Skip to main content
Headshot of Ken Pu

Ken Pu
PhD

Associate Professor

Computer Science
Faculty of Science

Increasing accessibility of open data to improve Internet transparency and accountability

Contact expert

ken.pu@ontariotechu.ca
905.721.8668 ext. 3444

Update this profile

Areas of expertise


  • Amin Beirami, KQ Pu and Y Zhu, Towards Optimal Snapshot Materialization to Support Large Query Workload for Append-only Temporal Databases, IEEE Service 2018, San Francisco, CA, July, pp. (4), 2018,
  • A Hedrick, Y Zhu and K Pu, Modeling Transition and Mobility Patterns, International Conference on Applied Human Factors and Ergonomics, pp. 528-537, 2017, Springer, Cham
  • E Reina, KQ Pu and FZ Qureshi, An Index Structure for Fast Range Search in Hamming Space, Computer and Robot Vision (CRV), 2017 14th Conference on, pp. 8-15, 2017, IEEE
  • A Hedrick, KQ Pu and Y Zhu, Hierarchical temporal mobility analysis with semantic labeling, Computational Science and Computational Intelligence (CSCI), 2016 International Conference on, pp. 1321-1326, 2016, IEEE
  • M Ferron, KQ Pu and J Szlichta, ARC: A pipeline approach enabling large-scale graph visualization, Advances in Social Networks Analysis and Mining (ASONAM), 2016 IEEE/ACM International Conference on, pp. 1397-1400,2016, IEEE
  • MA Helala, KQ Pu and FZ Qureshi, A Formal Algebra Implementation for Distributed Image and Video Stream Processing, Proceedings of the 10th International Conference on Distributed Smart Camera, pp. 84-91, 2016, ACM
  • R Drake and KQ Pu, Using document space for relational search, Information Reuse and Integration (IRI), 2014 IEEE 15th International Conference on, pp. 841-844, 2014, IEEE
  • MA Helala, KQ Pu and FZ Qureshi, Towards Efficient Feedback Control in Streaming Computer Vision Pipelines, Asian Conference on Computer Vision,pp. 314-329, 2014, Springer, Cham
  • ER Reina, F Qureshi and K Pu, An Index Structure for Fast Range Search in Hamming Space, 2014, UOIT
  • MA Helala, KQ Pu and FZ Qureshi, A stream algebra for computer vision pipelines, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 786-793, 2014,
  • KQ Pu and R Cheung, Tag Grid: Supporting Multidimensional Queries of Tagged Datasets, Recent Trends in Information Reuse and Integration, pp. 331-342, 2012, Springer, Vienna
  • WE Malloy and KQ Pu, Systems and computer program products to identify related data in a multidimensional database, 2012, US Patent 8,126,871
  • MA Helala, KQ Pu and FZ Qureshi, Road boundary detection in challenging scenarios, Advanced Video and Signal-Based Surveillance (AVSS), 2012 IEEE Ninth International Conference on, pp. 428-433, 2012, IEEE
  • A Hedrick and KQ Pu, Authoring relational queries on the mobile devices, Procedia Computer Science, pp. 752-757, 2012, Elsevier
  • L Rachevsky and KQ Pu, Selection of features for surname classification, Information Reuse and Integration (IRI), 2011 IEEE International Conference on, pp. 15-20, 2011, IEEE
  • KQ Pu and R Cheung, Tag grid: supporting collaborative and fuzzy multidimensional queries of tagged datasets, Information Reuse and Integration (IRI), 2010 IEEE International Conference on, pp. 364-367, 2010, IEEE
  • KQ Pu, O Hassanzadeh, R Drake and RJ Miller, Online annotation of text streams with structured entities, Proceedings of the 19th ACM international conference on Information and knowledge management, pp. 29-38, 2010, ACM
  • F Bourennani, KQ Pu and Y Zhu, Visualization and integration of databases using self-organizing map, Advances in Databases, Knowledge, and Data Applications, 2009. DBKDA'09. First International Conference on, pp. 155-160,2009, IEEE
  • F Bourennani, KQ Pu and Y Zhu, Visual integration tool for heterogeneous data type by unified vectorization, Information Reuse & Integration, 2009. IRI'09. IEEE International Conference on, pp. 132-137, 2009, IEEE
  • F Bourennani, KQ Pu and Y Zhu, Unified Vectorization of Numerical and Textual Data using Self-Organizing Map, International Journal on Advances in Systems and Measurements Volume 2, Numbers 2&3, 2009, 2009,
  • Y Zhu, W Howard and KQ Pu, Spatial inference using networks of RFID receiver: a Bayesian approach, Global Telecommunications Conference, 2009. GLOBECOM 2009. IEEE, pp. 1-6, 2009, IEEE
  • KQ Pu, Keyword query cleaning using hidden markov models, Proceedings of the First International Workshop on Keyword Search on Structured Data, pp. 27-32, 2009, ACM
  • KQ Pu and X Yu, Frisk: Keyword query cleaning and processing in action, IEEE International Conference on Data Engineering, pp. 1531-1534, 2009, IEEE
  • KQ Pu, Analysis of Service Compatibility: Complexity and Computation, Services and Business Computing Solutions with XML: Applications for Quality Management and Best Processes, pp. 136-155, 2009, IGI Global
  • KQ Pu, Analysis of Service Compatibility, Services and Business Computing Solutions with XML: Applications for Quality, pp. 136, 2009,
  • Y Zhu and KQ Pu, Modeling and synthesis of service composition using tree automata, Information Reuse and Integration, 2008. IRI 2008. IEEE International Conference on, pp. 46-51, 2008,
  • WE Malloy and KQ Pu, Methods to identify related data in a multidimensional database, 2008, US Patent 7,472,127
  • Y Zhu and KQ Pu, Adaptive multicast tree construction for elastic data streams, Global Telecommunications Conference, 2008. IEEE GLOBECOM 2008. IEEE, pp. 1-5, 2008, IEEE
  • KQ Pu, Service description and analysis from a type-theoretic approach, Data Engineering Workshop, 2007 IEEE 23rd International Conference on, pp. 379-386, 2007, IEEE
  • A Chandel, N Koudas, KQ Pu and D Srivastava, Fast identification of relational constraint violations, Data Engineering, 2007. ICDE 2007. IEEE 23rd International Conference on, pp. 776-785, 2007, IEEE
  • KQ Pu and Y Zhu, Fast archiving and querying of heterogeneous sensor data streams, Digital Telecommunications, 2007. ICDT'07. Second International Conference on, pp. 28-28, 2007, IEEE
  • KQ Pu and Y Zhu, Efficient indexing of heterogeneous data streams with automatic performance configurations, Scientific and Statistical Database Management, 2007. SSBDM'07. 19th International Conference on, pp. 34-34,2007, IEEE
  • K Pu, V Hristidis and N Koudas, Syntactic rule-based approach to web service composition, Data Engineering, 2006. ICDE'06. Proceedings of the 22nd International Conference on, pp. 31-31, 2006, IEEE
  • QK Pu, On formal methods of multidimensional databases, 2006, University of Toronto
  • KQ Pu and AO Mendelzon, Typed functional query languages with equational specifications, Proceedings of the 14th ACM international conference on Information and knowledge management, pp. 233-234, 2005, ACM
  • X Yu, KQ Pu and N Koudas, Monitoring k-nearest neighbor queries over moving objects, Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on, pp. 631-642, 2005, IEEE
  • KQ Pu, Modeling, querying and reasoning about OLAP databases: a functional approach, Proceedings of the 8th ACM international workshop on Data warehousing and OLAP, pp. 1-8, 2005, ACM
  • KQ Pu, Functional Integration of Relational, OLAP and XML Data, Proceedings of VLDB Workshop on Information Integration on the Web (IIWeb-2004), pp. 97, 2004,
  • AO Mendelzon and KQ Pu, Concise descriptions of subsets of structured sets, Proceedings of the twenty-second ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems, pp. 123-133, 2003, ACM
  • KQ Pu, Modeling and control of discrete-event systems with hierarchical abstraction, MA. Sc. thesis, Dept. Elect. Comput. Eng., Univ. Toronto, Toronto, ON, Canada, 2000,
  • K Pu, Modeling and Control of Discrete-Event Systems with Hierarchical abstraction. Ma sc, 2000, Thesis, Dept. of Electl. & Cmptr. Engrg., Univ. of Toronto
  • KQ Pu, Theory Of Discrete Wavelet Transform And An Error Analysis Of The Pyramid Algorithm, 1998, Citeseer
  • RJ Miller, F Nargesian, E Zhu, C Christodoulakis, KQ Pu and P Andritsos, Making Open Data Transparent: Data Discovery on Open Data,
  • KQ Pu and Y Zhu, Efficient Indexing of Heterogeneous Data Streams with Automatic Performance Tuning,
  • KQ Pu, Algorithm and Complexity of the Unification Problem of a Polymorphic Attribute-based Type System,
  • Renée J. Miller, Fatemeh Nargesian, Erkang Zhu, Christina Christodoulakis, Ken Q. Pu, Periklis Andritsos, Making Open Data Transparent: Data Discovery on Open Data., IEEE Data Eng. Bull., 41 (2) , pp. 59-70, 2018,
  • F Nargesian, E Zhu, KQ Pu and RJ Miller, Table union search on open data,Proceedings of the VLDB Endowment, 11 (7) , pp. 813-825, 2018, VLDB Endowment
  • E Zhu, KQ Pu, F Nargesian and RJ Miller, Interactive navigation of open data linkages, Proceedings of the VLDB Endowment, 10 (12) , pp. 1837-1840, 2017,VLDB Endowment
  • E Zhu, F Nargesian, KQ Pu and RJ Miller, LSH ensemble: Internet-scale domain search, Proceedings of the VLDB Endowment, 9 (12) , pp. 1185-1196,2016, VLDB Endowment
  • Z Yu, Y Liu, X Yu and KQ Pu, Scalable distributed processing of K nearest neighbor queries over moving objects, IEEE Transactions on Knowledge and Data Engineering, 27 (5) , pp. 1383-1396, 2015, IEEE
  • MA Helala, FZ Qureshi and KQ Pu, Automatic parsing of lane and road boundaries in challenging traffic scenes, Journal of electronic imaging, 24 (5) ,pp. 053020, 2015, International Society for Optics and Photonics
  • O Hassanzadeh, KQ Pu, SH Yeganeh, RJ Miller, L Popa, MA Hernández and H Ho, Discovering linkage points over web data, Proceedings of the VLDB Endowment, 6 (6) , pp. 445-456, 2013, VLDB Endowment
  • K Q Pu, Recent Patents on Information Retrieval Using Natural Language and Keyword Query, Recent Patents on Computer Science, 3 (3) , pp. 186-194,2010, Bentham Science Publishers
  • Y Zhu, B Li and KQ Pu, Dynamic multicast in overlay networks with linear capacity constraints, IEEE Transactions on Parallel and Distributed Systems, 20 (7) , pp. 925-939, 2009, IEEE
  • KQ Pu and X Yu, Keyword query cleaning, Proceedings of the VLDB Endowment, 1 (1) , pp. 909-920, 2008, VLDB Endowment
  • KQ Pu and AO Mendelzon, Concise descriptions of subsets of structured sets,ACM Transactions on Database Systems (TODS), 30 (1) , pp. 211-248, 2005,ACM
  • Scientific Data Analysis (CSCI 2000U)
    The principal goal of this course is to build computational skills required for analyzing scientific data in a variety of data formats (e.g. CSV, text, binary, sound, image, etc.). Topics include: automation of data analysis tasks using command-line user interfaces (e.g., the Unix shell); managing code and data using a version control system; modular programming for scientific data analysis; debugging and testing scientific software; plotting data (i.e., two- and three-dimensional graphics).
  • Programming Languages (CSCI 3055U)
    This course is a survey of different types of programming languages and an introduction to the formal study of programming languages. This course provides the student with a deeper understanding of programming languages and the basis for choosing the right language for the job. Topics covered include procedural programming languages, functional programming languages, logic based languages, scripting languages, programming language semantics and the implementation of programming languages.
  • Compilers (CSCI 4020U)
    This course provides a detailed study of the compilation process for a procedural language. Students will develop an understanding of compiler design and put these principles into practice through the construction of a fully functioning compiler for a small procedural language using widely available tools for compiler construction and a general-purpose programming language.