Janne AlataloAI / DATA / SOFTWARE
CV

Curriculum vitae

Janne Alatalo

I work with AI, data analytics, and software development.

Download PDFPDF in English

Experience

  1. – Present

    Senior Specialist

    Jamk University of Applied Sciences

    Institute of Information Technology

    Research and development in AI, data analytics, and software development.

  2. –

    Specialist

    Jamk University of Applied Sciences

    Institute of Information Technology

    Research and development in AI, data analytics, and software development.

  3. –

    Project Engineer

    Jamk University of Applied Sciences

    Institute of Information Technology

    Work in multiple research and development projects.

  4. –

    Project Worker

    SkyNest Project

    Worked in a test automation team developing the FreeNest Test Service (FTNS) tool.

  5. –

    Trainee

    SkyNest Project

    Worked in a maintenance team implementing automated Debian packaging for the FreeNest project platform and maintaining its background systems.

Education

  1. Graduated

    Master of Engineering

    Information Technology, Full Stack Software Development

    Jamk University of Applied Sciences

    60 ECTS credits

  2. Graduated

    Bachelor of Engineering

    Software Engineering

    Jamk University of Applied Sciences

    240 ECTS credits

Projects at Jamk

  1. Project period –

    AI-Boost (AI-Loikka)

    Project Manager, AI and Data Specialist

    Project page · Jamk

  2. Project period –

    DataBoost – Data to boost business in manufacturing industry (VauhtiData)

    AI and Data Specialist

    Project page · Jamk

  3. Project period –

    Resilience of Modern Value Chains in a Sustainable Energy System (KEMAR)

    AI and Data Specialist

    Project page · Jamk

  4. Project period –

    Data for Utilisation – Leveraging digitalisation through modern artificial intelligence solutions and cybersecurity (Tieto tuottamaan)

    AI and Data Specialist

    Project page · Jamk

  5. Project period –

    MATINE – Applying artificial intelligence for anomaly based network intrusion detection system, phase 2

    AI and Data Specialist

    Project page · JYVSECTEC

  6. Project period –

    New expertise and business opportunities through data analytics

    AI and Data Specialist

    Project page · Jamk

  7. Project period –

    MATINE – Applying AI for anomaly based network intrusion detection system, phase 1

    AI and Data Specialist

    Project page · JYVSECTEC

  8. Project period –

    RDI2CluB – Rural RDI milieus in transition towards smart Bioeconomy Clusters and Innovation Ecosystems

    Software Specialist

    Project page · Jamk

  9. Project period –

    FINCSC PLUS

    Software Specialist

    Project page · JYVSECTEC

  10. Project period –

    Cyber Trust

    Software Specialist

    Project page · Jamk

  11. Project period –

    N4S@JAMK – Need for Speed at JAMK

    Software Specialist

    Project page · Jamk

Research publications

2025

  • Alatalo, J., Heilimo, E., Rantonen, M., Väänänen, O., & Sipola, T. (2025). Reducing emissions using artificial intelligence in the energy sector: A scoping review. Applied Sciences, 15(2), Article 999. https://doi.org/10.3390/app15020999

2024

  • Alatalo, J., Sipola, T., & Kokkonen, T. (2024). Food supply chain cyber threats: A scoping review. In A. Rocha, H. Adeli, G. Dzemyda, F. Moreira, & V. Colla (Eds.), Information systems and technologies (Vol. 801, pp. 94–104). Springer. https://doi.org/10.1007/978-3-031-45648-0_10

2023

  • Alatalo, J., Sipola, T., & Rantonen, M. (2023). Improved difference images for change detection classifiers in SAR imagery using deep learning. IEEE Transactions on Geoscience and Remote Sensing, 61, 1–14. https://doi.org/10.1109/tgrs.2023.3324994

2022

  • Alatalo, J., Korpihalkola, J., Sipola, T., & Kokkonen, T. (2022). Chromatic and spatial analysis of one-pixel attacks against an image classifier. In M.-A. Koulali & M. Mezini (Eds.), Networked systems (Vol. 13464, pp. 303–316). Springer. https://doi.org/10.1007/978-3-031-17436-0_20
  • Alatalo, J., Sipola, T., & Kokkonen, T. (2022). Detecting one-pixel attacks using variational autoencoders. In A. Rocha, H. Adeli, G. Dzemyda, & F. Moreira (Eds.), Information systems and technologies (Vol. 468, pp. 611–623). Springer. https://doi.org/10.1007/978-3-031-04826-5_60
  • Sipola, T., Alatalo, J., Kokkonen, T., & Rantonen, M. (2022). Artificial intelligence in the IoT era: A review of edge AI hardware and software. In 2022 31st Conference of Open Innovations Association (FRUCT) (pp. 320–331). IEEE. https://doi.org/10.23919/fruct54823.2022.9770931

2019

  • Kokkonen, T., Puuska, S., Alatalo, J., Heilimo, E., & Mäkelä, A. (2019). Network anomaly detection based on WaveNet. In O. Galinina, S. Andreev, S. Balandin, & Y. Koucheryavy (Eds.), Internet of things, smart spaces, and next generation networks and systems (Vol. 11660, pp. 424–433). Springer. https://doi.org/10.1007/978-3-030-30859-9_36
  • Puuska, S., Kokkonen, T., Alatalo, J., & Heilimo, E. (2019). Anomaly-based network intrusion detection using wavelets and adversarial autoencoders. In J.-L. Lanet & C. Toma (Eds.), Innovative security solutions for information technology and communications (Vol. 11359, pp. 234–246). Springer. https://doi.org/10.1007/978-3-030-12942-2_18

Scholarly editorial work

  • Co-editor · 2024 · Peer-reviewed book

    Sipola, T., Alatalo, J., Wolfmayr, M., & Kokkonen, T. (Eds.). (2024). Artificial intelligence for security: Enhancing protection in a changing world. Springer. https://doi.org/10.1007/978-3-031-57452-8

Professional editorial work

Other writings

Articles and other writing on my website