This was the final day of the NIPS conference and the day of the workshop on Machine Learning for Sustainability; the workshop I submitted my paper to. It's a bit of a shame it came on the day when I think everyone was the most tired, but I think that's just a reality of post conference workshops. In general, the workshop mostly covered three main topics: climate modelling, energy and environmental management.
For me, the best part of this workshop was the chance to meet other researchers working on the problem of energy disaggregation. The workshop was organised by Zico Kolter, with an invited talk given by Mario Bergés, both of whom have published in this area and their papers have ended up on my reading list.
The morning invited talks were:
- Mario Bergés - Machine Learning Challenges in Building Energy Management: Energy Disaggregation as an Example
- Andreas Krause - Dynamic Resource Allocation in Conservation Planning
Before the midday break were the spotlights and poster session. These sessions were my first chance to present my work to the an external academic community and receive feedback, which was an absolutely invaluable opportunity. I tried my best to balance my time between presenting my poster to others and also to discuss the other posters with their authors. I was really impressed with the quality of the accepted papers, and hope this is indicative of the future of the MLSUST workshop.
The afternoon invited talks were:
- Drew Purves - Enabling Intelligent Management of the Biosphere
- Claire Monteleoni - Climate Informatics
- Kevin Swersky - Machine Learning for Hydrology, Water Monitoring and Environmental Sustainability
- Alex Rogers - Putting the “Smarts” into the Smart Grid: A Grand Challenge for Artificial Intelligence
For me, the workshop was a brilliant venue to receive feedback on my PhD work, and for that I owe the organisers thanks.