Check out our latest AI/ML-systems and quantum computing results for FCAI AI day.

ESE group will present the recent research results in FCAI day on November 16, 2022. See the following contributions that will be there:

Talks:

  • Lalli Myllyaho, Jukka K. Nurminen and Tommi Mikkonen: Node co-activations as a means of error detection—Towards fault-tolerant neural networks
  • Kai-Kristian Kemell and Ville Vakkuri: ECCOLA – A method for implementing ethically aligned AI systems

Posters:

  • Ilmo Salmenperä and Jukka K. Nurminen: Hyperparameter Optimization of Quantum Annealing Boosted Restricted Boltzmann Machines
  • Juha Mylläri: Augmenting the Student-Teacher Feature Pyramid Matching Method for Better Unsupervised Anomaly Localization
  • Juhani Kivimäki: Uncertainty Estimation with Calibrated Confidence Scores
  • Jussi Steenari, Lucy Ellen Lwakatare, Jukka K. Nurminen, Jaakko Talonen and Teemu Manderbacka: Mining port operation information from AIS data
  • Yumo Luo, Mikko Raatikainen, Lalli Myllyaho and Jukka K. Nurminen: From Misbehaviour and Fault Tolerance in ML system towards dependable and self-improving MLOps (edited) 

 

The final seminar of the AIGA (AI governance) project 13.10.2022 Online&Turku

Artificial Intelligence Governance and Auditing (AIGA) project, which ESE is a participant, will have its Final Seminar. We will present the key results of the project. We will also host more general discussions about the latest developments around responsible AI. Both researchers and industry representatives will share their views in the open seminar, and the program ends with an informal networking event.

The final seminar will take place on 13.10.2022 at the Turku School of Economics. A live stream is provided for remote participation. Please make sure to register before 5.10. (16:00).

For further information, please visit our event website: https://ai-governance.eu/final-seminar/

Register as a participant: https://konsta.utu.fi/Default.aspx?tabid=88&tap=13197

MLOps research and thesis positions

Machine learning (ML) is becoming an increasingly common technology that is used in software-based systems. While software and software engineering practices are still a quintessential part of the design of such systems, the design space has data and ML and respective data scientist stakeholders as new concerns. Hence, MLOps — as a derivative of DevOps — is currently emerging to better integrate data and ML into the software engineering way of working, as well as integrate ML better in the software-based systems. MLOps is about both practices and tools for ML-based systems that technically enable iterative software engineering practice.

The ESE research group is strengthening its research focus in the area of MLOps. In particular, we are participating in projects that study MLOps, such as AIGA https://ai-governance.eu/ and recently started IMLE4 https://itea4.org/project/iml4e.html.

We have funded thesis positions in the area of MLOps in these research projects that can be tailored to the interest of the applicant. For details, contact Mikko Raatikainen (first.last@helsinki.fi).