Lukasz Golab

Lukasz Golab

Associate Professor and Canada Research Chair
Department of Management Sciences, Faculty of Engineering
Cross-appointed to the School of Computer Science, Faculty of Mathematics
University of Waterloo

Email: lgolab at uwaterloo dot ca

Bio: I joined Waterloo in 2011 and was awarded a Tier-2 Canada Research Chair in 2015. From 2006 to 2011 I was a Senior Member of Research Staff at AT&T Labs. I have a BSc in Computer Science from the University of Toronto (2001; with High Distinction) and a PhD in Computer Science from the University of Waterloo (2006; with Alumni Gold Medal).

Research interests (also see my Data Science Lab)

Data for good (sustainability, clean energy and transportation, health, education, equality)
Data profiling and cleaning (discovering column dependencies and business rules from data, detecting data errors)
Data systems (blockchains, data stream systems and real-time analytics, graph and social network mining, distributed data management)

Recent and upcoming professional service: Associate Editor for Information Systems; PC co-chair for DEBS 2020; Senior PC member for EDBT 2021; Review Board Member for PVLDB 2018; PC member for AAAI 2021, WSDM 2021, AACL-IJCNLP 2020, CIKM 2020, SIGIR 2020, SSDBM 2020, AMW 2020, ICDE 2020, EDM 2019, ICDE 2019, CIKM 2018, SIGMOD 2018, SSDBM 2018; Publicity co-chair for SIGMOD 2020, ICDE 2019

Recent teaching: MSCI446 (Data Mining), MSCI623 (Big Data Analytics). Data science course notes here

Media

Tutorials

Z. Abedjan, L. Golab, F. Naumann, Data Profiling, SIGMOD 2017, 1747-1751 and ICDE 2016, 1432-1435. Slides here
L. Golab, T. Johnson, Data Stream Warehousing, ICDE 2014, 1290-1293 and SIGMOD 2013, 949-952. Slides here

Publications (or see DBLP)

2020

S. Bryson, H. Davoudi, L. Golab, M. Kargar, Y. Lytvyn, P. Mierzejewski, J. Szlichta, M. Zihayat, Robust Keyword Search in Large Attributed Graphs, Information Retrieval Journal, 23: 502-524, 2020, Article DOI: 10.1007/s10791-020-09379-9
S. Chopra, A. Khan, M. Mirsafian, L. Golab, Gender differences in work-integrated learning experiences of STEM students: From applications to evaluations, Int. Journal of Work-Integrated Learning 21(3):253-274, 2020
M. S. Parsa, L. Golab, Social Media Mining to Understand the Impact of Co-operative Education on Mental Health, EDM 2020, 653-657
X. Meng, L. Golab, Parallel Scheduling of Data-Intensive Tasks, Euro-Par 2020, 117-133
D. Kumar, L. Mou, L. Golab, O. Vechtomova, Iterative edit-based unsupervised sentence simplification, ACL 2020, 7918-7928
J. Szlichta, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, Erratum for Discovering Order Dependencies through Order Compatibility, EDBT 2020, 659-663
M. Kargar, L. Golab, D. Srivastava, J. Szlichta, M. Zihayat, Effective Keyword Search over Weighted Graphs, TKDE, 2020, Article DOI: 10.1109/TKDE.2020.2985376
R. Agarwal, R. Cohen, L. Golab, A. Tsang, Locating influential agents in social networks: Budget-constrained seed set selection, Canadian AI 2020, 15-28
R. Agarwal, D. Kumar, L. Golab, S. Keshav, Consentio: Managing Consent to Data Access using Permissioned Blockchains, IEEE Int. Conf. on Blockchain and Cryptocurrency (ICBC) 2020
C. Gorenflo, L. Golab, S. Keshav, XOX Fabric: A Hybrid Approach to Transaction Execution, IEEE Int. Conf. on Blockchain and Cryptocurrency (ICBC) 2020
C. Gorenflo, S. Lee, L. Golab, S. Keshav, FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second, Int. Journal of Network Management, 30(5): e2099, September/October 2020, Article DOI: 10.1002/nem.2099
A. Khan, L. Golab, Reddit Mining to Understand Gendered Movements, EDBT Workshop on Data Analytics Solutions for Real-Life Applications, 3:1-3:8
A. Jacobs, S. Chopra, L. Golab, Reddit Mining to Understand Women's Issues in STEM, EDBT Workshop on Data Analytics Solutions for Real-Life Applications, 10:1-10:8
L. Chen, L. Golab, Micro-Journal Mining to Understand Mood Triggers, Computing, 102(5):1227-1244 (2020)
A. Khan, L. Golab, M. Kargar, J. Szlichta, M. Zihayat, Compact Group Discovery in Attributed Graphs and Social Networks, Journal of Information Processing and Management 57(2): 102054, March 2020

2019

H. Saxena, L. Golab, I. Ilyas, Distributed Implementations of Dependency Discovery Algorithms, PVLDB 12(11): 1624-1636, 2019
M. Vollmer, L. Golab, K. Boehm, D. Srivastava, Informative Summarization of Numeric Data, SSDBM 2019, 97-108
C. Gorenflo, L. Golab, S. Keshav, Mitigating Trust Issues in Electric Vehicle Charging using a Blockchain, e-Energy 2019, 160-164
S. Chopra, A. Khan, M. Mirsafian, L. Golab, Gender Differences in Work-Integrated Learning Assessments, EDM 2019, 524-527
H. Davoudi, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, J. Szlichta, Bringing Order to Data, AMW 2019, 11:1-11:5
D. Kumar, R. Cohen, L. Golab, Online abuse detection: the value of preprocessing and neural attention models, NAACL workshop on Computational Approaches to Subjectivity, Sentiment & Social Media Analysis (WASSA), 16-24
S. Chopra, M. Mirsafian, A. Khan, L. Golab, Gender Differences in Science and Engineering: A Data Mining Approach, EDBT workshop on Data Analytics Solutions for Real-Life Applications, 7:1-7:8
C. Gorenflo, S. Lee, L. Golab, S. Keshav, FastFabric: Scaling Hyperledger Fabric to 20,000 Transactions per Second, IEEE Int. Conf. on Blockchain and Cryptocurrency (ICBC) 2019, 455-463
H. Saxena, L. Golab, I. Ilyas, Distributed Discovery of Functional Dependencies, ICDE 2019, 1590-1593
L. Golab, Types of Stream Processing Algorithms, Encyclopedia of Big Data Technologies, Springer, 2019

2018

S. Chopra, L. Golab, T. J. Pretti, A. Toulis, Using data mining methods for research in co-operative education, Int. Journal of Work Integrated Learning, 19(3): 297-310, 2018
Z. Abedjan, L. Golab, F. Naumann, T. Papenbrock, Data Profiling, Morgan & Claypool Publishers, 2018
K. El Gebaly, G. Feng, L. Golab, F. Korn, D. Srivastava, Explanation Tables, IEEE Data Engineering Bulletin, 41(3):43-51, 2018
J. Szlichta, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, Effective and Complete Discovery of Bidirectional Order Dependencies via Set-based Axioms, VLDB Journal, 27(4): 573-591
S. Chopra, H. Gautreau, A. Khan, M. Mirsafian, L. Golab, Gender Differences in Undergraduate Engineering Applicants: A Text Mining Approach, EDM 2018, 44-54
S. Chopra, L. Golab, Job Description Mining to Understand Work-Integrated Learning, EDM 2018, 32-43
L. Gao, L. Golab, T. Ozsu, G. Aluc, Stream WatDiv - A Streaming RDF Benchmark, SIGMOD workshop on Semantic Big Data, 3:1-3:6
M. Zihayat, A. An, L. Golab, M. Kargar, J. Szlichta, Effective Team Formation in Expert Networks, AMW 2018, 4:1-4:4
M. Langouri, Z. Zheng, F. Chiang, L. Golab, J. Szlichta, Contextual Data Cleaning, ICDE workshop on Context in Analytics, 21-24
G. Tang, S. Keshav, L. Golab, K. Wu, Bikeshare Pool Sizing for Bike-And-Ride Multimodal Transit, Trans. on Intelligent Transportation Systems, 19(7): 2279-2289
S. Chopra, Y. Jiang, A. Toulis, L. Golab, Data Analytics to Improve Co-Operative Education, EDBT workshop on Data Analytics Solutions for Real-Life Applications, 16-21
A. Mihaylov, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, J. Szlichta, FastOD: Bringing Order to Data, ICDE 2018, 1561-1564, demo paper
Z. Zheng, M. Langouri, Z. Qu, I. Currie, F. Chiang, L. Golab, J. Szlichta, FastOFD: Contextual Data Cleaning with Ontology Functional Dependencies, EDBT 2018, 694-697, demo paper
A. Andrade, S. Chopra, B. Nurlybayev, L. Golab, Quantifying the Impact of Entrepreneurship on Cooperative Job Creation, Int. Journal of Work Integrated Learning, 19(1): 51-68

2017

X. Meng, L. Golab, Optimal Reducer Placement to Minimize Data Transfer in MapReduce-Style Processing, IEEE BigData 2017, 339-346
S. Baskaran, A. Keller, F. Chiang, L. Golab, J. Szlichta, Efficient Discovery of Ontology Functional Dependencies, CIKM 2017, 1847-1856
C. Gorenflo, I. Rios, L. Golab, S. Keshav, Usage Patterns of Electric Bicycles: An Analysis of the WeBike Project, J. of Advanced Transportation, 2017, Article ID 3739505
Y. Yang, L. Golab, M. T. Ozsu, ViewDF: Declarative Incremental View Maintenance for Streaming Data, Information Systems, 71 (2017) 55-67
A. Toulis, L. Golab, Social Media Mining to Understand Public Mental Health, DMAH workshop at VLDB 2017, 55-70
K. El Gebaly, L. Golab, J. Lin, Portable In-Browser Data Cube Exploration, IDEA workshop at KDD 2017, 35-39
C. Gorenflo, L. Golab, S. Keshav, Managing Sensor Data Streams: Lessons Learned from the WeBike Project, SSDBM 2017, 1:1-1:11
S. Fink, L. Golab, S. Keshav, H. de Meer, How Similar is the Usage of Electric Cars and Electric Bicycles?, EV-Sys 2017, 334-340
A. Toulis, L. Golab, Graph Mining to Characterize Competition for Employment, Network Data Analytics workshop at SIGMOD 2017, 3:1-3:7
R. Miller, L. Golab, C. Rosenberg, Modelling Weather Effects for Impact Analysis of Residential Time-of-Use Electricity Pricing, Energy Policy 105 (2017) 534-546
J. Szlichta, P. Godfrey, L. Golab, M. Kargar, D. Srivastava, Effective and Complete Discovery of Order Dependencies via Set-based Axiomatization. PVLDB 10(7): 721-732, 2017
G. Feng, L. Golab, D. Srivastava, Scalable Informative Rule Mining, ICDE 2017, 48
M. Zihayat, A. An, L. Golab, M. Kargar, J. Szlichta, Authority-Based Team Discovery in Social Networks, EDBT 2017, 498-501
X. Liu, L. Golab, W. Golab, I. Ilyas, S. Jin, Smart Meter Data Analytics: Systems, Algorithms and Benchmarking, TODS 42(1): 2:1-2:39, 2017

2016

M. Kargar, L. Golab, J. Szlichta, eGraphSearch: Effective Keyword Search in Graphs, CIKM 2016, 2461-2464, demo paper. Tech report here
I. Rios, L. Golab, S. Keshav, Analyzing the Usage Patterns of Electric Bicycles, EV-Sys 2016, 2
A. Baer, P. Casas, A. D’Alconzo, P. Fiadino, L. Golab, M. Mellia, E. Schikuta, DBStream: A Holistic Approach to Large-Scale Network Traffic Monitoring and Analysis, Computer Networks 107 (2016) 5-19
L. Gebhard, L. Golab, S. Keshav, H. de Meer, Range prediction for electric bicycles, e-Energy 2016, 224-234
Y. Jiang, L. Golab, On Competition for Undergraduate Co-op Placements: A Graph Mining Approach, EDM 2016, 394-399
Y. Jiang, R. Levman, L. Golab, J. Nathwani, Analyzing the Impact of the 5CP Ontario Peak Reduction Program on Large Consumers, Energy Policy 93 (2016) 96-100
Y. Jiang, S. J. Syed, L. Golab, Data mining of undergraduate course evaluations, Informatics in Education 15(1): 85-102

2015

Y. Yang, L. Golab, M. T. Ozsu, ViewDF: declarative incremental view maintenance for streaming data, VLDB Workshop on Business Intelligence for the Real Time Enterprise (BIRTE) 2015. Early version here
C. Ge, M. Kaufmann, L. Golab, P. M. Fischer, A. Goel, Indexing bi-temporal windows, SSDBM 2015, 19
Z. Abedjan, L. Golab, F. Naumann, Profiling relational data - a survey, VLDB Journal 24(4): 557-581
J. Szlichta, L. Golab, D. Srivastava, On Axiomatization and Inference Complexity over a Hierarchy of Functional Dependencies, AMW 2015
Y. Jiang, S. Lee, L. Golab, Analyzing student and employer satisfaction with cooperative education through multiple data sources, Asia-Pacific Journal of Cooperative Education, 16(4):225-240, 2015
X. Gao, L. Golab, S. Keshav, What's wrong with my solar panels: a data-driven approach, EnDM 2015, 86-93
X. Liu, L. Golab, W. Golab, I. Ilyas, Benchmarking Smart Meter Data Analytics, EDBT 2015, 385-396
A. Baer, L. Golab, S. Ruehrup, M. Schiavone, P. Casas, Cache-Oblivious Scheduling of Shared Workloads, ICDE 2015, 855-866
L. Golab, F. Korn, F. Li, B. Saha, D. Srivastava, Size-Constrained Weighted Set Cover, ICDE 2015, 879-890
X. Liu, L. Golab, I. Ilyas, SMAS: A Smart Meter Data Analytics System, ICDE 2015, 1476-1479, demo paper

2014

A. Baer, A. Finamore, P. Casas, L. Golab, M. Mellia, Large-Scale Network Traffic Monitoring with DBStream, a System for Rolling Big Data Analysis, IEEE BigData 2014, 165-170
K. El Gebaly, P. Agrawal, L. Golab, F. Korn, D. Srivastava, Interpretable and Informative Explanations of Outcomes, PVLDB 8(1):61-72, 2014
L. Golab, M. Hadjieleftheriou, H. Karloff, B. Saha, Distributed Data Placement to Minimize Communication Costs via Graph Partitioning, SSDBM 2014, 20-31. Tech report here: CoRR abs/1312.0285
A. Baer, P. Casas, L. Golab, A. Finamore, DBStream: an Online Aggregation, Filtering and Processing System for Network Traffic Monitoring, Int. Workshop on Traffic Analysis and Characterization (TRAC) 2014, 611-616
S. J. Syed, Y. Jiang, L. Golab, Data Mining of Undergraduate Course Evaluations, EDM 2014, 347-348
T. Carpenter, L. Golab, S. J. Syed, Is the grass greener? Mining electric vehicle opinions, e-Energy 2014, 241-252
Y. Jiang R. Levman, L. Golab, J. Nathwani, Predicting peak-demand days in the Ontario peak reduction program for large consumers, e-Energy 2014, 221-222
O. Ardakanian, N. Koochakzadeh, R. P. Singh, L. Golab, S. Keshav, Computing Electricity Consumption Profiles from Household Smart Meter Data, EnDM 2014, 140-147. Slides here
L. Golab, H. Karloff, F. Korn, B. Saha, D. Srivastava, Discovering Conservation Rules, TKDE, 26(6):1332-1348, 2014
G. Beskales, I. Ilyas, L. Golab, A. Galuillin, Sampling from Repairs of Conditional Functional Dependency Violations, VLDB Journal, 23(1):103-128, 2014

2013

C. Ge, L. Golab, Lazy data structure maintenance for main-memory analytics over sliding windows, DOLAP 2013, 33-38
M. Deziel, D. Olawo, L. Truchon, L. Golab, Analyzing the mental health of Engineering students using classification and regression, EDM 2013, 228-231
G. Beskales, I. Ilyas, L. Golab, A. Galiullin, On the Relative Trust between Inconsistent Data and Inaccurate Constraints, ICDE 2013, 541-552
L. Golab, Data Warehouse Quality: Summary and Outlook, in S. Sadiq (ed.), Handbook of Data Quality Research and Practice, Springer-Verlag Berlin Heidelberg 2013

2012

A. Baer, L. Golab, Towards Benchmarking Stream Data Warehouses, DOLAP 2012, 105-112
L. Golab, T. Johnson, S. Sen, J. Yates, A Sequence-Oriented Stream Warehouse Paradigm for Network Monitoring Applications, PAM 2012, 53-63
L. Golab, H. Karloff, F. Korn, B. Saha, D. Srivastava, Discovering Conservation Rules, ICDE 2012, 738-749
L. Golab, T. Johnson, V. Shkapenyuk, Scalable Scheduling of Updates in Streaming Data Warehouses, TKDE, 24(6): 1092-1105, 2012

2011

M. Bateni, L. Golab, M. Hajiaghayi, H. Karloff, Scheduling to Minimize Staleness and Stretch in Real-Time Data Warehouses, Theory of Computing Systems, 49(4):757-780, 2011
L. Golab, F. Korn, D. Srivastava, Efficient and Effective Analysis of Data Quality using Pattern Tableaux, IEEE Data Engineering Bulletin, 34(3):26-33, 2011
L. Golab, F. Korn, D. Srivastava, Discovering Pattern Tableaux for Data Quality Analysis: a Case Study, QDB 2011, 47-53, 2011
L. Golab, T. Johnson, Consistency in a Stream Warehouse, CIDR 2011, 114-122

2010

L. Golab, M. T. Ozsu, Data Stream Management, Morgan & Claypool Publishers, 2010
G. Beskales, I. Ilyas, L. Golab, Sampling the Repairs of Functional Dependency Violations under Hard Constraints, PVLDB 3(1):197-207, 2010
L. Golab, H. Karloff, F. Korn, D. Srivastava, Data Auditor: Exploring Data Quality and Semantics using Pattern Tableaux, PVLDB 3(2):1641-1644, 2010, demo paper
D. Srivastava, L. Golab, R. Greer, T. Johnson, J. Seidel, V. Shkapenyuk, O. Spatscheck, J. Yates, Enabling Real Time Data Analysis, PVLDB 3(1): 1-2, 2010

2009

L. Golab, H. Karloff, F. Korn, A. Saha, D. Srivastava, Sequential Dependencies, PVLDB 2(1):574-585, 2009
L. Golab, T. Johnson, J. S. Seidel, V. Shkapenyuk, Stream Warehousing with DataDepot, SIGMOD 2009, 847-854
G. Cormode, L. Golab, F. Korn, A. McGregor, D. Srivastava, X. Zhang, Estimating the Confidence of Conditional Functional Dependencies, SIGMOD 2009, 469-482
L. Golab, T. Johnson, V. Shkapenyuk, Scheduling Updates in a Real-Time Stream Warehouse, ICDE 2009, 1207-1210
M. Bateni, L. Golab, M. Hajiaghayi, H. Karloff, Scheduling to Minimize Staleness and Stretch in Real-Time Data Warehouses, SPAA 2009, 29-38
L. Golab, Stream Models, Encyclopedia of Database Systems, 2009, 2834-2836
L. Golab, Data Stream, Encyclopedia of Database Systems, 2009, 638

2008

L. Golab, H. Karloff, F. Korn, D. Srivastava, B. Yu, On Generating Near-Optimal Tableaux for Conditional Functional Dependencies, PVLDB 1(1):376-390, 2008
L. Golab, T. Johnson, O. Spatscheck, Prefilter: Predicate Pushdown at Streaming Speeds, SSPS 2008, 29-37
L. Golab, T. Johnson, N. Koudas, D. Srivastava, D. Toman, Optimizing Away Joins on Data Streams, SSPS 2008, 48-57

2006

L. Golab, K. G. Bijay, M. T. Ozsu, Multi-Query Optimization of Sliding Window Aggregates by Schedule Synchronization, CIKM 2006, 844-845
L. Golab, P. Prahladka, M. T. Ozsu, Indexing Time-Evolving Data with Variable Lifetimes, SSDBM 2006, 265-274
L. Golab, K. G. Bijay, M. T. Ozsu, On Concurrency Control in Sliding Window Queries over Data Streams, EDBT 2006, 608-626

2005

L. Golab, M. T. Ozsu, Update-Pattern-Aware Modeling and Processing of Continuous Queries, SIGMOD 2005, 658-669

2004

L. Golab, S. Garg, M. T. Ozsu, On Indexing Sliding Windows over On-Line Data Streams, EDBT 2004, 712-729
L. Golab, D. DeHaan, A. Lopez-Ortiz, E. Demaine, Finding Frequent Items in Sliding Windows with Multinomially-Distributed Item Frequencies, SSDBM 2004, 425-426
L. Golab, Querying Sliding Windows Over Online Data Streams, EDBT Ph.D. Workshop 2004, 1-11

2003

L. Golab, D. DeHaan, E. Demaine, A. Lopez-Ortiz, J. I. Munro, Identifying Frequent Items in Sliding Windows over On-Line Packet Streams, IMC 2003, 173-178
L. Golab, M. T. Ozsu, Processing Sliding Window Multi-Joins in Continuous Queries over Data Streams, VLDB 2003, 500-511
L. Golab, M. T. Ozsu, Issues in Data Stream Management, SIGMOD Record, 32(2):5-14, 2003