Oman, S Rajasegarar, Y Zhu
(2018), Vol. 6, pp. 33306-33317, IEEE Access, C1
Leveraging label category relationships in multi-class crowdsourcing
Y Jin, L Du, Y Zhu, M Carman
(2018), Vol. 10938, pp. 128-140, PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Melbourne, Victoria, E1
A distance scaling method to improve density-based clustering
Y Zhu, K Ting, M Angelova
(2018), Vol. 10939, pp. 389-400, PAKDD 2018 : Advances in Knowledge Discovery and Data Mining : Proceedings of 22nd Pacific-Asia Conference, Melbourne, Victoria, E1
Distinguishing question subjectivity from difficulty for improved crowdsourcing
Y Jin, Mark Carman, Ye Zhu, Wray Buntine
(2018), Vol. 95, pp. 192-207, ACML 2018 : Proceedings of the 10th Asian Conference on Machine Learning Research, Beijing, China, E1
Density-ratio based clustering for discovering clusters with varying densities
Y Zhu, K Ting, M Carman
(2016), Vol. 60, pp. 983-997, Pattern recognition, Amsterdam, The Netherlands, C1-1
K Ting, Y Zhu, M Carman, Y Zhu, Z Zhou
(2016), pp. 1205-1214, KDD 2016 : Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, San Francisco, California, E1-1
Bivariate probability-based anomaly detection
H Lou, Y Zhu
(2015), pp. 1-6, BESC 2014 : International Conference on Behavior, Economic and Social Computing (BESC), Shanghai, China, E1-1
Funded Projects at Deakin
Other Public Sector Funding
Multiple networks in dynamical combat modelling and critical phenomena.
Prof Maia Angelova Turkedjieva, Dr Ye Zhu
Department of Defence
- 2018: $12,778
Intelligent Sensor processing for Enhancing Defence Decision Support.
Prof Maia Angelova Turkedjieva, Dr Ye Zhu, A/Prof Tim Wilkin, Dr Dan Dwyer, Dr Alex Kalloniatsis, Prof Paul Gastin
Defence Science Institute
- 2019: $30,000
- 2018: $20,000
Adversarial decision making networks and directed fires with non-combatant populations.
Prof Maia Angelova Turkedjieva, Dr Ye Zhu, Dr Sergiy Shelyag
DSTO Grant - Research - Defence Science & Technology Organisation
- 2019: $30,000
Modelling networked combat, adversarial C2 and information operations.
Prof Maia Angelova Turkedjieva, Dr Sergiy Shelyag, Dr Ye Zhu
Department of Defence
- 2020: $30,000
AI-empowered photovoltaic systems for sustainable buildings.
A/Prof Hong Xian Li, Dr Ye Zhu, Prof Tony Arnel
Innovation Connections
- 2024: $24,980
Industry and Other Funding
Explore the association rules between the fundamentals and short-term price dynamics
Dr Ye Zhu
MITA Capital Management LLC
- 2021: $21,384
AI-empowered photovoltaic systems for sustainable buildings.
A/Prof Hong Xian Li, Dr Ye Zhu, Prof Tony Arnel
IAPMO Oceana Pty Ltd
- 2023: $49,960
Other Funding Sources
Augmenting Cyber Defence Capability (ACDC).
Prof Gang Li, Dr Luxing Yang, Dr Nayyar Zaidi, Dr Ye Zhu, Prof Rajesh Vasa, Prof Kon Mouzakis, Prof Robin Ram Mohan Doss, Dr Thanh Thi Nguyen
Cyber Security Research Centre Limited
- 2024: $39,000
- 2023: $156,000
- 2022: $32,199
Socrates: Software Security with a focus on critical technologies.
A/Prof Lei Pan, Dr Syed Wajid Ali Shah, Prof Robin Ram Mohan Doss, Dr Zubair Baig, Prof Jemal Abawajy, Prof Shiri Krebs, Dr Jayson Lamchek, Dr Shamsul Huda, Dr Muna Al-Hawawreh, Dr Naeem Syed, Dr Jack Li, Dr Ye Zhu, Dr Frank Jiang, A/Prof William Yeoh, Prof Chang-Tsun Li, A/Prof Lennon Chang, Prof Patrick Emerton, Dr Hourieh Khalajzadeh, Dr Van-Hau Trieu, Dr Yanjun Zhang, Dr Leo Zhang
Cyber Security Research Centre Limited
- 2024: $60,488
- 2023: $120,976
Supervisions
Man Li
Thesis entitled: Weighted Dynamic Time Warping for Time Series Analysis
Doctor of Philosophy (Information Technology), School of Information Technology