Publications

  • Jürgen Großmann, Jukka K. Nurminen: Industrial Machine Learning for Enterprises (IML4E), Project Report at ICTSS 2021, London 2021 (paper, slides)
  • Dennis Muiruri: Practices and Infrastructures for ML Systems: An Interview Study, , 02/2022
  • Mohamed Abdelaal: Do We Really Need Data Cleaning for ML? A Comprehensive Benchmark, microTEC Südwest Clusterkonferenz, 05/2022
  • Stirbu, V., Raatikainen, M., Röntynen, J., Sokolov, V., Lehtonen, T., & Mikkonen, T. (2022). Towards multi-concern software development with Everything-as-Code. IEEE Software, 39(4), 27-33. https://doi.org/10.1109/ms.2022.3167481
  • D. Muiruri, L. E. Lwakatare, J. K. Nurminen, und T. Mikkonen, „Practices and Infrastructures for Machine Learning Systems: An Interview Study in Finnish Organizations“, Computer, Bd. 55, Nr. 6, S. 18–29, Juni 2022, doi: 10.1109/MC.2022.3161161
  • Jukka K. Nurminen: Lecture on Testing and Maintaining an AI system - from handcraft to industrial operation in "Diploma in AI" professional training by HY Plus and APro event, Lecture, 05/2022
  • L. Myllyaho, J. K. Nurminen, und T. Mikkonen, „Node co-activations as a means of error detection -Towards fault-tolerant neural networks“, Array, Bd. 15, S. 100201, Sep. 2022, doi: 10.1016/j.array.2022.100201
  • Mikko Raatikainen: University of Helsinki seminar in Novel Software Architecture Design: Beyond DevOps including but limited to MLOps, AIOps, DataOps, RegOps, DevSecOps, Lectures, 05/2022
  • D. Stjelja, J. Jokisalo, und R. Kosonen, „Scalable Room Occupancy Prediction with Deep Transfer Learning Using Indoor Climate Sensor“, Energies, Bd. 15, Nr. 6, S. 2078, März 2022, doi: 10.3390/en15062078
  • Johan Himberg: MLOps: Making Machine Learning Production Work (https://www.reaktor.com/blog/mlops-making-machine-learning-production-work/), White paper, 9/2022
  • Mikko Raatikainen: From Misbehaviour and Fault Tolerance in ML system towards dependable and self-improving MLOps, FCAI (Finnish Center for Artificial Intelligence) AI Day, poster session, Poster in FCAI day https://fcai.fi/ai-day-2022, 11/2022
  • Juhani Kivimäki: Uncertainty Estimation with Calibrated Confidence Scores, Poster in FCAI day, 11/2022
  • Lalli Myllyaho, Lalli Myllyaho, Jukka K. Nurminen and Tommi Mikkonen: Node co-activations as a means of error detection- towards fault-tolerant neural networks, Presentation in FCAI day, 11/2022
  • Kai-Kristian Kemell, Kai-Kristian Kemell and Ville Vakkuri: ECCOLA - A method for implementing ethically aligned AI systems, Presentation in FCAI day, 11/2022
  • Dorian Knoblauch, Jürgen Grossmann: Towards Continuous Audit-based Certification for MLOps, Presentation and lecture notes at WAICOM2022 (https://research.nii.ac.jp/~ksatoh/WAICOM2022/), Conference paper and presentation, 11/2022
  • Jouni Seppänen, Janne Sinkkonen: So you changed your website. How do you now measure success and avoid common A/B mistakes?, white paper, 12/2022
  • Mohamed Abdelaal: XAIR: A Systematic Metareview of Explainable AI (XAI) Aligned to the Software Development Process, Journal paper, 01/2023
  • Panu Korhonen: AI is a solution in search of a problem, White paper, 01/2023
  • Mohamed Abdelaal, Organization of a technical event at TU Darmstadt, jointly with the KompAKI project. The event comprises four talks covering MLOps tools and use cases, hyribd AI, and explainability, Darmstadt Meetup on ML automation and MLOps, 02/2023
  • Mohamed Abdelaal "REIN: A Comprehensive Benchmark
  • Framework for Data Cleaning Methods in ML Pipelines", Conference Paper, 01/2023
  • Mikko Raatikainen: Model card validation demo video. https://www.youtube.com/watch?v=5IZ6Tp3VtS8, Youtube video, 02/2023
  • Mohamed Abdelaal: RTClean: Context-aware Tabular Data Cleaning using Real-time OFDs, Conference paper, 03/2023
  • Jorma Valjakka (UH): Anomaly Localization in Audio via Feature Pyramid Matching, Conference Paper, 05/2023
  • Juha Mylläri (UH): Discrepancy Scaling for Fast Unsupervised Anomaly Localization, Conference Paper, 05/2023
  • Juhani Kivimäki (UH): Failure Prediction in 2D Document Information Extraction with Calibrated Confidence Scores, Conference Paper, 05/2023
  • Mikko Raatikainen: Systematic Mapping Study on Use of Pre-Trained Open Machine Learning Models, Conference Paper, 05/2023
  • Mikko Raatikainen: Systematic Literature Review on Cost-efficient Deep Learning, Journal paper, 05/2023
  • Mohamed Abdelaal: DiffML: End-to-end Differentiable ML Pipelines, Conference Paper, 06/2023
  • Yumo Luo: Autonomously Adaptive Machine Learning Systems: Experimentation-Driven Open-Source Pipeline, Conference Paper, 06/2023
  • Mohamed Abdelaal, AutoCure: Automated Tabular Data Curation Technique for ML Pipelines, Conference Paper, 06/2023
  • Balázs Tibor Morvay: Diffusion probabilistic model-based face anonymization in embedded environments, Conference paper, 06/2023
  • Dorian Knoblauch, Jürgen Großmann: Fraunhofer Fokus, Towards a Risk-Based Continuous Auditing-Based Certification for Machine Learning, Journal paper, 08/2023
  • Dorian Knoblauch, Jürgen Großmann: Fraunhofer Fokus, Continuous Auditing Based Conformity Assessment, Conference paper and presentation, 11/2023
  • Abhishek Shrestha, Dorian Knoblauch: Pipeline Probe: A Tool for Automated Quality Assessment in MLOps, Conference paper and presentation, 11/2023


Workshops

  • Heikki Ihasalo: Granlund internal workshop on sharing the knowledge of the state-of-the-art review in IML4E and planning of MLOps roadmap for Granlund. Workshop will be held at the end of February 2022, MLOps roadmap (workshop), 02/2022
  • Gabor Gulyas: Workshop for ~20 healthcare professionals (28th August), where we had a presentation of the minimal version of the device that we will develop within the project., Concept demo for healthcare professionals, 08/2021
  • Luca Szegletes: A workshop for industrial partners on sharing the knowledge in IML4E (the end-to-end machine learning pipeline, the best practices and tools)., Machine learning in practice: Workshop for industrial partners, 02/2022
  • Gabor Gulyas: Workshop for ~80 health visitors (15th October) in Debrecen, where we had a presentation and Q&Asession. This session covered both presenting the IML4E project and the Hungarian case study to the audience., Project & case study presentation, 10/2022
  • Jesse Pitkänen: Stable Diffusion deployment, internal workshop training, 11/2022
  • Jürgen Großmann, An introductory talk to the world of MLOps, Budapest MLOps Meetup, 11/2022
  • Dennis Muiruri: Practices and Infrastructures for MLOps, Budapest MLOps Meetup, 11/2022
  • Gabor Gulyas: We have organized a workshop for ~20 healthcare professionals (28th August), where we had a presentation of the IML4E project, focusing mainly on the work of Hungarian national consortium., Project presentation, 08/2021
  • Luca Szegletes: Presentation at Automation and Applied Computer Science Workshop, Conference paper, 06/2022
  • Mikko Raatikainen: Presentation on AI application development and DataOps vs. DevOps in ITEA Smart Systems Engineering workshop., Presentation and panelist, 04/2022
  • Souris Harry / Joaquin Rives Gambin: Presenting MLOps platform in the context of IML4E and discussing future steps, internal workshop, 01/2023
  • Souris Harry / Joaquin Rives Gambin: Introducing MLOps platform in the context of IML4E, focus on usability and scalability, internal workshop, 01/2023