Work
I'm a research scientist in the Trustworthy Green IoT Software research group in the Department of Sustainable Communication Technologies at SINTEF Digital .
For professional inquiries, I can be contacted on erik.johannes.husom@sintef.no .
My research interests lie within responsible and ethical use of Artificial Intelligence (AI), including trustworthy AI, explainable AI and green AI.
I also do research in AI engineering and applied machine learning.
Projects
Media
Klimakostnaden for bruk av Chat GPT kan bli større enn nytteverdien . Erik Johannes Husom, Finn Lützow-Holm Myrstad (fagdirektør i Forbrukerrådet), Gencer Erdogan (fungerende forskningsleder i Sintef Digital) og Elin Volder Rutle (leder for bærekraft i Forbrukerrådet). digi.no, 28. okt, 2024
ChatGPT krever moderering á la Wikipedia . Rustem Dautov, Erik Johannes Husom. Teknisk Ukeblad, 16. mai, 2023
Menneskapt eller ikke – spiller det noen rolle? Erik Johannes Husom. Vårt Land, 18. februar, 2023
Er vi klare for metaverset? Erik Johannes Husom, Ketil Stølen. Klassekampen, 31. oktober, 2022
Talks and presentations
KI og bærekraft i et klimaperspektiv , innlegg hos NIBIO, 2. desember 2024.
Hvordan få til bærekraftig bruk av KI? , foredrag på halvdagskonferasen "Bærekraftig bruk av AI" av Den norske dataforening, 14. nov 2024.
KI og ressursforbruk fra et forbrukerperspektiv , innlegg hos Forbrukerrådet, 03. september 2024.
Grønn KI , på arrangementet KI som klimaversting eller reddende engel? under Arendalsuka, 12. august 2024.
Kunstig intelligens – bare et gode? Etiske utfordringer i møte med ny teknologi , 30. mai 2024.
Engineering Carbon Emissions Aware Machine Learning Pipelines , presentation of conference paper, CAIN 2024, April 15th, 2024
Measuring and understanding energy use in Large Language Model inference , 21. mars 2024.
Kunstig intelligens og etikk , 6. mars 2024.
Kunstig intelligens – pålitelighet og bærekraft , 30. januar 2024.
Maskinlæringens klimaavtrykk: Hvordan måles det og hva kan vi bruke målingene til? , foredrag på seminaret "Bærekraft og maskinlæring – Lar det seg forene?" , 21. september 2023
AutoConf: Automated Configuration of Unsupervised Learning Systems using Metamorphic Testing and Bayesian Optimization , presentation of conference paper, ASE 2023, September 14th, 2023
The future of software engineering in the light of LLMs , May 2023
Replay-Driven Continual Learning for the Industrial Internet of Things , presentation of conference article, CAIN 2023, 15th May, 2023
Machine Learning for Fatigue Detection using Fitbit Fitness Trackers , presentation of conference article, icSports 2023, 27th October, 2022
UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing , presentation of conference article, CAIN 2022, 17th May, 2022
Scientific publications
19. Raft Protocol for Fault Tolerance and Self-Recovery in Federated Learning .
Rustem Dautov, Erik Johannes Husom .
19th International Conference on Software Engineering for Adaptive and Self-Managing Systems (SEAMS). 2024-04-16.
18. Engineering Carbon Emissions Aware Machine Learning Pipelines .
Erik Johannes Husom , Sagar Sen, Arda Goknil.
2024 IEEE/ACM 3rd International Conference on AI Engineering–Software Engineering for AI (CAIN). 2024-04-15.
Link to presentation slides .
17. Automated Behavior Labeling for IIoT Data .
Erik Johannes Husom , Arda Goknil, Simeon Tverdal, Sagar Sen, Phu Nguyen.
The 13th International Conference on the Internet of Things (IoT 2023). 2023-11-07.
16. REPTILE: a Tool for Replay-driven Continual Learning in IIoT .
Erik Johannes Husom , Sagar Sen, Arda Goknil, Simeon Tverdal, Phu Nguyen.
The 13th International Conference on the Internet of Things (IoT 2023). 2023-11-07.
15. Towards Community-Driven Generative AI .
Rustem Dautov, Erik Johannes Husom , Sagar Sen, Hui Song.
Position Papers of the 18th Conference on Computer Science and Intelligence Systems (fedCSIS 2023). 2023-09-17.
14. AutoConf: Automated Configuration of Unsupervised Learning Systems Using Metamorphic Testing and Bayesian Optimization .
Lwin Khin Shar, Arda Goknil, Erik Johannes Husom , Sagar Sen, Yan Naing Tun, Kisub Kim
2023 38th IEEE/ACM International Conference on Automated Software Engineering (ASE 2023). 2023-09-14.
13. Uncertainty-aware Virtual Sensors for Cyber-Physical Systems .
Sagar Sen, Erik Johannes Husom , Arda Goknil, Simeon Tverdal, Phu Nguyen.
IEEE Software. 2023-08-21. Journal paper.
12. Replay-driven continual learning for the industrial internet of things .
Sagar Sen, Simon Myklebust Nielsen, Erik Johannes Husom , Arda Goknil, Simeon Tverdal, Leonardo Sastoque Pinilla.
2023 IEEE/ACM 2nd International Conference on AI Engineering--Software Engineering for AI (CAIN). 2023-05-15.
Link to presentation slides .
11. Virtual sensors for erroneous data repair in manufacturing a machine learning pipeline .
Sagar Sen, Erik Johannes Husom , Arda Goknil, Dimitra Politaki, Simeon Tverdal, Phu Nguyen, Nicolas Jourdan.
Computers in Industry, Volume 149, August 2023, 103917. 2023-08-01. Journal paper.
10. A blockchain-based framework for trusted quality data sharing towards zero-defect manufacturing .
Mauro Isaja, Phu Nguyen, Arda Goknil, Sagar Sen, Erik Johannes Husom , Simeon Tverdal, Abhilash Anand, Yunman Jiang, Karl John Pedersen, Per Myrseth, Jørgen Stang, Harris Niavis, Simon Pfeifhofer, Patrick Lamplmair.
Computers in Industry, Volume 146, April 2023, 103853. 2023-04-01. Journal paper.
9. Bridging the Gap Between Java and Python in Mobile Software Development to Enable MLOps .
Rustem Dautov, Erik Johannes Husom , Fotis Gonidis, Spyridon Papatzelos, Nikolaos Malamas.
2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob). 2022-11-15.
8. Machine Learning for Fatigue Detection using Fitbit Fitness Trackers .
Erik Johannes Husom , Rustem Dautov, Adela-Aniela Nedisan, Fotis Gonidis, Spyridon Papatzelos, Nikolaos Malamas.
icSports 2022. 2022-10-28.
Link to presentation slides .
7. Taming Data Quality in AI-Enabled Industrial Internet of Things .
Sagar Sen, Erik Johannes Husom , Arda Goknil, Simeon Tverdal, Phu Nguyen, Iker Mancisidor.
IEEE Software. 2022-08-01. Journal paper.
6. Towards MLOps in Mobile Development with a Plug-in Architecture for Data Analytics .
Rustem Dautov, Erik Johannes Husom , Fotis Gonidis.
2022 6th International Conference on Computer, Software and Modeling (ICCSM). 2022-07-01.
5. UDAVA: An Unsupervised Learning Pipeline for Sensor Data Validation in Manufacturing .
Erik Johannes Husom , Simeon Tverdal, Arda Goknil, Sagar Sen.
2022 IEEE/ACM 1st International Conference on AI Engineering--Software Engineering for AI (CAIN). 2022-05-16.
Link to presentation
slides .
4. Deep learning to predict power output from respiratory inductive plethysmography data .
Erik Johannes Husom , Pierre Bernabé, Sagar Sen.
Applied AI Letters. 2022-04. Journal paper.
3. On The Reliability Of Machine Learning Applications In Manufacturing Environments .
Nicolas Jourdan, Sagar Sen, Erik Johannes Husom , Enrique Garcia-Ceja, Tobias Biegel, Joachim Metternich.
Workshop on Distribution Shifts, 35th Conference on Neural Information Processing Systems (NeurIPS 2021). 2021-12-19.
2. Deep learning to estimate power output from breathing .
Erik Johannes Husom .
2021-06. MSc Thesis.
1. DeepVentilation: Learning to Predict Physical Effort from Breathing .
Sagar Sen, Pierre Bernabé, Erik Johannes B. L. G. Husom .
Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence. 2020-07.
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©2018-2024 Erik Johannes Husom.