[ About me | Research | Teaching | Publications | Awards | Talks ]

Suprio Ray

Ph. D. (Univ. of Toronto), M.Sc (Univ. of British Columbia), B. E. (NIT)

Assistant Professor
Computer Science Department
University of New Brunswick
Fredericton, Canada
Email: sray@unb.ca
Phone: 458-7280
Office: Gillin Hall C106

logo2

                              


ABOUT ME

I am an Assistant Professor at the Faculty of Computer Science, University of New Brunswick, Fredericton. I lead the Big Data Systems and Analytics Lab. I received my Ph.D. from the Computer Science Department, University of Toronto. I obtained an M.Sc. (Computer Science) from University of British Columbia and a Bachelor of Engineering (Computer Science and Engineering) from NIT, Trichy.

Previously, I worked for a number of years as a software engineer, in companies including, Oracle, Lucent Technologies (Bell Labs), and Webtech Wireless. I also did a PhD research internship at SAP. A detailed CV can be provided on request. I am also associated with the IBM Centre for Advanced Studies Atlantic (CASA) and I regularly collaborate with researchers from other research institutes.

RESEARCH

I am interested in various aspects of Big Data management, including the management of spatial, spatio-temporal, graph data, as well as, analytical workloads. I explore how to build scalable systems and develop novel approaches for query processing and analytics. My research interests include:   
   - Big Data and database management systems
   - Spatial and spatio-temporal data processing
   - Run-time Systems for Scalable Data Science
   - Data management for the Internet of Things (IoT), Smart Grid and Healthcare analytics
   - Parallel and distributed systems, and Cloud computing

If you are interested in any of these research areas, please feel free to contact me. I am particularly looking for potential graduate students who have strong programming and software implementation skills. Previous research experience or work experience in the software industry is a plus.

Current projects

Project Summary
Scalable Data Science and Advanced Analytics The volume and velocity of data generated from a variety of sources are far outpacing the available storage and processing capacity – the term Big Data is used to signify this. Data science enables one to bring structure to large quantities of data and make analysis possible. However, existing data systems are not able the meet the computational challenges of Data Science applications. The goal of the research will be to devise new approaches to data processing that can support analysis on data at massive scales.
We have developed a data science benchmark, called Sanzu, which is accessible here.
Data Management on Modern Hardware We are looking into query processing in the changing landscape of modern hardware. The advent of multi-core processors, along with the ever growing main memory, has fundamentally changed how Big Data is processed. In this research, we are exploring how to exploit the growing memory, core count and GP-GPUs in the context of in-memory databases.
Recently, we demonstrated that in-memory hash joins are acutely affected by dataset skew and we proposed a solution for this.
Scalable Spatio-temporal Big Data Systems With the rapid rise in the volume and variety of spatial data, “spatial analytics” is no longer just a niche in scientific organizations and academia. The popularity of on-line services are also contributing to the growth of spatial analysis applications. We  developed Niharika, a spatial data analysis system for the Cloud. We also built a parallel in-memory spatial query execution system called  SPINOJA. We also developed an in-memory spatio-temporal index PASTIS that supports order of magnitude better update throughput than the state-of-the-art, while supporting thousands of concurrent historical, present and predictive spatio-temporal range queries. Previously we introduced a spatial database benchmark called Jackpine, which can be accessed here.
Rich Geo-spatial Query Processing With the growing data volume and popularity of Web services and Location-Based Services (LBS) new spatio-textual applications are emerging. These applications are contributing to a deluge of geo-tagged data. Increasingly, this data integrates multiple types of data, such as, textual data, location data, social information, scientific measurements and multimedia data. This "enriched" geo-referenced data offers significant potential for knowledge discovery. In this project, we are exploring efficient processing of novel spatio-textual queries.
Privacy-preserving Query Processing in the Cloud With the rising data volume, companies are increasingly using the Cloud to stage and process their data. However, this comes with the challenges of privacy and information security. In this project we are interested in addressing the question of how to support privacy-conscious efficient query execution in the Cloud.


Past projects

As part of my MSc thesis, I developed a realistic mobility model generator called GEMM.

TEACHING

CS6999 Directed Studies:  please contact me for exciting projects

Course Id Title Semester taught
CS2545 Data Science for Big Data Analysis Fall 2016, Fall 2017, Fall 2018
CS4545/CS6545 Big Data Systems Winter 2016, Winter 2017, Winter 2018, Winter 2019
INFO3403 Information System Administration Winter 2017, Winter 2018, Winter 2019
CS6585 Database Foundations Fall 2016
INFO1103 Data and Information Management Fall 2015, Winter 2016

PUBLICATIONS  [ Google scholar  ]

Conferences and Journals

Maria Patrou, Md Mahbub Alam, Puya Memarzia, Suprio Ray, Virendra Bhavsar, Kenneth Kent, Gerhard Dueck.  DISTIL: A Distributed In-Memory Data Processing System for Location-Based Services. International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS). Seattle, Washington,  2018. (accepted)


Md Mahbub Alam, Suprio Ray and Virendra C. Bhavsar.   A Performance Study of Big Spatial Data Systems. ACM SIGSPATIAL International Workshop on analytics for Big Geospatial Data (BigSpatial 2018). Seattle, Washington,  2018. (accepted)


Suprio Ray and Bradford G. Nickerson.   Improving Parallel Performance of Temporally Relevant Top-K Spatial Keyword Search. ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks (LocalRec 2018). Seattle, Washington,  2018. (accepted)


Puya Memarzia, Suprio Ray and Virendra C Bhavsar.  On Improving Data Skew Resilience In Main-memory Hash Joins. In Proceedings of International Database Engineering & Applications Symposium (IDEAS 2018),   Villa San Giovanni, Italy,   2018.  [pdf]


Pegah Yazdkhasti, Suprio Ray, Chris P. Diduch and Liuchen Chang.  Using a Cluster-Based Method for Controlling the Aggregated Power Consumption of Air Conditioners in a Demand-Side Management Program. In Proceedings of 2018 International Conference on Smart Energy Systems and Technologies (SEST),   Sevilla, Spain,   2018.  


Alex Watson, Deepigha Vittal Babu and Suprio Ray.  Sanzu: A Data Science Benchmark. IEEE International Conference on Big Data (IEEE BigData 2017),   Boston,   2017.    Acceptance rate 18%. [pdf]


Rene Richard and Suprio Ray.  A Tale of Two Cities: Analyzing Road Accidents with Big Spatial Data. IEEE International Workshop on Big Spatial Data (BSD) held in conjunction with IEEE International Conference on Big Data (IEEE BigData 2017),   Boston,   2017.   


Suprio Ray, Rolando Blanco, and Anil K. Goel.  High Performance Location-Based Services In A Main-Memory Database. GeoInformatica,  2017.  doi:10.1007/s10707-016-0278-6    


Antonio Filieri, Martina Maggio, Konstantinos Angelopoulos, Nicolas D'Ippolito, Ilias Gerostatopoulos, Andreas Hempel, Pooyan Jamshidi, Evangelia Kalyvianaki, Cristian Klein, Filip Krikava, Sasa Misailovic, Alessandro Papadopoulos, Suprio Ray, Amir M Sharifloo, Stepan Shevtsov, Mateusz Ujma and Thomas Vogel.  Control Strategies for Self-Adaptive Software Systems.. ACM Transactions on Autonomous and Adaptive Systems TAAS,  2017.


D Haynes, S Ray, S Manson.  Terra Populus: Challenges and Opportunities with Heterogeneous Big Spatial Data.. Advances in Geocomputation,  2017.  


Suprio Ray and Bradford G. Nickerson.  Dynamically Ranked Top-K Spatial Keyword Search. International ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data (GeoRich 2016, Co-located with SIGMOD/PODS 2016), San Francisco, California,  2016.  


Suprio Ray, Angela Demke Brown, Nick Koudas, Rolando Blanco, and Anil Goel.  Parallel In-Memory Trajectory-based Spatiotemporal Topological Join. In Proceedings of IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, California,  2015. Acceptance rate 17%.  [pdf]


Bogdan Simion, Daniel Ilha, Suprio Ray, Leslie Barron, Angela Demke Brown, and Ryan Johnson.  Slingshot: A Modular Framework for Designing Data Processing Systems. In Proceedings of IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, California,  2015. Acceptance rate 17%.


David Haynes, Suprio Ray, Steve Manson, and Ankit Soni.  High Performance Dynamic Analysis of Big Spatial Data. IEEE Big Data in the Geosciences Workshop, held in conjunction with IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, California,  2015.


David Haynes, Suprio Ray, Steven Manson, David Van Riper, Ankit Soni and Angela Demke Brown.  Towards A High Performance System for Heterogeneous Big Spatial Data. In Proceedings of the 2015 CyberGIS All Hands Meeting (CyberGIS AHM'15), Reston, Virginia,  2015.


Antonio Filieri, Martina Maggio, Konstantinos Angelopoulos, Nicolas D'Ippolito, Ilias Gerostathopoulos, Andreas Berndt Hempel, Henry Hoffmann, Pooyan Jamshidi, Evangelia Kalyvianaki, Cristian Klein, Filip Krikava, Sasa Misailovic, Alessandro Vittorio Papadopoulos, Suprio Ray, Amir M. Sharifloo, Stepan Shevtsov, Mateusz Ujma, and Thomas Vogel. Software Engineering Meets Control Theory. In Proceedings of the 10th International Symposium on Software Engineering for Adaptive and Self-Managing Systems (SEAMS), Florence, Italy, 2015. Acceptance rate 29%.


Suprio Ray, Rolando Blanco, and Anil K. Goel.  Supporting Location-Based Services in a Main-Memory Database. In Proceedings of the IEEE International Conference on Mobile Data Management (MDM). Brisbane, Australia,  2014. Best paper award. [pdf]


Suprio Ray.  Towards High Performance Spatio-temporal Data Management Systems. In Proceedings of the Ph.D. Colloquium, held in conjunction with IEEE International Conference on Mobile Data Management (MDM). Brisbane, Australia,  2014. Best paper award.


Suprio Ray, Bogdan Simion, Angela Demke Brown and Ryan Johnson. Skew-Resistant Parallel In-memory Spatial Join.  In Proceedings of the International Conference on Scientific and Statistical Database Management (SSDBM). Aalborg, Denmark,  2014. [pdf]


Suprio Ray, Bogdan Simion, Angela Demke Brown and Ryan Johnson. A Parallel Spatial Data Analysis Infrastructure for the Cloud. In Proceedings of the International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS). Orlando, Florida,  2013. Acceptance rate 17%[pdf]


Suprio Ray, Rolando Blanco, and Anil K. Goel. Enhanced Database Support for Location-Based Services. In Proceedings of the International Workshop on GeoStreaming (IWGS). Orlando, Florida,  2013.


Bogdan Simion, Suprio Ray, Angela Demke Brown. Surveying the Landscape: An In-Depth  Analysis of Spatial Database Workloads.  In Proceedings of the International Conference on Advances in Geographic Information Systems (ACM SIGSPATIAL GIS). Redondo Beach, California,  2012. Acceptance rate 17%.


Bogdan Simion, Suprio Ray, Angela Demke Brown.  Speeding up Spatial Database Query Execution using GPUs. In Proceedings of the Workshop on using Emerging Parallel Architectures (WEPA), ICCS, Omaha, Nebraska, 2012.


Suprio Ray, Bogdan Simion, and Angela Demke Brown. Jackpine: A Benchmark to Evaluate Spatial Database Performance. In Proceedings of the IEEE International Conference on Data Engineering (ICDE), Hannover, Germany, 2011. Acceptance rate 19.8%[pdf]


Alexandra Fedorova, Viren Kumar, Vahid Kazempour, Suprio Ray, and Pouya Alagheband. Cypress: A Scheduling Infrastructure for a Many-Core Hypervisor. In Proceedings of the Workshop on Managed Multi-Core Systems (MMCS'08) held in conjunction with the 17th International Symposium on High Performance Distributed Computing (HPDC-17), Boston, 2008.


Michael J. Feeley, Norman C. Hutchinson and Suprio Ray. Realistic Mobility for Mobile Ad Hoc Network Simulation. In Proceedings of the International Conference on Ad-hoc, Mobile, and Wireless Networks (ADHOC-NOW), Vancouver, Canada, 2004. [pdf]


Suprio Ray and Kris De Volder. Explicit Programming Approach for Modeling Agent Coordination. In Proceedings of the OOPSLA Workshop on Agent-Oriented Methodologies, Seattle, 2002.


Thesis

Suprio Ray. High Performance Spatial and Spatio-temporal Data Processing. PhD Thesis. University of Toronto, June 2015. [pdf]

Suprio Ray. Realistic Mobility for MANET Simulation. Master’s Thesis. University of British Columbia, December 2003. [pdf]



Patents


Suprio Ray, Rolando Blanco, and Anil K. Goel. Parallel Spatio-temporal Indexing For High-Update Workloads and Query Processing. US Patent Appl 20,150,081,719, 2015.


AWARDS

Harrison McCain Foundation Young Scholars award, 2016

Doctoral Completion Award, 2014 -2015

IBM Best Student Paper Award - IEEE MDM, 2014

IBM PhD Student Colloquium Paper Award - IEEE MDM PhD Colloquium, 2014

Heidelberg Laureate Forum invitee, 2014

NSERC Postgraduate Scholarship (Doctoral), 2012 – 2014

Ontario Graduate Scholarship, 2012-2013 (declined)

Helen Sawyer Hogg Graduate Admissions Award, 2012

ICCR Scholarship, 1995 – 1999

TALKS

Invited talks

Big Data – Research Opportunities and Challenges. ACENET Open House, Fredericton, 2016

Big Data – Research Opportunities and Challenges. UNB Research Discussion Forum: Leveraging Advanced Computing for Research & Innovation in New Brunswick, 2015

Big Spatial and Spatio-temporal Query Processing in Main Memory. High Performance Geoprocessing Symposium, Ottawa, 2014

Parallel Spatial Join Query Processing: Challenges and Opportunities. LocationTech Meetup,  Toronto, 2014

Extending Database Support for Location-Based Services. SAP Research Seminar. 2013

A parallel spatial data analysis infrastructure for the Cloud. University of Waterloo, Database Research Group Seminar, 2013

Ecommerce Systems with Wireless and GPS Technologies, Sauder School of Business, University of British Columbia, 2005, 2006 and 2007


Conference presentations


ACM SIGMOD Workshop on Managing and Mining Enriched Geo-Spatial Data (GeoRich 2016), San Francisco, California, 2016

IEEE International Conference on Big Data (IEEE BigData 2015), Santa Clara, California, 2015

International Conference on Mobile Data Management (MDM). Brisbane, Australia, 2014

PhD Colloquium, held in conjunction with International Conference on Mobile Data Management  (MDM). Brisbane, Australia, 2014

International Conference on Scientific and Statistical Database Management (SSDBM). Aalborg,  Denmark, 2014

International Conference on Advances in Geographic Information Systems (SIGSPATIAL GIS),  Orlando, Florida, 2013

International Workshop on GeoStreaming (IWGS), Orlando, Florida, 2013

International Conference on Data Engineering (ICDE), Hannover, Germany, 2011

Workshop on Managed Multi-Core Systems (MMCS), Boston, USA, 2008

International Conference on Ad-hoc, Mobile, and Wireless Networks (ADHOC-NOW), Vancouver,   Canada, 2004

severalvisitors.