Master’s Education in Computer Science

Master’s Education in Computer Science

Master’s Education in Computer Science

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- Morning Coffee with IT
- IT Seminar Series

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PAWS Lab

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Education program
Projects
- Active projects
  Autonomous work machines (AUWO)
  Data-driven efficiency, productivity and competitiveness
  Tailoring the Master’s Programme in IT for the Central Ostrobothnia Region
  DustSense – Smart Dust Monitoring in Industrial Areas
  Developing the ICT Sector in Central Ostrobothnia
  IoT learning environment
  Quality for distance learning
  TAKOMO Smart Environmental Monitoring in Industrial Areas
  Industrial Big Data
  TIRA - Efficient Facility Management through Robotics and Sensor Technology
  Smart and sustainable living
  VESIKKO – Älykäs vesistökuormituksen monitorointiverkosto
- Completed projects
  YMPYRÄ
  DiVes
  WinIT
  HANKO
  SCIP
  RUOSTE
  ICT recruitment survey
  TEHO
  LoRE
  HAVINA
  LIoT
  DUDE
  SmartCampus
  SINNE
  SmartHome4E
  HATTU - From Project to Product
Research
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News and Events
- Events
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Contact

Leevi Lind, postdoctoral researcher

Information technology, teaching, research and projects

Email

Leevi Lind JyU:n sivuilla

Mäkelä, T., Luomala, J., Lind, L., & Hakala, I. (2026). Machine Learning Soft Sensor for Predicting the Product Quality of a Hydrogen Reduction Furnace. In 2026 12th International Conference on Control, Decision and Information Technologies (CoDIT) (pp. 227-232). IEEE. International conference on control, decision and information technologies. https://doi.org/10.1109/codit70676.2026.11630751

IoT technology