Teknologiseminar
From Robin
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Revision as of 15:15, 4 February 2023
Meeting structure
Place: ROBIN pause area, 4th floor Ole-Johan Dahls hus / gather town
12:00-12:15 Brief exchange of recent news, plans, updates, etc.
~12:20-12:35 Presentation on: Technology / Own Research / Journal review (see guidelines), time excludes discussion
Whatever content you present, remember that some of those attending have no advance knowledge about your project or work so introduce it in the beginning and stay focused on the main issues/challenges etc. Thus, make your presentation simple and understandable for as many as possible.
Dates and subjects - Spring2022 – Thursdays 12:00-12:45
5-20 min housekeeping/updates + 20 min talk
| When | What | Who |
| 12.01 | Runtime Analysis of Evolutionary Algorithms | Per Kristian Lehre (external, from University of Birmingham) |
| 19.01 | Projects at Institute for Energy Technology (IFE) / Humans and Automation Department | Alexandra Fernandes (external) |
| 26.01 | Real-World Applications of Multi-Objective Evolutionary Computation (Trial Lecture) | Frank Veenstra |
| 02.02 | No presentation since relevant for many to attend Julian's defence at RITMO | |
| 09.02 | Bayesian Neural Networks for continual deep learning | Mateusz Wasiluk |
| 16.02 | Comparing optimization algorithms and improving their efficiency | Etor Arza |
| 23.02 | Winter holiday - Casual meeting today | |
| 02.03 | Kai Olav Ellefsen | |
| 09.03 | ||
| 16.03 | ||
| 23.03 | ||
| 30.03 | The SmartAUVs project | Ivar-Kristian Waarum |
| 06.04 | Easter Break – No meeting | |
| 13.04 | ||
| 20.04 | NeuroAI: Combining neuroscience and machine learning to develop next-generation AI | Mikkel Lepperød |
| 27.04 | ||
| 04.05 | Sharing the experience from the stay in Japan | Diana Saplacan |
| 11.05 | Introduction to biosignal processing to derive metrics describing the sympathetic nervous system | Ulysse Côté-Allard |
| 18.05 | Ascension day - No meeting | |
| 25.05 | ||
| 01.06 | ||
| 08.06 | ||
| 15.06 |
Examples of interesting topics for technology introduction
Feel free to add topics to the wishlist!
- Robotics
- Reinforcement learning for robotics
- SLAM
- embodied cognition
- Swarm
- Neural networks
- Recursive NNs and LSTMs
- NEAT / HyperNEAT
- Deep NNs
- Evolutionary algorithms and other types of optimization
- Performance comparison of EAs (statistical tests)
- Differential evolution
- Diversity preservation methods
- Novelty search, MAP-Elites and variants
- Bayesian optimization
- Tools
- SLURM
- R
- Python as alternative to R, incl. matplotlib
- ROS
- Deep learning frameworks and practice
- Unity ML agents
