Biography

Dr. Makonin received a Ph.D. degree in computing science from Simon Fraser University (SFU), Burnaby, Canada, in 2014. He is an Adjunct Professor in the School of Engineering Science and the Principal Investigator of the Computational Sustainability Lab at Simon Fraser University (SFU). He also has the position of Head Instructor at SFU’s Big Data Hub, where he teaches data science and machine learning courses. He is a registered Professional Engineering (P.Eng.) with EGBC and has been a software engineer for over 25 years. Stephen is a Senior Member of the IEEE. He currently sits on the IEEE DataPort Advisory Committee, serves as the Editor in Chief of the IEEE DataPort Metadata Review Board, and serves as an Editorial Board Member of Nature’s Scientific Data journal. Additionally, he is the Vice-Chair of the Big Data Governance and Metadata Management (BDGMM, P2957).

Publications (Peer-Reviewed) [Citation data from Google Scholar]

Power/Energy Engineering & Smart Grid

  1. Bundit Buddhahai, Stephen Makonin.
    A Nonintrusive Load Monitoring Based on Multi-Target Regression Approach.
    IEEE Access, vol. 9, pp. 163033-163042 (2021).
  2. Alon Harell, Richard Jones, Stephen Makonin, Ivan V. Bajic.
    TraceGAN: Synthesizing Appliance Power Signatures Using Generative Adversarial Networks.
    IEEE Transactions on Smart Grid, vol. 12, no. 5, pp. 4553-4563 (2021).
  3. Md. Zulfiquar Ali Bhotto, Richard Jones, Stephen Makonin, Ivan V. Bajic.
    Short-Term Demand Prediction Using an Ensemble of Linearly-Constrained Estimators.
    IEEE Transactions on Power Systems, vol. 36, no. 4, pp. 3163-3175 (2021).
  4. Christoph Klemenjak, Stephen Makonin, Wilfried Elmenreich.
    Investigating the performance gap between testing on real and denoised aggregates in non-intrusive load monitoring.
    Energy Informatics, vol. 4, 3. 5, pp. 1-15 (2021).
  5. Richard Jones, Christoph Klemenjak, Stephen Makonin, Ivan V. Bajic.
    Stop! Exploring Bayesian Surprise to Better Train NILM.
    Proceedings of the 5th International Workshop on Non- Intrusive Load Monitoring, 2020.
  6. Shikha Singh, Angshul Majumdar, Stephen Makonin.
    Compressive Non-Intrusive Load Monitoring.
    Proceedings of the 7th ACM International Conference on Systems for Energy-Efficient Built Environments (BuildSys), 2020.
  7. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Residential Power Forecasting Based on Affinity Aggregation Spectral Clustering.
    IEEE Access, vol. 8, pp. 99431-99444 (2020).
  8. Richard Jones, Alejandro Rodriguez-Silva, Stephen Makonin.
    Increasing the Accuracy and Speed of Universal Non-Intrusive Load Monitoring (UNILM) Using a Novel Real-Time Steady-State Block Filter.
    Proceedings of the 11th Conference on Innovative Smart Grid Technologies (ISGT), 2020.
  9. Christoph Klemenjak, Stephen Makonin, Wilfried Elmenreich.
    Towards Comparability in Non-Intrusive Load Monitoring: On Data and Performance Evaluation.
    Proceedings of the 11th Conference on Innovative Smart Grid Technologies (ISGT), 2020.
  10. Christoph Klemenjak, Anthony Faustine, Stephen Makonin, Wilfried Elmenreich.
    On metrics to assess the transferability of machine learning models in non-intrusive load monitoring.
    arXiv preprint arXiv:1912.06200, 2019.
  11. Megha Gaur, Stephen Makonin, Ivan V. Bajic, Angshul Majumdar.
    Performance evaluation of techniques for identifying abnormal energy consumption in buildings.
    IEEE Access, vol. 7, pp. 62721-62733 (2019).
  12. Alejandro Rodriguez-Silva, Stephen Makonin.
    Universal Non-Intrusive Load Monitoring (UNILM) Using Filter Pipelines, Probabilistic Knapsack, and Labelled Partition Maps.
    Proceedings of the 11th IEEE PES Asia-Pacific Power and Energy Engineering Conference 2019 (APPEEC), 2019.
  13. Alon Harell, Stephen Makonin, Ivan V. Bajic.
    WaveNILM: A Causal Neural Network for Power Disaggregation from the Complex Power Signal.
    Proceedings of the 44th International Conference on Acoustics, Speech, and Signal Processing (ICASSP), pp. 8335-8339, 2019.
  14. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Residential Power Forecasting Using Load Identification and Graph Spectral Clustering.
    IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 66, no. 11 , pp. 1900-1904 (2019).
  15. Alon Harell, Stephen Makonin, Ivan V. Bajic.
    A Recurrent Neural Network for Multisensory Non-Intrusive Load Monitoring on a Raspberry Pi.
    Proceedings of the IEEE 20th International Workshop on Multimedia Signal Processing (MMSP), 2018.
  16. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Incorporating Time-Of-Day Usage Patterns Into Non-Intrusive Load Monitoring.
    Proceedings of the 5th IEEE Global Conference on Signal and Information Processing (GlobalSIP), 2017.
  17. Chinthaka Dinesh, Stephen Makonin, Ivan V. Bajic.
    Understanding Appliance Power Consumption Without Sensors.
    In Poster Session at the 3rd Annual IC-IMPACTS Research Conference, 2017.
  18. Md. Zulfiquar Ali Bhotto, Stephen Makonin, Ivan V. Bajic.
    Load disaggregation based on aided linear integer programming.
    IEEE Transactions on Circuits and Systems II: Express Briefs, vol. 64, no. 7, pp. 792-796 (2016).
  19. Stephen Makonin.
    Investigating the Switch Continuity Principle Assumed in Non-Intrusive Load Monitoring (NILM).
    Proceedings of the 29th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2016.
  20. Stephen Makonin, Fred Popowich, Ivan V. Bajic, Bob Gill, Lyn Bartram.
    Exploiting HMM Sparsity to Perform Online Real-Time Nonintrusive Load Monitoring.
    IEEE Transactions on Smart Grid, vol. 7, no. 6, pp. 2575-2585 (2016).
  21. Bradley Ellert, Stephen Makonin, Fred Popowich.
    Appliance Water Disaggregation via Non-Intrusive Load Monitoring (NILM).
    Proceedings of the EAI International Conference on Big Data and Analytics for Smart Cities (BigDASC), 2015.
  22. Stephen Makonin, Fred Popowich.
    Nonintrusive Load Monitoring (NILM) Performance Evaluation.
    Energy Efficiency, vol. 8, no. 4, pp. 809–814 (2015).
  23. Stephen Makonin.
    Real-Time Embedded Low-Frequency Load Disaggregation.
    PhD Thesis, Simon Fraser University, School of Computing Science, 2014.
  24. Stephen Makonin, Ivan V. Bajic, Fred Popowich.
    Efficient Sparse Matrix Processing for Nonintrusive Load Monitoring (NILM).
    Proceedings of the 2nd International Workshop on Non-Intrusive Load Monitoring, 2014.
  25. Stephen Makonin, Laura Guzman Flores, Robyn Gill, Roger Alex Clapp, Lyn Bartram, Bob Gill.
    A Consumer Bill of Rights for Energy Conservation.
    Proceedings of the IEEE Canada International Humanitarian Technology Conference (IHTC), 2014.
  26. Stephen Makonin
    Nonintrusive Load Monitoring (NILM): What an algorithm can tell you about your energy consumption.
    In Poster Session at SFU Postdoctoral Research Day, 2016.
    In Poster Session at IEEE Vancouver Section Annual General Meeting, 2014.
  27. Stephen Makonin, William Sung, Ryan Dela Cruz, Brett Yarrow, Bob Gill, Fred Popowich, Ivan V. Bajic.
    Inspiring Energy Conservation Through Open Source Metering Hardware and Embedded Real-Time Load Disaggregation.
    Proceedings of the 5th IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC), 2013.
  28. Stephen Makonin, Fred Popowich, Bob Gill.
    The Cognitive Power Meter: Looking Beyond the Smart Meter.
    Proceedings of the 26th Annual IEEE Canadian Conference on Electrical and Computer Engineering (CCECE), 2013.
  29. Stephen Makonin.
    Approaches to Non-Intrusive Load Monitoring (NILM) in the Home.
    PhD depth report, Simon Fraser University, School of Computing Science, 2012.

Data Engineering, Public Datasets & Big Data

  1. Mostafa Farrokhabadi, Jethro Browell, Yi Wang, Stephen Makonin, Wencong Su, Hamidreza Zareipour.
    Day-Ahead Electricity Demand Forecasting Competition: Post-COVID Paradigm.
    IEEE Open Access Journal of Power and Energy, Early Access (2022),
  2. Christoph Klemenjak, Andreas Reinhardt, Lucas Pereira, Stephen Makonin, Mario Bergés, Wilfried Elmenreich.
    Electricity Consumption Data Sets: Pitfalls and Opportunities.
    Proceedings of the 6th ACM International Conference on Systems for Energy-Efficient Built Environments, Cities, and Transportation (BuildSys), 2019.
  3. Stephen Makonin.
    HUE: The Hourly Usage of Energy Dataset for Buildings in British Columbia.
    Data in Brief, vol. 23, no. 103744, pp. 1-4 (2019).
  4. Stephen Makonin, Z. Jane Wang, Chris Tumpach.
    RAE: The Rainforest Automation Energy Dataset for Smart Grid Meter Data Analysis.
    Data, vol. 3, no. 1, article 7, pp. 1-9 (2018)
  5. Stephen Makonin, Bradley Ellert, Ivan V. Bajic, Fred Popowich.
    Electricity, water, and natural gas consumption of a residential house in Canada from 2012 to 2014.
    Scientific Data, vol. 3, no. 160037, pp. 1-12 (2016).
  6. Stephen Makonin, Fred Popowich, Lyn Bartram, Bob Gill, Ivan V. Bajic.
    AMPds: A Public Dataset for Load Disaggregation and Eco-Feedback Research.
    Proceedings of the 2013 IEEE Electrical Power and Energy Conference (EPEC), 2013.
  7. Stephen Makonin.
    ODDs: Occupancy Detection Dataset.
    Harvard Dataverse, V1, 2010.

Software Engineering, incl. Electrical & Computer Engineering (ECE)

  1. Stephen Makonin.
    Start-Up Creation: The Smart Eco-Efficient Built Environment.
    Editors: Fernando Pacheco-Torgal, Erik Rasmussen, Claes-Goran Granqvist, Volodymyr Ivanov, Arturas Kaklauskas, Stephen Makonin.
    1st Ed. Woodhead Publishing, ISBN: 978-0-08-100546-0 (hardcover), 978-0-08-100549-1 (ebook), 2016.
    2st Ed. Woodhead Publishing, ISBN: 978-0-12-819946-6 (paperback), 978-0-12-819947-3 (ebook), 2020.
  2. Laura Guzman, Stephen Makonin, Roger Alex Clapp.
    CarbonKit: Designing A Personal Carbon Tracking Platform.
    Proceedings of SocialSense ’19: Fourth International Workshop on Social Sensing, pp. 24-29, 2019.
  3. Joanna Wallace, Kyle Richardson, Bob Gill, Stephen Makonin.
    Cognitive Radio Technology: System Evolution.
    Proceedings of the 4th International Conference On Wireless Networks and Embedded Systems (WECON), 2015.
  4. Reza Filsoof, Alison Bodine, Bob Gill, Stephen Makonin, Robert Nicholson.
    Transmitting Patient Vitals Over a Reliable ZigBee Mesh Network.
    Proceedings of the IEEE Canada International Humanitarian Technology Conference (IHTC), 2014.
  5. David Bennett, Stephen Makonin, Vincent W. Mayfield, Ted Neustaedter, Mark R. Wrenn.
    Visual C++ 5.0 Developer's Guide.
    Sams Publishing, ISBN: 978-0-672-31031-7, 1996.

Visualization & Human-Computer Interaction (HCI)

  1. Stephen Makonin, Daniel McVeigh, Wolfgang Stuerzlinger, Khoa Tran, Fred Popowich.
    Mixed-Initiative for Big Data: The Intersection of Human + Visual Analytics + Prediction.
    Proceedings of the 49th Hawaii International Conference on System Sciences (HICSS), pp. 1427-1436, 2016.
  2. Stephen Makonin, Lyn Bartram, Fred Popowich.
    A Smarter Smart Home: Case Studies of Ambient Intelligence.
    IEEE Pervasive Computing, vol. 12, no. 1, pp. 58–66 (2013).
  3. Stephen Makonin, Fred Popowich, TaeJin Moon, Bob Gill.
    Inspiring Energy Conservation Through Open Source Power Monitoring and In-Home Display.
    Proceedings of the IEEE Power and Energy Society General Meeting, 2013.
  4. Stephen Makonin, Fred Popowich.
    Home Occupancy Agent: Occupancy and Sleep Detection.
    GSTF Journal on Computing, vol. 2, no. 1, pp. 182–186 (2012).
  5. Stephen Makonin, Maryam H. Kashani, Lyn Bartram.
    The Affect of Lifestyle Factors on Eco-Visualization Design.
    Proceedings of Computer Graphics International (CGI), 2012.
  6. Stephen Makonin, Philippe Pasquier, Lyn Bartram.
    Elements of Consumption: An abstract visualization of household consumption.
    Proceedings of the 11th International Symposium on Smart Graphics, LNSC 6815:194–198, 2011.
  7. Stephen Makonin, Fred Popowich.
    An intelligent agent for determining home occupancy using power monitors and light sensors.
    Proceedings of the 9th International Conference on Smart Homes and Health Telematics (ICOST), LNSC 6719:236–240, 2011.

Academic Exploits

Current Supervision

Past Supervision

Visiting Scholars

Research Grants [PI = Principal Investigator]

Course Instruction

Awards & Achievements

2017.09
IEEE Signal Processing Society Appreciation Certificate — Dedicated Leadership & Support
2015.04
IEEE Vancouver Section Leadership and Contribution Award — Initiative

Service To Profession

Advisory Boards/Committees

Journal Editorship

Standards Associations

General Chair/Co-Chair & Organizer

Website & Social Media Chair

Local Arrangements Chair

Technical Program Committee