Resource Aware Machine Learning workshop

The enRichMyData was represented at the Resource Aware Machine Learning workshop at the Danish Digitalization, Data Science and AI 2.0 (D3A) Conference, Nyborg, Denmark, on the 1st and 2nd of February 2024.

This workshop aimed at reasoning critically about how we build software and hardware for end-to-end Machine Learning (ML). The fruitful discussions led to increased awareness for understanding the utilization of modern hardware and kickstarting future developments to minimize hardware underutilization. Interest and contribution are raised from academics (especially PhD students) and industry across fields of data management, machine learning, systems, and computer architecture, covering expertise of algorithmic optimizations in machine learning, job scheduling and resource management in distributed computing, parallel computing, and data management and processing.

The speakers of the workshop were as follows:

  • Ingrid Munne, Data Scientist and ML Engineer at Electricity Maps;
  • Robin Troesch, Data Engineer at Electricity Maps;
  • Pedram Bakhtiarifard, Research Assistant at the University of Copenhagen and maintainer of the Carbontracker framework;
  • Ehsan Yousefzadeh-Asl-Miandoab, PhD student at IT University of Copenhagen;
  • Mahyar Tourchi Moghaddam, Assistant Professor at the University of Southern Denmark;
  • Julie Koefoed Bielefeldt, Business Developer for Datahubben at Energinet.
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