Foteini Liwicki

About me

I am a pationate lifelong learner researcher, seeking to expand my knowledge in the field of Neuroscience, fascinating of the curiosity of my brain to learn how itself -brain- is working. Since I remember my self, always wanted to be an inventor.

Since 2022, I lead the Machine Learning Focus Group – Brain Analysis, which develops computational methods for multimodal brain analysis to advance the understanding of communication and cognition in health and disease. Our research spans several complementary areas, including the neural mechanisms of inner speech and their role in communication (with relevance to Amyotrophic Lateral Sclerosis and language impairments), neurodegenerative disorders such as dementia, neurodevelopmental conditions such as ADHD, and the therapeutic effects of singing on mental health and emotional well-being. Together, we aim to build integrative and ethically grounded machine learning approaches to better understand and support human communication across diverse populations.

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”. A web based demonstrator of the mathematical expression recongition tool is available here.

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, 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.

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

Main research focus

• Inner speech and communication
• Neurodegenerative disorders
• Neurodevelopmental disorders
• Music and mental health
  
• Multimodal data fusion (EEG–fMRI integration)
• Interpretable machine learning for brain decoding

Reviewer in: She serves as a reviewer in international scientific journals and conferences (e.g. TNNLS, Scientific Data, Pattern Recognition Letters, DAS, ICFHR, ICDAR).

Member of: ENCALS

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

Projects

• 2025-2027, Understanding the Neural Dynamics of Inner Speech: A Multimodal and Longitudinal Perspective, Kempestiftelserna link
• 2025-2027, MADHD-NET: Multimodal ADHD prediction model with Brain connectivity Networks, Kempestiftelserna link
• 2025-2029, Investigating the effect of singing in individuals with psychiatric disorders or mental conditions link
• 2023-2024, Bimodal synchronous electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition link
• 2022-2023, Bimodal asynchronous electroencephalography-functional magnetic resonance imaging dataset for inner-speech recognition link, publication link, dataset link, github link

Professional activities

• Advisory board member of ICDAR, 2024-present.
• Member of the IAPR Committee, for Equity, Diversity, and Inclusion (EDI).
• Education officer of the International Association for Pattern Recognition (IAPR) Technical Committee Number 11: Reading Systems.
• Institute of Document Analysis and Knowledge Science, Kyoto, Japan, link
• General chair of the 18th International Conference on Document Analysis and Recognition 2024, ICDAR2024
• Competition organizer of ICDAR2023 Competition on Recognition of Handwritten Mathematical Expressions CROHME 2023, part of ICDAR 2023
• Competition chair of the 16th International Conference on Document Analysis and Recognition, ICDAR 2021.
• Competition organiser of the ICDAR 2019 Historical Document Reading Challenge on Large Structured Family Records.
• Competition organiser of the ICDAR2017 Competition on layout analysis for challenging medieval manuscripts, link
• Program Committee member of 16th International Conference on Document Analysis and Recognition, ICDAR 2021.
• Program Committee member of 25th International Conference on Pattern Recognition, ICPR 2020.
• Program Committee member of 14th International Workshop on Document Analysis Systems, DAS 2020.
• Program Committee member of 17th International Conference on Frontiers of Handwriting Recognition, ICFHR 2020.
• Program Committee member of 15th International Conference on Document Analysis and Recognition, ICDAR 2019.
• Program Committee member of 2nd International Workshop on Open Services and Tools for Document Analysis, ICDAR-OST
• Program Committee member of 13th International Workshop on Document Analysis Systems, DAS2018
• Program Committee member of 14th International Conference on Document Analysis and Recognition, ICDAR2017
• Program Committee member of 1st International Workshop on Open Services and Tools for Document Analysis, ICDAR-OST

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

Awards

• 2023-2025: Kompetensutveckling till professor, dnr LTU-154-2023 link
• 2022: Grants for Excellent Research Projects Proposals of SRT.ai 2022
• 2020-2021: Ansökan juniora lovande forskare, dnr LTU-4449-2019

Teaching/Supervision

Courses

• Neuromorphic Computing (D7064E)
• Introduction to Artificial Intelligence (D0030E)

PhD students

• present, Kalliopi Petrou (main supervisor), Investigating the effect of singing in individuals with psychiatric disorders or mental conditions, link
• present, Christian Gunther (main supervisor), A Human-in-the-Loop Machine Learning approach to support the multi-modal and multi-task geological drill core analysis
• present, Filip Siman (co-supervisor), Lithostratigraphy and alteration at the Rävliden VMS deposit
• present, Pedro Alonso (co-supervisor), Intent classification
• 2023, Mattias Nilsson (co-supervisor), Event-Driven Architectures for Heterogeneous Neuromorphic Computing Systems, link
• 2022, Oluwatosin Adewumi (co-supervisor), Vector Representations of Idioms in Data-Driven Chatbots for Robust Assistance, link
• 2022, Priyamvada Shankar (co-supervisor), Data driven crop disease modeling, link

Master students

• present, Nathan Hiruy, Real time BCI using motor imagery paradigm.
• 2023, Maxime Arnaud, Inner speech detection using bimodal inner speech dataset.
• 2022, Valeria Buenrostro-Leiter, Fellipe Rollin, Brain Signal Analysis for Inner detection, link.
• 2022, Lisa Jonsson, Using machine learning to analyse EEG brain signals for inner speech detection, link.

In media

• 2024-11-04, Interview for the magazine University teachers in Sweden, link
• 2024-01-26, UR Sverige forskar, Tankeläsning med AI?
• 2023-05-04, Forskning & Framsteg
• 2023-05-09, Dagens ETC
• 2023-04-20, Invited Keynote Speaker, Title: Combining EEG and fMRI for inner speech decoding, BCI & NEUROTECHNOLOGY SPRING SCHOOL 2023, organized by g.tec link
• 2023-03-18 till 2023-03-25, Invited associate professor at the University of Nantes, France, link
• 2022-11-16, Speaker: Inner speech recognition – Toward speech prosthesis, MIRAI 2.0 Research and Innovation Week, Kyushu University, Japan, link
• 2022-05-28, Speaker: Using machine learning to analyse brain data, online event, MIRAI, link

Publications of Foteini Liwicki (Google Scholar)