Projects per year
Personal profile
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 7 Affordable and Clean Energy -
SDG 9 Industry, Innovation, and Infrastructure -
SDG 17 Partnerships for the Goals
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Dive into the research topics where Mikko Seppi is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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RheoMaTe: Rheology for Sustainable Manufacturing Technologies
Laukkanen, O.-V. (Manager), Kouko, J. (Owner), Koponen, A. (Participant), Jäsberg, A. (Participant), Turpeinen, T. (Participant), Prakash, B. (Participant), Järvinen, M. (Participant), Viitala, J. (Participant), Kiiskinen, T. (Participant), Kade, J. (Participant), Agustin, M. (Participant), Seppi, M. (Participant), Kallio, S. (Participant), Gorshkova, E. (Participant), Korhonen, M. (Participant), Ojaniemi, U. (Participant), Syrjänen, J. (Participant), Reiman, T. (Participant), Lappalainen, T. (Participant), Virkajärvi, J. (Participant) & Kontkanen, O. (Participant)
1/03/25 → 28/02/27
Project: Business Finland project
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AIMODE: Development of Artificial Intelligence and Machine Learning for Online Perception and Operating Mode Optimization in Process Industry
Linnosmaa, J. (Manager), Seppi, M. (Participant), Zeb, A. (Participant), Saarela, O. (Participant), Verma, N. (Participant), Freimane, L. (Participant), Aho, J. (Participant) & Tahkola, M. (Participant)
1/09/22 → 31/08/25
Project: Business Finland project
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Deep learning-based surrogate model for generation of wood microstructures
Mińkowski, M., Seyedheydari, F., Seppi, M., Chen, B., Grassano, D. & Särkkä, S., 2026, In: Next Materials. 13, 102641.Research output: Contribution to journal › Article › Scientific › peer-review
Open Access -
Development of Artificial Intelligence and Machine Learning for Online Perception and Operating Mode Optimization in Process Industry (AIMODE) - Project results
Linnosmaa, J., Seppi, M., Zeb, A., Verma, N. & Freimane, L., 13 Oct 2025, VTT Technical Research Centre of Finland. 13 p. (VTT Research Report; No. VTT-R-00442-25).Research output: Book/Report › Report
Open AccessFile81 Downloads (Pure) -
Dynamic process optimization using data-driven surrogate models: Application to mineral processing
Zeb, A., Linnosmaa, J., Seppi, M., Verma, N. & Freimane, L., 13 Nov 2025.Research output: Contribution to conference › Conference Poster › Professional
Open AccessFile26 Downloads (Pure) -
Forecasting Process Output using Machine Learning Surrogates and Digital Twin
Seppi, M., Linnosmaa, J. & Zeb, A., 2025, Nuclear Plant Instrumentation and Control & Human-Machine Interface Technology (NPIC&HMIT 2025). American Nuclear Society (ANS), p. 434-443Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
File63 Downloads (Pure) -
Physics-informed machine learning surrogate models: Enhancing data-driven forecasting for digital twins in mineral processing
Seppi, M., Linnosmaa, J. & Zeb, A., 1 Sept 2025, In: Minerals Engineering. 230, 109424.Research output: Contribution to journal › Article › Scientific › peer-review
Open AccessFile15 Link opens in a new tab Citations (Scopus)644 Downloads (Pure)