Roles and responsibilities
I am an Associate Research Officer in the Scientific Data Mining team at the Digital Technologies Research Center. I collaborate with government, research and industrial partners/stakeholders to analyze high-volume, complex data.
Current research and/or projects
My research centers on employing both established and innovative techniques for analyzing data streams. Specifically, I concentrate on harnessing the edge-fog-cloud continuum to efficiently manage the influx of data and conduct analytical tasks. The overarching goal is to identify opportunities and mitigate risks across various domains.
Education
Masters of Science and Engineering (MScE), Geodesy & Geomatics Engineering - University of New Brunswick, 2022
Graduate Certificate, Object Oriented Software Engineering - Southern Alberta Institute of Technology, 1999
Bachelor, Economics - Université de Moncton, 1984
Awards
2021 : Best Student Paper Award - 10th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS). For the paper titled : An Automated Clustering Process for Helping Practitioners to Identify Similar EV Charging Patterns across Multiple Temporal Granularities.
2021 : Albert Stevens Award - Student Paper Competition, Master’s Category - Canadian Transportation Research Forum. For the paper titled : Autonomous Vehicles and the Moral Domain.
2017 : NRC Research and Technology Breakthrough of the Year Award - National Research Council. For establishing quantitative trait loci (QTL) and expression quantitative trait loci (eQTL) research pipeline published in BMC Bioinformatics issue 17, page 531.
2008 : Digital Technologies - Director’s Award - National Research Council. For outstanding contributions towards the success of the Inaugural NB Innovation Forum.
2006 : Digital Technologies Recognition Certificate - National Research Council. For the important role played in the office relocation from Saint John to Fredericton, New Brunswick.
2003 : CS Atlantic Team Award - National Research Council. For outstanding contributions towards the establishment of IIT’s new research programs in the Atlantic. Specifically, for the procurement, installation and configuration of IIT Atlantic’s network and server infrastructure within severe time constraints.
Key publications
Cao, H., Wachowicz, M., Richard, R., & Hsu, C. H. (2023). Fostering new vertical and horizontal IoT applications with intelligence everywhere. Collective Intelligence, 2(4).
Richard, R., Cao, H., & Wachowicz, M. (2022). EVStationSIM: An end-to-end platform to identify and interpret similar clustering patterns of EV charging stations across multiple time slices. Applied Energy, 322, 119491.
Richard, R., Cao, H., & Wachowicz, M. (2022). A Spatial-Temporal Comparison of EV Charging Station Clusters Leveraging Multiple Validity Indices. In Smart Cities, Green Technologies, and Intelligent Transport Systems: 10th International Conference, SMARTGREENS 2021, and 7th International Conference, VEHITS 2021, Virtual Event, April 28–30, 2021, Revised Selected Papers (pp. 34-57). Cham: Springer International Publishing.
Belacel, N., Richard, R., & Xu, Z. M. (2022). An LSTM Encoder-Decoder Approach for Unsupervised Online Anomaly Detection in Machine Learning Packages for Streaming Data. In 2022 IEEE International Conference on Big Data (Big Data) (pp. 3348-3357). IEEE Computer Society
Belacel, N., Richard, R., Rangavajjala, D. P., & Adhaduk, R. (2022). Online Anomaly Detection for Streaming Data Implemented on Top of Kafka, Scikit-Multiflow and River. In Proceedings of the Future Technologies Conference (FTC) 2021, Volume 3 (pp. 826-836). Springer International Publishing.
Richard, R., Cao, H., & Wachowicz, M. (2020, September). Discovering EV Recharging Patterns through an Automated Analytical Workflow. In 2020 IEEE International Smart Cities Conference (ISC2) (pp. 1-8). IEEE.
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