Johannes Lindén

Doktorand|Doctoral Student

  • Tjänstetitel: Doktorand
  • Annan titel: Big Data Analysis
  • Avdelning: Institutionen för informationssystem och -teknologi (IST)
  • Telefon arbete: 010-1428069
  • E-postadress:
  • Rumsnummer: L428
  • Ort: Sundsvall
  • Forskningscentra: Sensible Things that Communicate
  • Anställd vid ämnet: Datateknik, Elektronik, Grafisk design, Matematik/Tillämpad matematik

PhD in Natural Language Processing

I am currently doing my PhD in Big Data Analysis with focus on understanding and processing unformated texts.


I was born in 1993 and raised in Gothenburg and educated as a Computer science engineer in Sundsvall. I love challanges and never want to give up the search for a solution to the facing problems. Having fun is also a part of my life and I enjoy the exitement of graphical programming where I can see the changes while developing, and combined with the theoretical parts I beleive anything is possible.

In the spare time I usualy do tennis, reading playing with friends and paintings


Text analysis
- Understanding unformated text
- Processing text
- Generating text


I just started my PhD so I don't have a lot to write here.

Extra kontaktinformation



Artiklar i tidskrifter

Lindén, J. , Wang, X. , Forsström, S. & Zhang, T. (2020). Productify news article classification model with Sagemaker. Advances in Science, Technology and Engineering Systems, vol. 5: 2, ss. 13-18.    


Lindén, J. , Wang, X. , Forsström, S. & Zhang, T. (2019). Bilingual Auto-Categorization Comparison of two LSTM Text Classifiers. I 2019 8th International Congress on Advanced Applied Informatics (IIAI-AAI).  

Lindén, J. , Forsström, S. & Zhang, T. (2018). Evaluating Combinations of Classification Algorithms and Paragraph Vectors for News Article Classification. I Proceedings of the 2018 Federated Conference on Computer Science and Information Systems. Warzaw : (Annals of Computer Science and Information Systems). S. 489--495.  

Licentiatavhandlingar, sammanläggningar

Lindén, J. (2021). Extracting Text into Meta-Data : Improving machine text-understanding of news-media articles. Lic.-avh. (Sammanläggning) Sundsvall : Mid Sweden University, 2021 (Mid Sweden University licentiate thesis : 181)