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Foteini Liwicki
Foteini Liwicki

Foteini Liwicki

Associate Professor
Luleå University of Technology
Machine Learning
Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
foteini.liwicki@ltu.se
+46 (0)920 491004
A3579 Luleå

Biography

Foteini Simistira Liwicki received her Ph.D. diploma from the School of Electrical and Computer Engineering, NTUA, Greece, in the field of Pattern Recognition in 2015 with the title “Recognition of online handwritten mathematical expressions”. From 1997 till 2015, she worked as Research Associate in the Institute of Language and Speech Processing, ATHENA R.C., where she was mainly responsible for research programs in the field of Pattern Recognition, Machine Learning and Natural Language Processing. She was also highly involved in the design and development of innovative educational platforms (targeting mainly high school education in Greece but also in other European countries). From 2015 till June 2019 she worked as a PostDoc fellow in the University of Fribourg (DIVA research group) in the field of Document Image Analysis and Database generation. From June 2018 till June 2019 she worked as a PostDoc fellow with the Machine Learning group at the Luleå University of Technology, Sweden. She serves as a reviewer in international scientific journals and conferences (e.g. Pattern Recognition Letters, DAS, ICFHR, ICDAR). Foteini Simistira Liwicki is also a scientific member of the Institute of Document Analysis and Knowledge Science, Kyoto, Japan.

From May 2022, she is working as Associate Professor at the Luleå University, in the area of Machine Learning and Artificial Intelligence.

Research interests

  • Machine Learning
  • Artificial Intelligence (AI)
  • Brain understanding
  • Behavior Analysis
  • Natural Language Processing (NLP)
  • Document Analysis
  • Handwriting recognition

Medical Neuroscience by Duke University on Coursera. Certificate earned at Wednesday, July 3, 2019 11:09 AM GMT (certificate)

Research activities

Program Committee member

  • 14th International Conference on Document Analysis and Recognition (ICDAR2017)
  • 1st International Workshop on Open Services and Tools for Document Analysis (ICDAR-OST) , part of the ICDAR2017 conference
  • 13th International Workshop on Document Analysis Systems (DAS2018)
  • 15th International Conference on Document Analysis and Recognition (ICDAR2019
  • 2nd International Workshop on Open Services and Tools for Document Analysis (ICDAR-OST), part of the ICDAR2019 conference
  • 14th International Workshop on Document Analysis Systems (DAS2020)
  • 17th International Conference on Frontiers of Handwriting Recognition (ICFHR2020)
  • 25th International Conference on Pattern Recognition (ICPR2020)
  • 16th International Conference on Document Analysis and Recognition (ICDAR2021

Competition Organiser

Competition Chair

  • 16th International Conference on Document Analysis and Recognition (ICDAR2021

General Chair

  • 18th International Conference on Document Analysis and Recognition (ICDAR2024) 

Evaluation of PhD theses

  • 2019 - External examiner for Stefano Martina - PhD Thesis - Classification of cancer records with deep learning methods, University of Florence, Italy
  • 2019 - External examiner for Qurat ul Ain - PhD Thesis - Segmentation of Urdu Nastalique, University of Engineering and Technology Lahore, Pakistan

Book chapters

  1. Simistira Liwicki, F. and Liwicki, M., 2020. Deep learning for historical document analysis. In Handbook Of Pattern Recognition And Computer Vision (pp. 287-303).
  2. Simistira Liwicki, F., 2020. DIVA-HisDB A Precisely Annotated Dataset of Challenging Medieval Manuscripts. Handwritten Historical Document Analysis, Recognition, And Retrieval-State Of The Art And Future Trends89, p.25.
  3. Simistira Liwicki F. et al., Deep Neural Network approaches for Analysing Videos of Music Performances, submitted to Journal of Creative Music Systems 2021, status: under revision

Preprint

  1. Simistira Liwicki, Foteini, et al. "Bimodal pilot study on inner speech decoding reveals the potential of combining EEG and fMRI." bioRxiv (2022). pdf

Teaching activities

Advanced Data Mining (D7043E), link
Introduction to Artificial Intelligence (D0030E), link
Program responsible of the national master in Applied Artificial Intelligence TCAIA, link
Program responsible of the international master in Applied Artificial Intelligence TMDIA, link

 

Presentations

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Publications

Conference paper

Fitting Rävliden North Zn-Pb-Ag-Cu deposit host stratigraphy into regional Skellefte district nomenclature (2022)

Simán. F, Jansson. N, Johnson. S, Liwicki. F, Rincon. J, Nordfeldt. E, et al.
Part of: Geological Society of Sweden, 150 year anniversary meeting, Abstract volume, s. 156-157, 2022
Conference paper

Imagined Object Recognition Using EEG-Based Neurological Brain Signals (2022)

Saini. R, Prabhu. S, Upadhyay. R, Rakesh. S, Chhipa. P, Mokayed. H, et al.
Part of: Recent Trends in Image Processing and Pattern Recognition (RTIP2R 2021), s. 305-319, Springer, 2022
Conference paper

Innovative Education Approach Toward Active Distance Education: a Case Study in the Introduction to AI course (2022)

Al-Azzawi. S, Kovács. G, Mokayed. H, Chronéer. D, Liwicki. F, Liwicki. M
Part of: Conference Proceedings. The Future of Education 2022, 2022
Conference paper

ML_LTU at SemEval-2022 Task 4: T5 Towards Identifying Patronizingand Condescending Language (2022)

Adewumi. T, Alkhaled. L, Mokayed. H, Liwicki. F, Liwicki. M
Part of: Proceedings of the 16th International Workshop on Semantic Evaluation (SemEval-2022), s. 473-478, Association for Computational Linguistics, 2022
Conference paper

Potential Idiomatic Expression (PIE)-English: Corpus for Classes of Idioms (2022)

Adewumi. T, Vadoodi. R, Tripathy. A, Nikolaidou. K, Liwicki. F, Liwicki. M
Part of: Proceedings of the 13th Language Resources and Evaluation Conference, s. 689-696, European Language Resources Association (ELRA), 2022