Science · Technology · Engineering

Debangsha Sarkar

Also published as Debangsha Kusum Sarkar

Burnaby, Metro Vancouver, British Columbia

Overview

Debangsha Sarkar is a computer scientist and machine learning practitioner based in Burnaby, in Metro Vancouver. He holds two master’s degrees from the University of British Columbia: an M.Sc. in Computer Science and a Master of Data Science. His published research concerns representative sampling and active learning. Since April 2024 he has been Chief Technology Officer of EclimAi Ltd in Dublin.

Education

  • M.Sc. Computer Science, University of British Columbia

    Thesis: Improved sampling strategy for representative set construction (2022). https://doi.org/10.14288/1.0406204

  • Master of Data Science, University of British Columbia

    The second of two master’s degrees from UBC, alongside the M.Sc. in Computer Science.

Research and publications

Graduate research at UBC focused on sampling strategies for representative set construction and active learning. The following peer-reviewed works list Sarkar as an author.

  1. Sarkar, D., Ramezankhani, M., Narayan, A., & Milani, A. S. (2023). Non data hungry smart composite manufacturing using active transfer learning with sigma point sampling (SPSATL). Computers in Industry, 151, 103989.

    https://doi.org/10.1016/j.compind.2023.103989

  2. Sarkar, D., Shabani, A., & Narayan, A. (2022). Novel Representative Sampling for Improved Active Learning. IFAC-PapersOnLine, 55(20), 55–60. MATHMOD 2022.

    https://doi.org/10.1016/j.ifacol.2022.09.071

Current role

Chief Technology Officer, EclimAi Ltd (Dublin), April 2024–present. The role covers edge computer vision and machine learning for commercial building energy efficiency.

Prior work

Earlier roles listed on the portfolio experience section include freelance machine learning engineering; machine learning engineering at Versatile Media Ltd in Vancouver (NeRF, photogrammetry, and virtual production); AI research development at Tveon in British Columbia; and graduate research assistant and teaching assistant appointments at UBC (2019–2022) connected to the sampling and active-learning work above.