Green AI Seminar
Content
This seminar explores the potential of AI in combating global climate change by discussing its role in monitoring climate crises, conserving nature, and reducing greenhouse gas emissions in various sectors. The seminar will also consider the sustainability of AI itself, as advances in machine learning come with a significant increase in carbon emissions. Participants will learn about essential aspects of improving the sustainability of machine learning algorithms and gain a different perspective on machine learning’s role in addressing climate change.
The seminar provides:
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- Introduction to “Green AI” versus “Red AI”
- Guests talks on related research topics
- Group discussions on future prospects of AI, specifically machine learning
- Best practices for literature review and scientific presentations
- Literature review on Green AI in certain areas in groups
- Scientific talk of each student on one specific topic
Contact: Dr.-Ing. Eva Dorschky
Time and place: The seminar will not be offered in the upcoming winter semester 24/25.
Guest Talks Winter Semester 23/24
Solar energy forecasting from cloud cover observations
This talk will present recent advances in solar forecasting with computer vision, with a focus on how machine learning can be used to anticipate the future solar power variability from cloud cover observations. Accurately predicting future changes in solar energy production is key to facilitate the large-scale integration of this low-carbon energy source into power systems.
Guest speaker: Quentin Paletta (European Space Agency)
Date: 22.11.2023
Zoom only: Zoom link, Meeting ID: 698 5376 3200, Passcode: 131943
Forest fire detection using drones
This talk will present research on the use of convolutional neural networks (CNN) to automatically search for forest- and wildfires in drone-based applications. It will be shown how the combination of AI with autonomous long distance drones can make life safer and easier for fire brigades and dampen the effects of wildfires on climate change.
Guest Speakers: Isabella Hufnagl and Simon Gehringer (Evolonic)
Date: 13.12.2023
Neuromorphic Computing: The state and potential of Spiking Neural Networks
This talk will present an introduction to biology-inspired Spiking Neural Networks (SNNs), their current state, and their potential as an energy-efficient alternative to conventional artificial neural networks (ANNs). In addition, the necessity, benefit, and challenges of developing neuromorphic hardware suitable for SNNs will be discussed.
Guest speaker: Ferdinand Pscheidl (Fraunhofer EMFT)
Date: 07.02.2024
Zoom only: Zoom link, Meeting ID: 683 7186 9072, Passcode: 568984
Schedule Winter Semester 23/24
Seminar | Dates |
Introduction and group work | 18.10.2023 |
Literature review and scientific writing | 25.10.2023 |
Scientific presentations | 08.11.2023 |
Sustainability of AI | 15.11.2023 |
Invited talk by Quentin Paletta on solar energy forecasting | 22.11.2023 |
Q & A | 29.11.2023 |
Interim report of groups | 06.12.2023 |
Invited talk by Evolonic on forest fire detection using drones | 13.12.2023 |
Student talks | 20.12.2023 |
Student talks | 10.01.2024 |
Student talks | 17.01.2024 |
Student talks | 24.01.2024 |
Student talks | 31.01.2024 |
Invited talk by Ferdinand Pscheidl on spiking neural networks | 07.02.2024 |