Edyta Łukasik, Ph.D.
email: e.lukasik@pollub.pl
Biography
Edyta Łukasik graduated mathematics at the University of Maria Curie-Sklodowska in Lublin. In 2007 received PhD titled “Iterative methods for nonlinear regular singular equations” in Faculty of Mathematics, Physics and Computer Science at UMCS in Lublin. She worked as assistant at the Institute of Computer Science, Lublin University of Technology from 1998 to 2007. Since 2007 she worked as assistant Professor at the Department of Computer Science, Lublin University of Technology.
For over 25 years, he has been conducting laboratory classes and lectures on the following subjects: programming in C, C++, Python, algorithms and data structures, numerical methods, programming in Objective-C and mobile applications in iOS. She also conducts classes for students on foreign exchange as part of the Erasmus project in the subject of Numerical Methods.
Currently, her scientific interests are brought together around three-dimensional data of movement, biomechanical analysis and neural networks. For several years, she has been scientifically working at the Laboratory of motion capture, equipped in the Vicon Motion Capture System. From 2024 she is a member of Division of Computer Vision and Machine Learning.
She is a promoter of over 60 engineering and master’s theses, and co-author of four academic textbooks and over 90 scientific and didactic articles.
She has experience in realization various of local and international projects and in project management.
Since 2020 she is Vice-Dean for student affairs for the direction of computer science at The Faculty of Electrical and Computer Science.
- Three-dimensional data of movement
- Biomechanical analysis
- Neural networks
- Fuzzy C-Means Clustering for Motion Capture Tennis Time-Series Data, Maria Skublewska-Paszkowska, Paweł Powroźnik, Paweł Karczmarek, Edyta Lukasik, Jakub Smolka, IEEE Access.- 2024, vol. 11, s. 1-22
- Recognition of human gait based on ground reaction forces and combined data from two gait laboratories, Marcin Derlatka, Maria Skublewska-Paszkowska, Paweł Powroźnik, Jakub Smołka, Edyta Łukasik, Agnieszka Borysiewicz, Piotr Borkowski, Dariusz Czerwiński, Acta Mechanica et Automatica.- 2024, vol. 18, nr 2, s. 361-366
- Tennis Patterns Recognition Based on a Novel Tennis Dataset – 3DTennisDS, Maria Skublewska-Paszkowska, Paweł Powroźnik, Edyta Łukasik, Jakub Smołka, Advances in Science and Technology Research Journal.- 2024, vol. 18, nr 6, s. 159-176
- Recognition of human gait based on ground reaction forces and combined data from two gait laboratories, Marcin Derlatk, Maria Skublewska-Paszkowska, Paweł Powroźnik, Jakub Smołka, Edyta Łukasik , Agnieszka Borysiewicz, Piotr Borkowski, Dariusz Czerwiński, Acta Mechanica et Automatica, 2024, vol. 18, nr 2, s. 361-366
- Relationship of lumbar-hip kinematics during trunk flexion and sex, body mass index, and self-reported energy expenditure: a cross-sectional analysis, Magdalena Zawadka, Jakub Smołka, Maria Skublewska-Paszkowska, Edyta Łukasik, Grzegorz Zieliński, Piotr Gawda, Acta of Bioengineering and Biomechanics, 2023, vol. 25, nr 1, s. 55-64
- Efficiency Comparison Of Networks in Handwritten Latin Characters Recognition with Diacritics, Edyta Łukasik, Wiktor Flis, Applied Computer Science, 2023, vol. 19, nr 4, s. 88-102
- The influence of sedentary behaviour on lumbar-pelvic kinematics during squatting and forward bending among physically active students, Magdalena Zawadka, Jakub Smołka, Maria Skublewska-Paszkowska, Edyta Łukasik, Mirosław Jabłoński, Piotr Gawda, Ergonomics, 2023, vol. 66, nr 1, s. 101-112
- Szybkość uczenia czy dokładność predykcji? Analiza porównawcza szkieletów programistycznych do sztucznej inteligencji, Konrad Zdeb, Piotr Żukiewicz, Edyta Łukasik, JCSI – Journal of Computer Sciences Institute, 2022, vol. 24, s. 172-175
- 3D technologies for intangible cultural heritage preservation—literature review for selected databases, Maria Skublewska-Paszkowska, Marek Miłosz, Paweł Powroźnik and Edyta Łukasik, Heritage Science, 2022, vol. 10, s. 1-24
- Analysis of the Possibility of Using the Singular Value Decomposition in Image Compression, Edyta Łukasik, Emilia Łabuć, Applied Computer Science, 2022, vol. 18, nr 4, s. 53-67