Dr. Thanh Tam Nguyen
Dr. Thanh Tam Nguyen
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PhD@EPFL, Switzerland
Postdoc@International Leibniz Future Laboratory for Artificial Intelligence, Germany
Fellow of Higher Education Academy (FHEA)
Lecturer (Assistant Professor), Griffith University, Australia
Dr. Thanh Tam Nguyen is a lecturer (assistant professor) at Griffith University and a Fellow of Higher Education Academy (FHEA). He earned his PhD degree in Computer Science from EPFL (top-8 world universities in computer science by QS Ranking 2019), Switzerland in 2019. His research interests include Big Data, Social Network Mining, Stream Processing, Privacy-Preserving ML, and Recommender Systems, with special focus on Retrieval Engines, Trust Models, Explainable AI and Graph Neural Networks for data lakes, social networks, and event streams. He has published 70+ papers (40+ CORE A*, 15+ CORE A, 55+ as the first or corresponding author) in top-tier conferences (e.g. SIGMOD, VLDB, SIGIR, ICDE, IJCAI) and high-impact journals (e.g. VLDBJ, TKDE, Pattern Recognition, CSUR). He has served as a PC member for several A*/A conferences such as VLDB, WSDM, AAAI, IJCAI, TheWebConf (WWW), SIGIR, ICDE, KDD, EDBT, CIKM, and INTERSPEECH. He is a guest editor of IEEE Journal of Biomedical and Health Informatics, an area chair of ACL and EMNLP, a program chair of ADC and PDCAT, and a reviewer of CSUR, TKDE, JVLDB, TNNLS, Pattern Recognition, Information Sciences, etc. His research has attracted over 4600+ citations (h-index 35+).
Since 2020, he has been awarded over $1M in funding from government schemes (DFAT, A4I, AKF, etc.), industrial partners (CSIRO, Ubitech, Cybella, J&J, Phacogen, etc.) and international bodies (NAFOSTED, ETRI, KARI, KARN, SIU, etc.). His work on machine unlearning has been cited in the International AI Safety Report 2025 (chaired by Turing-award winner Yoshua Bengio and written by top 100 AI experts) as a pioneering paradigm to remove sensitive information or harmful data from trained AI models.
His research centers on advancing Big Data and Smart technologies by developing efficient algorithms that enhance data integration, processing, and analysis. He aims to bridge the gap between human insights and data models, ensuring transparency and trust in data-driven decisions. His work also explores the dynamic interactions within large-scale, multi-modal datasets, uncovering hidden patterns and trends in complex networked environments.
His collaborations include Prof. Karl Aberer (SWTR Fellow) at Ecole Polytechnique Federale de Lausanne (Switzerland), Prof. Wolfgang Nejdl (Acatech Fellow) at International Future Lab for AI, Prof. Björn W. Schuller (IEEE Fellow) at Imperial College London (UK), Prof. Matthias Weidlich (Fellow of the German Informatics Society) at Humboldt-Universität zu Berlin (Germany), Prof. Hongzhi Yin (ARC Future Fellow) at The University of Queensland, Prof. Xiaofang Zhou (IEEE Fellow) at Hong Kong University of Science and Technology, and Prof. Alan Wee-Chung Liew (Queensland Academy Fellow) at Griffith University.
Academic achievements
1. Advances the field of emergent trust management by developing models for early detection, minimal-effort validation, and efficient visualisation of misinformation on social media platforms: ICDE'15 (CORE A*, 94 citations), IJCAI'17 (CORE A*, 73 citations) TKDE'18 (IF 9.235, CORE A*, 74 citations), Information Fusion (IF 18.6, Top 3%), two VLDB'19 (CORE A*, 128 citations), SIGIR'20 (CORE A*), ICDE'22 (CORE A*), VLDBJ'22 (CORE A*, Q1), CVIU'22 (548 citations), CSUR'24 (CORE A*), TKDE'24 (CORE A*) etc.
Our modern society is struggling with an unprecedented amount of online misinformation, which does harm to democracy, economics, and cybersecurity. Journalism and politics have been impacted by misinformation on a global scale, with weakened public trust in governments seen during the Brexit referendum and viral fake election stories outperforming genuine news on social media during U.S. presidential election campaigns. Online misinformation also single-handedly caused $136.5 billion in losses in the stock market value through a single fake news about explosions in the White House.
Our works make significant contributions to the field by developing comprehensive models and methodologies for early detection, validation, and visualisation of misinformation on social media platforms. These advancements address key challenges in the timely and accurate debunking of misinformation, enhancing the effectiveness of misinformation management frameworks and providing valuable insights for future research and practical applications. Our works contribute to economic stability by preventing financial disruptions caused by misinformation, bolsters cybersecurity by addressing AI-driven threats, and safeguards public health by combating false health information. Additionally, the research provides valuable educational tools for promoting digital literacy and critical thinking, and aids media organizations in ensuring the accuracy and credibility of their reporting, thereby improving the quality of information available to the public.
Modeling Social Media Propagation of Fake News, Misinformation, Rumour, Propaganda, etc.
2. Develops user-centric systems, explainable AI techniques, and human-in-the-loop to enhance algorithmic accuracy to bridge the trust gap between humans and AI: KBS'24 (IF 8.8), WSDM'23 (COREA*, 33 citations), JBHI'23 (IF 7.7, CORE A*, Top 10%), Information Sciences'23 (IF 8.233, 37 citations), ESWA'22 (IF 8.665), SIGMOD'21 (COREA*, 40 citations), Information Systems'19 (CORE A*, 30 citations), ICDE'18 (CORE A*, 40 citations), VLDBJ'17 (CORE A*, 125 citations), WISE'13 (265 citations), etc.
Working with user-centric systems has been a long-time passion and one that I have championed since the beginning of my career. For example, one of my publications revolves around providing example-based explanations for streaming fraud detection on graphs, where we designed techniques to offer the best contextual explanations to get optimal user feedback without bias. I also worked on model-agnostic and diverse explanations for streaming rumour graphs, focusing on visualising these explanations and supporting information effectively. I was the first to propose and analyse the novel problem of leveraging human experts to improve the quality of algorithmic results, combining scarce expert knowledge with redundant crowd knowledge to resolve the trade-off between quality and scalability, an achievement that traditional approaches have struggled to match. Additionally, I developed techniques for example-based explanations with adversarial attacks for respiratory sound analysis, and real-time wildfire detection with semantic explanations, showcasing the necessity of explanation computing in many fields to bridge the trust gap between humans and AI. Our research fosters trust in AI by making it more transparent, supports informed policy recommendation, enhances public safety, and ensures AI systems are reliable and accurate, contributing to a more knowledgeable and resilient society.
Multi-dimension Explainable AI
3. Advances graph data management by developing superior unsupervised graph alignment and embedding techniques applied across various domains, including explainable AI, social media, and misinformation detection: TKDE'25 (IF 9.235, CORE A*), two TKDE'23 (71 citations), ICDE'23 (CORE A*), PR'22 (IF 8.518, CORE A*, 42 citations), ICDE'22, EMNLP'22 (CORE A*), TKDE'21 (81 citations), ICDE'21, ESWA'21 (61 citations), TOIS'21 (56 citations), ICDE'20 (115 citations), VLDBJ'17 (CORE A*), ICDE'14, SIGIR'13, etc.
My research has significantly advanced graph data management, developing an unsupervised graph alignment framework that outperforms supervised baselines without labels. I have also designed several streaming graph management methods, including vector-based indexing, cache management, and query streaming processing, and novel unsupervised graph embedding techniques for tasks like node classification, link prediction, subgraph isomorphism, and graph classification. Notably, I revolutionized subgraph isomorphisms for multiple graph queries under streaming settings, overcoming complex graph traversal challenges . My methods have been applied in explainable AI, social media, data filtering, and information retrieval. For instance, I developed a graph-based anomaly detection framework to detect misinformation like fake news and rumors, helping to restore public trust, demonstrating the efficacy of my graph-based approach in large-scale networks and systems. These advancements help create safer, more reliable digital environments and foster informed communities.
Holistic graph representation learning
Publications (see details here)
70. Thanh Tam Nguyen, Thanh Toan Nguyen, Matthias Weidlich, Jun Jo, Quoc Viet Hung Nguyen, Hongzhi Yin, Alan Wee-Chung Liew. Handling Low Homophily in Recommender Systems with Partitioned Graph Transformer. In TKDE 2025. (Funded by ARC)
69. Thanh Tam Nguyen, Thanh Trung Huynh, Zhao Ren, Phi Le Nguyen, Alan Wee-Chung Liew, Hongzhi Yin, Quoc Viet Hung Nguyen. A Survey of Machine Unlearning. In TIST 2025. (Funded by ARC)
68. Huu Tien Nguyen, Dac Thai Nguyen, Duc Nguyen The Minh, Trung Thanh Nguyen, Thao Nguyen Truong, Hieu Pham, Johan Barthelemy, Tran Minh Quan, Quoc Viet Hung Nguyen, Thanh Tam Nguyen, et al. Toward a Vision-Language Foundation Model for Medical Data: Multimodal Dataset and Benchmarks for Vietnamese PET/CT Report Generation. In NeurIPS 2025.
67. Dung Nguyen, Minh Khoi Ho, Huy Ta, Thanh Tam Nguyen, et al. Localizing Before Answering: A Benchmark for Grounded Medical Visual Question Answering. In IJCAI 2025.
66. Yi Chang, Zhao Ren, Zhonghao Zhao, Thanh Tam Nguyen, Kun Qian, Tanja Schultz, Bjorn W. Schuller. Breaking Resource Barriers in Speech Emotion Recognition via Data Distillation. In INTERSPEECH 2025.
65. Thanh Toan Nguyen, Quoc Viet Hung Nguyen, Thanh Tam Nguyen, Thanh Trung Huynh, Thanh Thi Nguyen, Matthias Weidlich, Hongzhi Yin. Manipulating Recommender Systems: A Survey of Poisoning Attacks and Countermeasures. In CSUR 2024. (Funded by ARC)
64. Thanh Tam Nguyen, Zhao Ren, Thanh Toan Nguyen, Jun Jo, Quoc Viet Hung Nguyen, Hongzhi Yin. Portable graph-based rumour detection against multi-modal heterophily. In KBS 2024
63. Chaoqun Yang, Wei Yuan, Liang Qu, Thanh Tam Nguyen. PDC-FRS: Privacy-preserving Data Contribution for Federated Recommender System. In ADMA 2024
62. Thanh Trung Huynh, Trong Bang Nguyen, Thanh Toan Nguyen, Phi Le Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen, Thanh Tam Nguyen. Certified Unlearning for Federated Recommendation. In TOIS 2024
61. Thanh Trung Huynh, Trong Bang Nguyen, Phi Le Nguyen, Thanh Tam Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer. Fast-FedUL: A Training-Free Federated Unlearning with Provable Skew Resilience. In ECML PKDD 2024
60. Zhao Ren, Yi Chang, Thanh Tam Nguyen, Yang Tan, Kun Qian, Björn W. Schuller. A Comprehensive Survey on Heart Sound Analysis in the Deep Learning Era. In IEEE-CIM 2024.
59. Darnbi Sakong, Viet Hung Vu, Thanh Trung Huynh, Phi Le Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen, Thanh Tam Nguyen. Higher-order Knowledge-enhanced Recommendation with Heterogeneous Hypergraph Multi-Attention. In Information Sciences 2024.
58. Minh Tam Pham, Thanh Trung Huynh, Thanh Tam Nguyen, Thanh Toan Nguyen, Thanh Thi Nguyen, Jun Jo, Hongzhi Yin, Quoc Viet Hung Nguyen. A dual benchmarking study of facial forgery and facial forensics. In TRIT 2024.
57. Zhao Ren, Björn W. Schuller, Björn M. Eskofier, Thanh Tam Nguyen, Wolfgang Nejdl. Trustworthy and Collaborative AI for Personalised Healthcare through Edge-of-Things. In JBHI 2023.
56. Thanh Tam Nguyen, Chi Thang Duong, Hongzhi Yin, Matthias Weidlich, Thai Son Mai, Karl Aberer, Nguyen Quoc Viet Hung. Efficient and Effective Multi-Modal Queries through Heterogeneous Network Embedding. In ICDE 2023.
55. Thanh Tam Nguyen, Thanh Cong Phan, Hien Thu Pham, Thanh Thi Nguyen, Jun Jo, Quoc Viet Hung Nguyen. Example-based Explanations for Streaming Fraud Detection on Graphs. In Information Sciences 2023
54. Thanh Tam Nguyen, Thanh Trung Huynh, Minh Tam Pham, Thanh Dat Hoang, Thanh Thi Nguyen, Hongzhi Yin, Quoc Viet Hung Nguyen. Validating Functional Redundancy with Mixed Generative Adversarial Networks. In KBS 2023
53. Thanh Trung Huynh, Minh Hieu Nguyen, Thanh Tam Nguyen, Phi Le Nguyen, Matthias Weidlich, Quoc Viet Hung Nguyen, Karl Aberer. Efficient Integration of Multi-Order Dynamics and Internal Dynamics in Stock Movement Prediction. In WSDM 2023
52. Huynh Thanh Trung, Tong Vinh Van, Nguyen Thanh Tam, Jo Jun, Yin Hongzhi, Nguyen Quoc Viet Hung. Learning Holistic Interactions in LBSNs with High-order, Dynamic, and Multi-role Contexts. In TKDE 2023
51. Huynh, Thanh Trung, Chi Thang Duong, Tam Thanh Nguyen, Vinh Van Tong, Abdul Sattar, Hongzhi Yin, and Quoc Viet Hung Nguyen. Network Alignment with Holistic Embeddings. In TKDE 2023 (Funded by ARC)
50. Thanh Toan Nguyen, Thanh Tam Nguyen, Thanh Hung Nguyen, Hongzhi Yin, Thanh Thi Nguyen, Jun Jo, Nguyen Quoc Viet Hung. Isomorphic Graph Embedding for Progressive Maximal Frequent Subgraph Mining. In TIST 2023.
49. Zhao Ren, Thanh Tam Nguyen, Mehdi Mohammad Zahed, Wolfgang Nejdl. Self-Explaining Neural Networks for Respiratory Sound Classification with Scale-Free Interpretability. In IJCNN 2023
48. Thanh Toan Nguyen, Quang-Duc Nguyen, Zhao Ren, Jun Jo, Quoc Viet Hung Nguyen, Thanh Tam Nguyen. 10X Faster Subgraph Matching: Dual Matching Networks with Interleaved Diffusion Attention. In IJCNN 2023
47. Zhao Ren, Thanh Tam Nguyen, Yi Chang, Björn W. Schuller. Fast Yet Effective Speech Emotion Recognition with Self-Distillation. In ICASSP 2023
46. Yi Chang, Zhao Ren, Thanh Tam Nguyen, Kun Qian, Björn W. Schuller. Knowledge Transfer for On-Device Speech Emotion Recognition with Neural Structured Learning. In ICASSP 2023
45. Darnbi Sakong, Thanh Trung Huynh, Thanh Tam Nguyen, Thanh Toan Nguyen, Jun Jo, Quoc Viet Hung Nguyen. Complex Representation Learning with Graph Convolutional Networks for Knowledge Graph Alignment. In IJIS 2023
44. Thanh Tam Nguyen, Thanh Trunh Huynh, Hongzhi Yin, Matthias Weidlich, Thanh Thi Nguyen, Thai Son Mai, Quoc Viet Hung Nguyen. Detecting Rumours with Latency Guarantees using Massive Streaming Data. In VLDBJ 2022
43. Thanh Tam Nguyen, Thanh Cong Phan, Minh Hieu Nguyen, Matthias Weidlich, Hongzhi Yin, Jun Jo, Quoc Viet Hung Nguyen. Model-Agnostic and Diverse Explanations for Streaming Rumour Graphs. In KBS 2022 (Funded by ARC)
42. Thanh Tam Nguyen, Chi Thang Duong, Trung-Dung Hoang, Hongzhi Yin, Matthias Weidlich, Quoc Viet Hung Nguyen. Deep MinCut: Learning Node Embeddings from Detecting Communities. In Pattern Recognition 2022
41. Huynh, Thanh Trung, Chi Thang Duong, Tam Thanh Nguyen, Vinh Van Tong, Abdul Sattar, Hongzhi Yin, and Quoc Viet Hung Nguyen. Network Alignment with Holistic Embeddings. In ICDE 2022
40. Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Dung Tien Nguyen, Duc Thanh Nguyen, Thien Huynh-The, Saeid Nahavandi, Thanh Tam Nguyen, Quoc-Viet Pham, Cuong M. Nguyen. Deep Learning for Deepfakes Creation and Detection: A Survey. In CVIU 2022
39. Yi Chang, Zhao Ren, Thanh Tam Nguyen, Wolfgang Nejdl, Bjorn W. Schuller. Example-based Explanations with Adversarial Attacks for Respiratory Sound Analysis. In INTERSPEECH 2022
38. Thanh Thi Nguyen, Mohamed Abdelrazek, Dung Tien Nguyen, Sunil Aryal, Duc Thanh Nguyen, Sandeep Reddy, Quoc Viet Hung Nguyen, Amin Khatami, Thanh Tam Nguyen et al. Origin of novel coronavirus causing COVID-19: A computational biology study using artificial intelligence. In MLWA 2022.
37. Thanh Cong Phan, Thanh Tam Nguyen, Matthias Weidlich, Hongzhi Yin, Jun Jo, Quoc Viet Hung Nguyen. exRumourLens: Auditable Rumour Detection with Multi-View Explanations. In ICDE 2022
36. Phan, Thanh Cong, Nguyen Duc Khang Quach, Thanh Tam Nguyen, Thanh Toan Nguyen, Jun Jo, and Quoc Viet Hung Nguyen. Real-time wildfire detection with semantic explanations. In ESWA 2022
35. Thang, Duong Chi, Hoang Thanh Dat, Nguyen Thanh Tam, Jun Jo, Nguyen Quoc Viet Hung, and Karl Aberer. Nature vs. Nurture: Feature vs. Structure for Graph Neural Networks. In Pattern Recognition Letters 2022
34. Thanh Toan Nguyen, Khang Nguyen Duc Quach, Thanh Tam Nguyen, Thanh Trung Huynh, Viet Hung Vu, Phi Le Nguyen, Jun Jo, Quoc Viet Hung Nguyen. Poisoning GNN-based Recommender Systems with Generative Surrogate-based Attacks. In TOIS 2022
33. Zhao Ren, Thanh Tam Nguyen, Wolfgang Nejdl. Prototype Learning for Interpretable Respiratory Sound Analysis. In ICASSP 2022
32. Vinh Tong, Dat Quoc Nguyen, Trung Thanh Huynh, Tam Thanh Nguyen, Quoc Viet Hung Nguyen, Mathias Niepert. Joint Multilingual Knowledge Graph Completion and Alignment. In EMNLP 2022
31. Thanh Tam Nguyen, Thanh Trung Huynh, Hongzhi Yin, Vinh Van Tong, Darnbi Sakong, Bolong Zheng and Quoc Viet Hung Nguyen. Entity Alignment for Knowledge Graphs with Multi-order Convolutional Networks. In TKDE 2021.
30. Bo Zhao, Han van der Aa, Nguyen Thanh Tam, Nguyen Quoc Viet Hung and Matthias Weidlich. EIRES: Efficient Integration of Remote Data in Event Stream Processing. In SIGMOD 2021.
29. Chi Thang Duong, Thanh Tam Nguyen, Hongzhi Yin, Matthias Weidlich, Thai Son Mai, Karl Aberer, Nguyen Quoc Viet Hung. Efficient and Effective Multi-Modal Queries through Heterogeneous Network Embedding. In TKDE 2021.
28. Nguyen Thanh Toan, Nguyen Thanh Tam, Nguyen Thanh Thi, Bay Vo, Jun Jo, Nguyen Quoc Viet Hung. JUDO: Just-in-time rumour detection in streaming social platforms. In Information Sciences 2021.
27. Thanh Tam Nguyen, Thanh Trung Huynh, Hongzhi Yin, Vinh Van Tong, Darnbi Sakong, Bolong Zheng and Quoc Viet Hung Nguyen. Entity Alignment for Knowledge Graphs with Multi-order Convolutional Networks. In ICDE 2021.
26. Thanh Toan Nguyen, Minh Tam Pham, Thanh Tam Nguyen, Thanh Trung Huynh, Quoc Viet Hung Nguyen, Thanh Tho Quan. Structural representation learning for network alignment with self-supervised anchor links. In ESWA 2021.
25. Thanh Tam Nguyen, Matthias Weidlich, Hongzhi Yin, Bolong Zheng, Quang Huy Nguyen and Quoc Viet Hung Nguyen. FactCatch: Incremental Pay-as-You-Go Fact Checking with Minimal User Effort. In SIGIR 2020.
24. Thanh Trung Huynh, Van Vinh Tong, Thanh Tam Nguyen, Hongzhi Yin, Matthias Weidlich, Quoc Viet Hung Nguyen. Adaptive Network Alignment with Unsupervised and Multi-order Convolutional Networks. In ICDE 2020.
23. Thanh Tam Nguyen, Thanh Dat Hoang, Minh Tam Pham, Vu Tuyet Trinh, Thanh-Hung Nguyen, Quyet-Thang Huynh, Jun Jo. Monitoring agriculture areas with satellite images and deep learning. In Applied Soft Computing 2020.
22. Nguyen Thanh Tam, Matthias Weidlich, Bolong Zheng, Hongzhi Yin, Nguyen Quoc Viet Hung, Bela Stantic. From Anomaly Detection to Rumour Detection using Data Streams of Social Platforms. In VLDB 2019.
21. Nguyen Thanh Tam, Matthias Weidlich, Hongzhi Yin, Bolong Zheng, Nguyen Quoc Viet Hung, Bela Stantic. User Guidance for Efficient Fact Checking. In VLDB 2019.
20. Nguyen Quoc Viet Hung, Matthias Weidlich, Nguyen Thanh Tam, Zoltan Miklos, Karl Aberer, Avigdor Gal, Bela Stantic. Handling Probabilistic Integrity Constraints in Pay-as-you-go Reconciliation of Data Models. In Information Systems 2019.
19. Phan Thanh Cong, Nguyen Thanh Tam, Hongzhi Yin, Bolong Zheng, Nguyen Quoc Viet Hung, Bela Stantic. Efficient User Guidance for Validating Participatory Sensing Data. In TIST 2019.
18. Thanh Tam Nguyen, Thanh Cong Phan, Nguyen Quoc Viet Hung, Karl Aberer, Bela Stantic. Maximal Fusion of Facts on the Web with Credibility Guarantee. In Information Fusion, 2019.
17. Nguyen Quoc Viet Hung, Huynh Huu Viet, Nguyen Thanh Tam, Matthias Weidlich, Hongzhi Yin, Xiaofang Zhou. Computing Crowd Consensus with Partial Agreement. In TKDE 2018.
16. Nguyen Quoc Viet Hung, Kai Zheng, Matthias Weidlich, Bolong Zheng, Hongzhi Yin, Nguyen Thanh Tam, Bela Stantic. What-if Analysis with Conflicting Goals: Recommending Data Ranges for Exploration. In ICDE 2018.
15. Nguyen Thanh Toan, Phan Thanh Cong, Nguyen Thanh Tam, Nguyen Quoc Viet Hung, Bela Stantic. Diversifying Group Recommendation. In IEEE Access 2018.
14. Nguyen Quoc Viet Hung, Huynh Huu Viet, Nguyen Thanh Tam, Matthias Weidlich, Hongzhi Yin, Xiaofang Zhou. Computing Crowd Consensus with Partial Agreement. In ICDE 2018.
13. Nguyen Thanh Tam, Duong Chi Thang, Matthias Weidlich, Hongzhi Yin, Nguyen Quoc Viet Hung. Retaining data from streams of social platforms with minimal regret. In IJCAI 2017.
12. Nguyen Quoc Viet Hung, Duong Chi Thang, Nguyen Thanh Tam, Matthias Weidlich, Karl Aberer, Hongzhi Yin, Xiaofang Zhou. Argument Discovery via Crowdsourcing. In VLDBJ 2017.
11. Nguyen Quoc Viet Hung, Duong Chi Thang, Nguyen Thanh Tam, Matthias Weidlich, Karl Aberer, Hongzhi Yin, Xiaofang Zhou. Answer Validation for Generic Crowdsourcing Tasks with Minimal Efforts. In VLDBJ 2017.
10. Nguyen Quoc Viet Hung, Nguyen Thanh Tam, Chau Vinh Tuan, Tri Kurniawan Wijaya, Zoltan Miklos, Karl Aberer, Avigdor Gal and Matthias Weidlich. SMART: A tool for analyzing and reconciling schema matching networks. In ICDE 2015.
9. Nguyen Thanh Tam, Nguyen Quoc Viet Hung, Matthias Weidlich and Karl Aberer. Result Selection and Summarization for Web Table Search. In ICDE 2015.
8. Duong Chi Thang, Nguyen Thanh Tam, Nguyen Quoc Viet Hung and Karl Aberer. An Evaluation of Diversification Techniques. In DEXA 2015.
7. Nguyen Quoc Viet Hung, Do Son Thanh, Nguyen Thanh Tam, Karl Aberer. Tag-based Paper Retrieval: Minimizing User Effort with Diversity Awareness. In DASFAA 2015.
6. Nguyen Quoc Viet Hung, Do Son Thanh, Nguyen Thanh Tam, Karl Aberer. Privacy-Preserving Schema Reuse. In DASFAA 2014.
5. Nguyen Quoc Viet Hung, Nguyen Thanh Tam, Zoltan Miklos, Karl Aberer, Avigdor Gal and Matthias Weidlich. Pay-as-you-go Reconciliation in Schema Matching Networks. In ICDE 2014.
4. Nguyen Quoc Viet Hung, Nguyen Thanh Tam, Zoltan Miklos, Karl Aberer. Reconciling Schema Matching Networks Through Crowdsourcing. In Trans. Collaborative Computing 2014.
3. Nguyen Quoc Viet Hung, Nguyen Thanh Tam, Lam Ngoc Tran, Karl Aberer. An Evaluation of Aggregation Techniques in Crowdsourcing. In WISE 2013.
2. Nguyen Quoc Viet Hung, Nguyen Thanh Tam, Lam Ngoc Tran, Karl Aberer. A Benchmark for Aggregation Techniques in Crowdsourcing. In SIGIR 2013.
1. Nguyen Quoc Viet Hung, Nguyen Thanh Tam, Zoltan Miklos, Karl Aberer. On Leveraging Crowdsourcing Techniques for Schema Matching Networks. In DASFAA 2013 (Best Student Paper Award)
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