Publications

A complete list can be found on Google Scholar.

• Ma, L., Pu, K., Zhu, Y., & Taylor, W. (2025). Comparing large language models for generating complex queries. Journal of Computer and Communications, 13(2), 236–249.
• Fu, Z., Chen, Y., Davoudi, K., & Pu, K. Q. (2025). Database entity recognition with data augmentation and deep learning. IEEE 26th International Conference on Information Reuse and Integration, 1–6.
• Ma, L., Pu, K., & Zhu, Y. (2024). Evaluating llms for text-to-sql generation with complex sql workload. arXiv Preprint arXiv:2407.19517.
• Mekael Wasti, S., Pu, K. Q., & Neshati, A. (2024). Large language user interfaces: Voice interactive user interfaces powered by LLMs. arXiv e-Prints, arXiv–2402.
• Wasti, S. M., Pu, K. Q., & Neshati, A. (2024). Large language user interfaces: Voice interactive user interfaces powered by LLMs. Intelligent Systems Conference, 639–655.
• Ma, L., & Pu, K. Q. (2024). Accelerating relational keyword queries with embedded predictive neural networks. 2024 IEEE International Conference on Information Reuse and Integration for Data Science (IRI), 84–89.
• Fu, Z., Yang, C., Davoudi, H., & Pu, K. (2024). Transforming text-to-SQL datasets into closed-domain NER benchmark. Ontario DataBase Day–Program, 12.
• Nargesian, F., Pu, K., Ghadiri-Bashardoost, B., Zhu, E., & Miller, R. J. (2022). Data lake organization. IEEE Transactions on Knowledge and Data Engineering, 35(1), 237–250.
• Pu, K., & Ma, L. (2022). Incremental computation of information gain in temporal relational streams. 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI), 234–235.
• Ma, L., & Pu, K. Q. (2022). Neural network accelerated tuple search for relational data. 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI), 81–82.
• Ouellette, P., Sciortino, A., Nargesian, F., Bashardoost, B. G., Zhu, E., Pu, K. Q., & Miller, R. J. (2021). RONIN: Data lake exploration. Proceedings of the VLDB Endowment, 14(12).
• Nargesian, F., Pu, K. Q., Zhu, E., Ghadiri Bashardoost, B., & Miller, R. J. (2020). Organizing data lakes for navigation. Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, 1939–1950.
• Helala, M. A., Qureshi, F. Z., & Pu, K. Q. (2020). A stream algebra for performance optimization of large scale computer vision pipelines. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(2), 905–923.
• Polovina, S., Polovina, R., Kemp, N., & Pu, K. (2020). MOVE: Measuring ontologies in value-seeking environments: CSCW for human adaptation. Companion Publication of the 2020 Conference on Computer Supported Cooperative Work and Social Computing, 475–482.
• Mior, M. J., & Pu, K. Q. (2020). Semantic data understanding with character level learning. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 253–258.
• Stoica, A., Pu, K. Q., & Davoudi, H. (2020). NLP relational queries and its application. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 395–398.
• Valdron, M., & Pu, K. Q. (2020). Data driven relational constraint programming. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 156–163.
• Nargesian, F., Zhu, E., Miller, R. J., Pu, K. Q., & Arocena, P. C. (2019). Data lake management: Challenges and opportunities. Proceedings of the VLDB Endowment, 12(12), 1986–1989.
• Beirami, A., Zhu, Y., & Pu, K. (2019). Trusted relational databases with blockchain: Design and optimization. Procedia Computer Science, 155, 137–144.
• Stoica, A., Valdron, M., & Pu, K. (2019). Scalable analysis of open data graphs. 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI), 334–341.
• Nargesian, F., Zhu, E., Pu, K. Q., & Miller, R. J. (2018). Table union search on open data. Proceedings of the VLDB Endowment, 11(7), 813–825.
• Miller, R. J., Nargesian, F., Zhu, E., Christodoulakis, C., Pu, K. Q., & Andritsos, P. (2018). Making open data transparent: Data discovery on open data. IEEE Data Eng. Bull., 41(2), 59–70.
• Beiraimi, A., Pu, K., & Zhu, Y. (2018). Towards optimal snapshot materialization to support large query workload for append-only temporal databases. 2018 IEEE International Congress on Big Data (BigData Congress), 268–271.
• Nargesian, F., Pu, K. Q., Bashardoost, B. G., Zhu, E., & Miller, R. J. (2018). Data lake organization. arXiv Preprint arXiv:1812.07024.
• Hedrick, A., Zhu, Y., & Pu, K. (2017). Modeling transition and mobility patterns. International Conference on Applied Human Factors and Ergonomics, 528–537.
• Zhu, E., Pu, K. Q., Nargesian, F., & Miller, R. J. (2017). Interactive navigation of open data linkages. Proceedings of the VLDB Endowment, 10(12), 1837–1840.
• Reina, E., Pu, K. Q., & Qureshi, F. Z. (2017). An index structure for fast range search in hamming space. 2017 14th Conference on Computer and Robot Vision (CRV), 8–15.
• Zhu, E., Nargesian, F., Pu, K. Q., & Miller, R. J. (2016). LSH ensemble: Internet-scale domain search. arXiv Preprint arXiv:1603.07410.
• Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2016). A formal algebra implementation for distributed image and video stream processing. Proceedings of the 10th International Conference on Distributed Smart Camera, 84–91.
• Ferron, M., Pu, K. Q., & Szlichta, J. (2016). ARC: A pipeline approach enabling large-scale graph visualization. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 1397–1400.
• Hedrick, A., Pu, K. Q., & Zhu, Y. (2016). Hierarchical temporal mobility analysis with semantic labeling. 2016 International Conference on Computational Science and Computational Intelligence (CSCI), 1321–1326.
• Helala, M. A., Qureshi, F. Z., & Pu, K. Q. (2015). Automatic parsing of lane and road boundaries in challenging traffic scenes. Journal of Electronic Imaging, 24(5), 053020–053020.
• Yu, Z., Liu, Y., Yu, X., & Pu, K. Q. (2014). Scalable distributed processing of k nearest neighbor queries over moving objects. IEEE Transactions on Knowledge and Data Engineering, 27(5), 1383–1396.
• Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2014). A stream algebra for computer vision pipelines. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 786–793.
• Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2014). Towards efficient feedback control in streaming computer vision pipelines. Asian Conference on Computer Vision, 314–329.
• Drake, R., & Pu, K. Q. (2014). Using document space for relational search. Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014), 841–844.
• Hassanzadeh, O., Pu, K. Q., Yeganeh, S. H., Miller, R. J., Popa, L., Hernández, M. A., & Ho, H. (2013). Discovering linkage points over web data. Proceedings of the VLDB Endowment, 6(6), 445–456.
• Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2012). Road boundary detection in challenging scenarios. 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, 428–433.
• Hedrick, A., & Pu, K. Q. (2012). Authoring relational queries on the mobile devices. Procedia Computer Science, 10, 752–757.
• Malloy, W. E., & Pu, K. Q. (2012). Systems and computer program products to identify related data in a multidimensional database.
• Rachevsky, L., & Pu, K. Q. (2011). Selection of features for surname classification. 2011 IEEE International Conference on Information Reuse & Integration, 15–20.
• Pu, K. Q., & Cheung, R. (2011). Tag grid: Supporting multidimensional queries of tagged datasets. In Recent trends in information reuse and integration (pp. 331–342). Springer Vienna Vienna.
• Pu, K. Q., Hassanzadeh, O., Drake, R., & Miller, R. J. (2010). Online annotation of text streams with structured entities. Proceedings of the 19th ACM International Conference on Information and Knowledge Management, 29–38.
• Pu, K. Q., & Cheung, R. (2010). Tag grid: Supporting collaborative and fuzzy multidimensional queries of tagged datasets. 2010 IEEE International Conference on Information Reuse & Integration, 364–367.
• Q Pu, K. (2010). Recent patents on information retrieval using natural language and keyword query. Recent Patents on Computer Science, 3(3), 186–194.
• Pu, K. Q. (2009). Keyword query cleaning using hidden markov models. Proceedings of the First International Workshop on Keyword Search on Structured Data, 27–32.
• Bourennani, F., Pu, K. Q., & Zhu, Y. (2009). Visual integration tool for heterogeneous data type by unified vectorization. 2009 IEEE International Conference on Information Reuse & Integration, 132–137.
• Bourennani, F., Pu, K. Q., & Zhu, Y. (2009). Visualization and integration of databases using self-organizing map. 2009 First International Confernce on Advances in Databases, Knowledge, and Data Applications, 155–160.
• Pu, K. Q., & Yu, X. (2009). Frisk: Keyword query cleaning and processing in action. 2009 IEEE 25th International Conference on Data Engineering, 1531–1534.
• Zhu, Y., Howard, W., & Pu, K. Q. (2009). Spatial inference using networks of RFID receiver: A bayesian approach. GLOBECOM 2009-2009 IEEE Global Telecommunications Conference, 1–6.
• Bourennani, F., Pu, K. Q., & Zhu, Y. (2009). Unified vectorization of numerical and textual data using self-organizing map. International Journal On Advances in Systems and Measurements, 2.
• Pu, K. Q. (2009). Analysis of service compatibility. Services and Business Computing Solutions with XML: Applications for Quality, 136.
• Pu, K. Q., & Yu, X. (2008). Keyword query cleaning. Proceedings of the VLDB Endowment, 1(1), 909–920.
• Zhu, Y., Li, B., & Pu, K. Q. (2008). Dynamic multicast in overlay networks with linear capacity constraints. IEEE Transactions on Parallel and Distributed Systems, 20(7), 925–939.
• Malloy, W. E., & Pu, K. Q. (2008). Methods to identify related data in a multidimensional database.
• Zhu, Y., & Pu, K. Q. (2008). Adaptive multicast tree construction for elastic data streams. IEEE GLOBECOM 2008-2008 IEEE Global Telecommunications Conference, 1–5.
• Pu, K. Q., & Zhu, Y. (2008). Modeling and synthesis of service composition using tree automata. 2008 IEEE International Conference on Information Reuse and Integration, 46–51.
• Pu, K. Q., & Zhu, Y. (2007). Efficient indexing of heterogeneous data streams with automatic performance configurations. 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007), 34–34.
• Pu, K. Q. (2007). Service description and analysis from a type theoretic approach. 2007 IEEE 23rd International Conference on Data Engineering Workshop, 379–386.
• Pu, K. Q., & Zhu, Y. (2007). Fast archiving and querying of heterogeneous sensor data streams. 2007 Second International Conference on Digital Telecommunications (ICDT’07), 28–28.
• Pu, K., Hristidis, V., & Koudas, N. (2006). Syntactic rule based approach toweb service composition. 22nd International Conference on Data Engineering (ICDE’06), 31–31.
• Chandel, A., Koudas, N., Pu, K. Q., & Srivastava, D. (2006). Fast identification of relational constraint violations. 2007 IEEE 23rd International Conference on Data Engineering, 776–785.
• Pu, Q. K. (2006). On formal methods of multidimensional databases [PhD thesis].
• Yu, X., Pu, K. Q., & Koudas, N. (2005). Monitoring k-nearest neighbor queries over moving objects. 21st International Conference on Data Engineering (ICDE’05), 631–642.
• Pu, K. Q., & Mendelzon, A. O. (2005). Concise descriptions of subsets of structured sets. ACM Transactions on Database Systems (TODS), 30(1), 211–248.
• Pu, K. Q. (2005). Modeling, querying and reasoning about OLAP databases: A functional approach. Proceedings of the 8th ACM International Workshop on Data Warehousing and OLAP, 1–8.
• Pu, K. Q., & Mendelzon, A. O. (2005). Typed functional query languages with equational specifications. Proceedings of the 14th ACM International Conference on Information and Knowledge Management, 233–234.
• Pu, K. Q. (2004). Functional integration of relational, OLAP and XML data. Proceedings of VLDB Workshop on Information Integration on the Web (IIWeb-2004), 97.
• Mendelzon, A. O., & Pu, K. Q. (2003). Concise descriptions of subsets of structured sets. Proceedings of the Twenty-Second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 123–133.
• Pu, K. (2000). Modeling and control of discrete-event systems with hierarchical abstraction. Ma sc [PhD thesis]. Thesis, Dept. of Electl. & Cmptr. Engrg., Univ. of Toronto.
• Pu, K. Q. (1998). Theory of discrete wavelet transform and an error analysis of the pyramid algorithm [PhD thesis]. Citeseer.
• Ma, L., Synytski, B., Zhu, Y., & Pu, K. (2025). Semantic relational types for AI tool selection. In Proc. Of IEEE CASCON 2025.

References

Fu, Z., Chen, Y., Davoudi, K., & Pu, K. Q. (2025). Database entity recognition with data augmentation and deep learning. IEEE 26th International Conference on Information Reuse and Integration, 1–6.

Ma, L., Pu, K., Zhu, Y., & Taylor, W. (2025). Comparing large language models for generating complex queries. Journal of Computer and Communications, 13(2), 236–249.

Ma, L., Synytski, B., Zhu, Y., & Pu, K. (2025). Semantic relational types for AI tool selection. In Proc. Of IEEE CASCON 2025.

Fu, Z., Yang, C., Davoudi, H., & Pu, K. (2024). Transforming text-to-SQL datasets into closed-domain NER benchmark. Ontario DataBase Day–Program, 12.

Ma, L., & Pu, K. Q. (2024). Accelerating relational keyword queries with embedded predictive neural networks. 2024 IEEE International Conference on Information Reuse and Integration for Data Science (IRI), 84–89.

Ma, L., Pu, K., & Zhu, Y. (2024). Evaluating llms for text-to-sql generation with complex sql workload. arXiv Preprint arXiv:2407.19517.

Mekael Wasti, S., Pu, K. Q., & Neshati, A. (2024). Large language user interfaces: Voice interactive user interfaces powered by LLMs. arXiv e-Prints, arXiv–2402.

Wasti, S. M., Pu, K. Q., & Neshati, A. (2024). Large language user interfaces: Voice interactive user interfaces powered by LLMs. Intelligent Systems Conference, 639–655.

Ma, L., & Pu, K. Q. (2022). Neural network accelerated tuple search for relational data. 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI), 81–82.

Nargesian, F., Pu, K., Ghadiri-Bashardoost, B., Zhu, E., & Miller, R. J. (2022). Data lake organization. IEEE Transactions on Knowledge and Data Engineering, 35(1), 237–250.

Pu, K., & Ma, L. (2022). Incremental computation of information gain in temporal relational streams. 2022 IEEE 23rd International Conference on Information Reuse and Integration for Data Science (IRI), 234–235.

Ouellette, P., Sciortino, A., Nargesian, F., Bashardoost, B. G., Zhu, E., Pu, K. Q., & Miller, R. J. (2021). RONIN: Data lake exploration. Proceedings of the VLDB Endowment, 14(12).

Helala, M. A., Qureshi, F. Z., & Pu, K. Q. (2020). A stream algebra for performance optimization of large scale computer vision pipelines. IEEE Transactions on Pattern Analysis and Machine Intelligence, 44(2), 905–923.

Mior, M. J., & Pu, K. Q. (2020). Semantic data understanding with character level learning. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 253–258.

Nargesian, F., Pu, K. Q., Zhu, E., Ghadiri Bashardoost, B., & Miller, R. J. (2020). Organizing data lakes for navigation. Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data, 1939–1950.

Polovina, S., Polovina, R., Kemp, N., & Pu, K. (2020). MOVE: Measuring ontologies in value-seeking environments: CSCW for human adaptation. Companion Publication of the 2020 Conference on Computer Supported Cooperative Work and Social Computing, 475–482.

Stoica, A., Pu, K. Q., & Davoudi, H. (2020). NLP relational queries and its application. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 395–398.

Valdron, M., & Pu, K. Q. (2020). Data driven relational constraint programming. 2020 IEEE 21st International Conference on Information Reuse and Integration for Data Science (IRI), 156–163.

Beirami, A., Zhu, Y., & Pu, K. (2019). Trusted relational databases with blockchain: Design and optimization. Procedia Computer Science, 155, 137–144.

Nargesian, F., Zhu, E., Miller, R. J., Pu, K. Q., & Arocena, P. C. (2019). Data lake management: Challenges and opportunities. Proceedings of the VLDB Endowment, 12(12), 1986–1989.

Stoica, A., Valdron, M., & Pu, K. (2019). Scalable analysis of open data graphs. 2019 IEEE 20th International Conference on Information Reuse and Integration for Data Science (IRI), 334–341.

Beiraimi, A., Pu, K., & Zhu, Y. (2018). Towards optimal snapshot materialization to support large query workload for append-only temporal databases. 2018 IEEE International Congress on Big Data (BigData Congress), 268–271.

Miller, R. J., Nargesian, F., Zhu, E., Christodoulakis, C., Pu, K. Q., & Andritsos, P. (2018). Making open data transparent: Data discovery on open data. IEEE Data Eng. Bull., 41(2), 59–70.

Nargesian, F., Pu, K. Q., Bashardoost, B. G., Zhu, E., & Miller, R. J. (2018). Data lake organization. arXiv Preprint arXiv:1812.07024.

Nargesian, F., Zhu, E., Pu, K. Q., & Miller, R. J. (2018). Table union search on open data. Proceedings of the VLDB Endowment, 11(7), 813–825.

Hedrick, A., Zhu, Y., & Pu, K. (2017). Modeling transition and mobility patterns. International Conference on Applied Human Factors and Ergonomics, 528–537.

Reina, E., Pu, K. Q., & Qureshi, F. Z. (2017). An index structure for fast range search in hamming space. 2017 14th Conference on Computer and Robot Vision (CRV), 8–15.

Zhu, E., Pu, K. Q., Nargesian, F., & Miller, R. J. (2017). Interactive navigation of open data linkages. Proceedings of the VLDB Endowment, 10(12), 1837–1840.

Ferron, M., Pu, K. Q., & Szlichta, J. (2016). ARC: A pipeline approach enabling large-scale graph visualization. 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), 1397–1400.

Hedrick, A., Pu, K. Q., & Zhu, Y. (2016). Hierarchical temporal mobility analysis with semantic labeling. 2016 International Conference on Computational Science and Computational Intelligence (CSCI), 1321–1326.

Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2016). A formal algebra implementation for distributed image and video stream processing. Proceedings of the 10th International Conference on Distributed Smart Camera, 84–91.

Zhu, E., Nargesian, F., Pu, K. Q., & Miller, R. J. (2016). LSH ensemble: Internet-scale domain search. arXiv Preprint arXiv:1603.07410.

Helala, M. A., Qureshi, F. Z., & Pu, K. Q. (2015). Automatic parsing of lane and road boundaries in challenging traffic scenes. Journal of Electronic Imaging, 24(5), 053020–053020.

Drake, R., & Pu, K. Q. (2014). Using document space for relational search. Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration (IEEE IRI 2014), 841–844.

Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2014). A stream algebra for computer vision pipelines. Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 786–793.

Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2014). Towards efficient feedback control in streaming computer vision pipelines. Asian Conference on Computer Vision, 314–329.

Yu, Z., Liu, Y., Yu, X., & Pu, K. Q. (2014). Scalable distributed processing of k nearest neighbor queries over moving objects. IEEE Transactions on Knowledge and Data Engineering, 27(5), 1383–1396.

Hassanzadeh, O., Pu, K. Q., Yeganeh, S. H., Miller, R. J., Popa, L., Hernández, M. A., & Ho, H. (2013). Discovering linkage points over web data. Proceedings of the VLDB Endowment, 6(6), 445–456.

Hedrick, A., & Pu, K. Q. (2012). Authoring relational queries on the mobile devices. Procedia Computer Science, 10, 752–757.

Helala, M. A., Pu, K. Q., & Qureshi, F. Z. (2012). Road boundary detection in challenging scenarios. 2012 IEEE Ninth International Conference on Advanced Video and Signal-Based Surveillance, 428–433.

Malloy, W. E., & Pu, K. Q. (2012). Systems and computer program products to identify related data in a multidimensional database.

Pu, K. Q., & Cheung, R. (2011). Tag grid: Supporting multidimensional queries of tagged datasets. In Recent trends in information reuse and integration (pp. 331–342). Springer Vienna Vienna.

Rachevsky, L., & Pu, K. Q. (2011). Selection of features for surname classification. 2011 IEEE International Conference on Information Reuse & Integration, 15–20.

Pu, K. Q., & Cheung, R. (2010). Tag grid: Supporting collaborative and fuzzy multidimensional queries of tagged datasets. 2010 IEEE International Conference on Information Reuse & Integration, 364–367.

Pu, K. Q., Hassanzadeh, O., Drake, R., & Miller, R. J. (2010). Online annotation of text streams with structured entities. Proceedings of the 19th ACM International Conference on Information and Knowledge Management, 29–38.

Q Pu, K. (2010). Recent patents on information retrieval using natural language and keyword query. Recent Patents on Computer Science, 3(3), 186–194.

Bourennani, F., Pu, K. Q., & Zhu, Y. (2009). Unified vectorization of numerical and textual data using self-organizing map. International Journal On Advances in Systems and Measurements, 2.

Bourennani, F., Pu, K. Q., & Zhu, Y. (2009). Visual integration tool for heterogeneous data type by unified vectorization. 2009 IEEE International Conference on Information Reuse & Integration, 132–137.

Bourennani, F., Pu, K. Q., & Zhu, Y. (2009). Visualization and integration of databases using self-organizing map. 2009 First International Confernce on Advances in Databases, Knowledge, and Data Applications, 155–160.

Pu, K. Q. (2009). Analysis of service compatibility. Services and Business Computing Solutions with XML: Applications for Quality, 136.

Pu, K. Q. (2009). Keyword query cleaning using hidden markov models. Proceedings of the First International Workshop on Keyword Search on Structured Data, 27–32.

Pu, K. Q., & Yu, X. (2009). Frisk: Keyword query cleaning and processing in action. 2009 IEEE 25th International Conference on Data Engineering, 1531–1534.

Zhu, Y., Howard, W., & Pu, K. Q. (2009). Spatial inference using networks of RFID receiver: A bayesian approach. GLOBECOM 2009-2009 IEEE Global Telecommunications Conference, 1–6.

Malloy, W. E., & Pu, K. Q. (2008). Methods to identify related data in a multidimensional database.

Pu, K. Q., & Yu, X. (2008). Keyword query cleaning. Proceedings of the VLDB Endowment, 1(1), 909–920.

Pu, K. Q., & Zhu, Y. (2008). Modeling and synthesis of service composition using tree automata. 2008 IEEE International Conference on Information Reuse and Integration, 46–51.

Zhu, Y., Li, B., & Pu, K. Q. (2008). Dynamic multicast in overlay networks with linear capacity constraints. IEEE Transactions on Parallel and Distributed Systems, 20(7), 925–939.

Zhu, Y., & Pu, K. Q. (2008). Adaptive multicast tree construction for elastic data streams. IEEE GLOBECOM 2008-2008 IEEE Global Telecommunications Conference, 1–5.

Pu, K. Q. (2007). Service description and analysis from a type theoretic approach. 2007 IEEE 23rd International Conference on Data Engineering Workshop, 379–386.

Pu, K. Q., & Zhu, Y. (2007). Efficient indexing of heterogeneous data streams with automatic performance configurations. 19th International Conference on Scientific and Statistical Database Management (SSDBM 2007), 34–34.

Pu, K. Q., & Zhu, Y. (2007). Fast archiving and querying of heterogeneous sensor data streams. 2007 Second International Conference on Digital Telecommunications (ICDT’07), 28–28.

Chandel, A., Koudas, N., Pu, K. Q., & Srivastava, D. (2006). Fast identification of relational constraint violations. 2007 IEEE 23rd International Conference on Data Engineering, 776–785.

Pu, K., Hristidis, V., & Koudas, N. (2006). Syntactic rule based approach toweb service composition. 22nd International Conference on Data Engineering (ICDE’06), 31–31.

Pu, Q. K. (2006). On formal methods of multidimensional databases [PhD thesis].

Pu, K. Q. (2005). Modeling, querying and reasoning about OLAP databases: A functional approach. Proceedings of the 8th ACM International Workshop on Data Warehousing and OLAP, 1–8.

Pu, K. Q., & Mendelzon, A. O. (2005). Concise descriptions of subsets of structured sets. ACM Transactions on Database Systems (TODS), 30(1), 211–248.

Pu, K. Q., & Mendelzon, A. O. (2005). Typed functional query languages with equational specifications. Proceedings of the 14th ACM International Conference on Information and Knowledge Management, 233–234.

Yu, X., Pu, K. Q., & Koudas, N. (2005). Monitoring k-nearest neighbor queries over moving objects. 21st International Conference on Data Engineering (ICDE’05), 631–642.

Pu, K. Q. (2004). Functional integration of relational, OLAP and XML data. Proceedings of VLDB Workshop on Information Integration on the Web (IIWeb-2004), 97.

Mendelzon, A. O., & Pu, K. Q. (2003). Concise descriptions of subsets of structured sets. Proceedings of the Twenty-Second ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, 123–133.

Pu, K. (2000). Modeling and control of discrete-event systems with hierarchical abstraction. Ma sc [PhD thesis]. Thesis, Dept. of Electl. & Cmptr. Engrg., Univ. of Toronto.

Pu, K. Q. (1998). Theory of discrete wavelet transform and an error analysis of the pyramid algorithm [PhD thesis]. Citeseer.