Tung Kieu

💻 Assistant Professor

🏛 Department of Computer Science
The Technical Faculty of IT and Design
Aalborg University

🚪 Office 3.2.03
Selma Lagerlöfs Vej 300
DK-9220, Aalborg Øst, Denmark

📧 tungkvt at cs dot aau dot dk
📧 kvttung at gmail dot com

Profile

I am an Assistant Professor in Department of Computer Science at Aalborg University. I am a faculty member in Center for Data-Intensive Systems. I am also affiliated with the department's team on Artificial Intelligence and Machine Learning and the university's Center on AI for the People.

I obtained my Ph.D. degree from Aalborg University in April 2021 under supervision of Prof. Christian S. Jensen and Prof. Bin Yang. During April 2021 to May 2021, I was a Research Assistant at Aalborg University. During June 2021 to August 2021, I was a Postdoctoral Fellow at Aalborg University. All the time, I have worked in the Data-Intensive Systems (Daisy) group headed by Prof. Christian S. Jensen.

Research Interests

Data mining and machine learning, in particular, on spatio-temporal data, time series, graphs, and uncertain data.

Education

B.Sc. in Computer Science, University of Science, Vietnam National University, Ho Chi Minh City, Vietnam.
B.Eng. in Civil Engineering, University of Architecture, Ho Chi Minh City, Vietnam.
M.Sc. in Computer Science, University of Science, Vietnam National University, Ho Chi Minh City, Vietnam.
Ph.D. in Computer Science, Aalborg University, Aalborg, Denmark.

Work Experience

Data Entry Operator at FTA Research & Consultant, Ho Chi Minh City, Vietnam.
Web Developer at BeRich.vn, Ho Chi Minh City, Vietnam.
Data Warehouse Specialist at FPT, Ho Chi Minh City, Vietnam.
Database Specialist at FPT, Ho Chi Minh City, Vietnam.
Researcher at Aalborg University, Aalborg, Denmark.
Assistant Professor at Aalborg University, Aalborg, Denmark.

Publication

Huy Le, Tung Kieu, Anh Nguyen, and Ngan Le. WAVER: Writing-style Agnostic Video Retrieval via Distilling Vision-Language Models Through Open-Vocabulary Knowledge [pdf].
ICASSP 2024
David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, and Christian S. Jensen. LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation [pdf].
SIGMOD 2023
Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Xuanyi Dong, Shirui Pan, and Bin Yang. Triformer: Triangular, Variable-Specific Attention for Long Sequence Multivariate Time Series Forecasting [pdf].
IJCAI 2022
Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Shirui Pan, and Bin Yang. Towards Spatio-Temporal Aware Traffic Time Series Forecasting [pdf].
ICDE 2022
Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Yan Zhao, Feiteng Huang, and Kai Zheng. Robust and Explainable Autoencoders for Time Series Outlier Detection [pdf].
ICDE 2022
Tung Kieu, Bin Yang, Chenjuan Guo, Razvan-Gabriel Cirstea, Yan Zhao, Yale Song, and Christian S. Jensen. Anomaly Detection in Time Series with Robust Variational Quasi-Recurrent Autoencoders [pdf].
ICDE 2022
Yan Zhao, Xuanhao Chen, Liwei Deng, Tung Kieu, Chenjuan Guo, Bin Yang, Kai Zheng, and Christian S. Jensen. Outlier Detection for Streaming Task Assignment in Crowdsourcing [pdf].
WWW 2022
David Campos, Tung Kieu, Chenjuan Guo, Feiteng Huang, Kai Zheng, Bin Yang, and Christian S. Jensen. Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles [pdf].
VLDB 2022
Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Bin Yang, and Sinno Jialin Pan. EnhanceNet: Plugin Neural Networks for Enhancing Correlated Time Series Forecasting [pdf].
ICDE 2021
Tung Kieu, Bin Yang, Chenjuan Guo, and Christian S. Jensen. Outlier Detection for Time Series with Recurrent Autoencoder Ensembles [pdf].
IJCAI 2019
Tung Kieu, Bin Yang, Chenjuan Guo, and Christian S. Jensen. Distinguishing Trajectories from Different Drivers using Incompletely Labeled Trajectories [pdf].
CIKM 2018
Tung Kieu, Bin Yang, and Christian S. Jensen. Outlier Detection for Multidimensional Time Series Using Deep Neural Networks [pdf].
MDM 2018
Tung Kieu, Bay Vo, Tuong Le, Zhi-Hong Deng, and Bac Le. Mining Top-k Co-occurrence Items with Sequential Pattern [pdf].
Expert Syst. Appl. 85 2017

Preprint

Huy Le, Tung Kieu, Anh Nguyen, and Ngan Le. WAVER: Writing-style Agnostic Video Retrieval via Distilling Vision-Language Models Through Open-Vocabulary Knowledge [pdf].
David Campos, Miao Zhang, Bin Yang, Tung Kieu, Chenjuan Guo, and Christian S. Jensen. LightTS: Lightweight Time Series Classification with Adaptive Ensemble Distillation--Extended Version [pdf].
Tung Kieu, Bin Yang, Chenjuan Guo, Christian S. Jensen, Yan Zhao, Feiteng Huang, and Kai Zheng. Robust and Explainable Autoencoders for Time Series Outlier Detection--Extended Version [pdf].
Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Xuanyi Dong, Shirui Pan, and Bin Yang. Triformer: Triangular, Variable-Specific Attentions for Long Sequence Multivariate Time Series Forecasting--Extended Version [pdf].
Razvan-Gabriel Cirstea, Tung Kieu, Chenjuan Guo, Shirui Pan, and Bin Yang. Towards Spatio-Temporal Aware Traffic Time Series Forecasting--Extended Version [pdf].
David Campos, Tung Kieu, Chenjuan Guo, Feiteng Huang, Kai Zheng, Bin Yang, and Christian S. Jensen. Unsupervised Time Series Outlier Detection with Diversity-Driven Convolutional Ensembles--Extended Version [pdf].
Yan Zhao, Liwei Deng, Xuanhao Chen, Chenjuan Guo, Bin Yang, Tung Kieu, Feiteng Huang, Torben Bach Pedersen, Kai Zheng, and Christian S. Jensen. A Comparative Study on Unsupervised Anomaly Detection for Time Series: Experiments and Analysis [pdf].

Teaching

Courses

Advanced Algorithm (shared with Prof. Bin Yang and Prof. Chenjuan Guo).
Algorithms and Computability (shared with Prof. Bin Yang, Prof. Dalin Zhang, and Prof. Alvaro Torralba).
Algorithms and Satisfiability (shared with Prof. Bin Yang, Prof. Dalin Zhang, and Prof. Alvaro Torralba).

Supervision

Software 5 (SW5).
Software 6 (SW6).
Specialization course in Database Technology (SpDT).
Master Thesis (shared with Prof. Bin Yang).

Teaching Assistant

Algorithms and Data Structures (shared with Sean Bin Yang).
Advanced Algorithm (shared with Sean Bin Yang).
Algorithms and Computability (shared with Jákup Odssonur Svöðstein).
Algorithms and Satisfiability (shared with Jákup Odssonur Svöðstein).

Collaboration

Collaborating with TADAA! (in aSTEP project).
Collaborating with the BioX (in aSTEP project).
Collaborating with Huawei (in Huawei project)

Students

M.Sc.

David Campos (co-supervised with Prof. Bin Yang)
Mik Christensen (co-supervised with Prof. Bin Yang)

Ph.D.

David Campos (co-supervised with Prof. Bin Yang)

Scientific Services

Conferences

ACM SIGKDD Conference on Knowledge Discovery and Data Mining (SIGKDD)
Conference on Neural Information Processing Systems (NEURIPS)
International Joint Conference on Artificial Intelligence (IJCAI)
AAAI Conference on Artificial Intelligence (AAAI)
International Conference on Very Large Data Bases (VLDB)
IEEE International Conference on Data Engineering (ICDE)
ACM International Conference on Information and Knowledge Management (CIKM)
ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems (SIGSPATIAL/GIS)
International Conference on Advanced Data Mining and Applications (ADMA)
APWeb-WAIM International Joint Conference on Web and Big Data (APWEB-WAIM)
IEEE International Conference on Mobile Data Management (MDM)

Journals

Journal of Artificial Intelligence Research (JAIR)
ACM Transactions on Information Systems (TOIS)
IEEE Transactions on Neural Networks and Learning Systems (TNNLS)
IEEE Transactions on Knowledge and Data Engineering (TKDE)
IEEE Transactions on Intelligent Transportation Systems (TITS)
IEEE Transactions on Network Science and Engineering (TNSE)
IEEE Transactions on Industrial Informatics (TII)
Data Mining and Knowledge Discovery (DMKD)
Pattern Recognition
Neural Networks
Machine Learning
Expert Systems with Applications
Neural Processing Letters
IEEE Access

tungk / tungk.github.io