I obtained my Ph.D. in School of Computing Technologies from RMIT University in 2025. My research lies at the intersection of data management, machine learning, and large-scale intelligent systems.

I focus on building learning-enhanced, target-oriented data ecosystems that improve both AI performance and data system scalability. My work develops data-centric frameworks and algorithms for intelligent data discovery, assemblage, and selection across multi-modal data lakes, enabling high-quality, cost-effective, and explainable data pipelines for downstream AI applications.

Broadly, my goal is to unify database principles with modern AI techniques—exploring how AI can enhance data management systems through adaptive optimization and learning, and how data management foundations can in turn improve AI reliability, efficiency, and transparency. Through this integration, I aim to advance next-generation data ecosystems that combine data quality, traceability, and accessibility with model intelligence, fostering scalable, deployable, and reproducible data-driven systems.

EDUCATION

PUBLICATIONS

Conference

Tingting Wang, Shixun Huang, Zhifeng Bao, J. Shane Culpepper, Volkan Dedeoglu, Reza Arablouei: Distinctiveness Maximization in Datasets Assemblage. In Proceedings of the ACM on Web Conference 2025 (WWW 2025): 3219-3232. [Paper]
Tingting Wang, Shixun Huang, Zhifeng Bao, J. Shane Culpepper, Volkan Dedeoglu, Reza Arablouei: Optimizing Data Acquisition to Enhance Machine Learning Performance. Proceedings of the VLDB Endowment (PVLDB), 17(6): 1310-1323 (2024). [Paper]
Tingting Wang, Shixun Huang, Zhifeng Bao, J. Shane Culpepper, Reza Arablouei: Representative Routes Discovery From Massive Trajectories. In the 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD 2022): 4059-4069. [Paper]
Tingting Wang, Lei Duan, Chengxin He, Geng Deng, Ruiqi Qin, Yidan Zhang: ATOM: Construction of Anti-tumor Biomaterial Knowledge Graph by Biomedicine Literature. In: International Conference on Bioinformatics & Biomedicine 2019 (BIBM 2019): 1256-1258. [Paper]

Journal

Tingting Wang, Hui Luo, Zhifeng Bao, and Lei Duan: Dynamic Ridesharing with Minimal Regret: Towards an Enhanced Engagement Among Three Stakeholders. IEEE Transactions on Knowledge and Data Engineering, 35(4): 3712-3726 (2023). [Paper]
Tingting Wang, Lei Duan, Guozhu Dong, and Zhifeng Bao: Efficient Mining of Outlying Sequence Patterns for Analyzing Outlierness of Sequence Data. ACM Transaction on Knowledge and Data Discovery, 14(5): 62:1-62:26 (2020). [Paper]
Chengxin He, Lei Duan, Guozhu Dong, Jyrki Nummenmaa, Tingting Wang, Tinghai Pang: Efficient mining of concept-hierarchy aware distinguishing sequential patterns. Knowledge-Based Systems, 255: 109710 (2022). [Paper]
Wuli Xu, Lei Duan, Huiru Zheng, Jesse Li-Ling, Weipeng Jiang, Yidan Zhang, Tingting Wang, Ruiqi Qin: An Integrative Disease Information Network Approach to Similar Disease Detection. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 20(5): 2724-2735 (2023). [Paper]
Yidan Zhang, Lei Duan, Huiru Zheng, Jesse Li-Ling, Ruiqi Qin, Zihao Chen, Chengxin He, Tingting Wang: Mining Similar Aspects for Gene Similarity Explanation Based on Gene Information Network. IEEE/ACM Transactions on Computational Biology and Bioinformatics, 19(3): 1734-1746 (2022). [Paper]
Lei Duan, Lu Liu, Guozhu Dong, Jyrki Nummenmaa, Tingting Wang, Pan Qin, Hao Yang: Mining distinguishing customer focus sets from online customer reviews. Computing, 100(4): 335-351 (2018). [Paper]

EXPERIENCE

AWARDS

Data61 PhD Scholarship, 2022-2024
Second-class Scholarship of SCU, 2018-2020
Outstanding Graduate Award of SCU, 2017
National Scholarship of China, 2016
First-class Scholarship of SCU, 2016
Meritorious Winner of MCM/ICM, 2016
Outstanding Student Award of SCU, 2014-2016