Dr. Mevludin Memedi is an Assistant Professor at the Department of Operations and Project Management, College of Business, Alfaisal University. He earned his PhD in Information Technology from Örebro University, Sweden, in 2014. Following his PhD, he held a tenure-track position in the Computer Engineering department at Dalarna University, Sweden, and later served as an Assistant Professor in Informatics at Örebro University. He has also been affiliated with the department of Information Systems and Operations Management, Vienna University of Economics and Business.
His teaching experience spans undergraduate and graduate courses at Swedish universities and Alfaisal University, covering topics such as computing technologies, information security, business statistics, e-commerce, database systems, machine learning, and quantitative research methods. He has been involved in course development, including new Master's program in Information Security Management at Örebro University, and together with colleagues at Örebro University has received a pedagogical award for a so-called "Walkshop model", which focuses on student-centered learning, from Swedish Information Systems Academy. In addition, Dr. Mevludin was involved in a study related to the effectiveness of flipped classroom approach at Dalarna University. He has also supervised PhD students, with two graduating in 2020 and 2022. Furthermore, during 2020 and 2021 Dr. Mevludin was involved in executive education related to Information Security for Örebro municipality and Swedish Transportation Agency.
Dr. Mevludin's research focuses on developing information systems for sustainable healthcare, particularly using machine learning, sensor technologies, and data visualization to improve patient care. His projects include monitoring Parkinson's disease symptoms, assessing pain using biosensors, empowering patients with digital tools, and preventing social isolation among the elderly. He has managed externally funded projects, collaborated with hospitals and companies, and authored over 40 peer-reviewed articles. He also has a patent application submitted.
Education
- Associate professor (Swedish academic title: Docent) in Informatics/Information Systems, 2024, Örebro University, Örebro, Sweden.
- PhD in Information Technology, 2014, Örebro University, Örebro, Sweden.
- Licentiate in Information Technology, 2011, Örebro University, Örebro, Sweden.
- Master of Science in Computer Engineering, 2008, Dalarna University, Borlänge, Sweden.
Projects
- Behaviours and beyond: Investigating information security policy compliance among IT professionals in Saudi Arabia (Funded by Alfaisal University)
- Controlled treatment of opiate-requiring pain using biosensors (Funded by Swedish Agency for Innovation)
- Remote monitoring of Parkinson's disease - empowerment of patients and improved treatment using ICT-based tools (Funded by Swedish Knowledge Foundation)
- Multimodal motor symptoms quantification platform for individualized Parkinson's disease (Funded by Swedish Agency for Innovation)
Awards/patents
- Teaching award from Swedish Information Systems Academy, 2023
- Best Master thesis degree from Teknikdalen Foundation in Borlänge, Sweden, 2009
- US patent application 16617088, Systems for evaluating dosage parameters.
Editorial, peer-review roles and PhD supervision:
- Editorial board member: Informatics in Medicine Unlocked.
- Editorial board member: BMC Medical Informatics and Decision Making.
- Evaluator for the Research-Based Teaching Program of the Ministry of Education, Science, Technology, and Innovation in Kosovo.
- Guest editor of special issue on "Advances in IoT, AI, and sensor-based technologies for disease treatment, health promotion and ageing well" at Sensors journal.
- Guest editor of special issue on "Emerging frontiers in technological integration for health, agriculture, and urban sustainability" at Discover Internet of Things journal.
- Track co-chair on "Cybersecurity and digitalization of financial and payment services in the era of emerging technologies" at the 16th Mediterranean Conference on Information Systems.
- Evaluator for the Slovenian SMASH research programme.
- Evaluator for the PEARL research programme of Luxemburg National Research Fund.
- Co-chair of a session at the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology, Honolulu, Hawaii, USA.
- Regular reviewer for following journals: Artificial Intelligence in Medicine, Journal of Medical Internet Research, Computer Methods and Programs in Biomedicine, IEEE Journal of Biomedical and Health Informatics, and Sensors.
- PhD supervision: two finished in May 2020 and Sep 2022 and two ongoing.
List of journal publications (h-index = 17 and circa 850 citations according to Google Scholar)
22. Thangavel, G., Memedi, M., & Hedström, K (2024). Information and communication technology for managing social isolation and loneliness among people with Parkinson disease: qualitative study of barriers and facilitators. Journal of Medical Internet Research, 26.
21. Thangavel, G. , Memedi, M. & Hedström, K. (2022).Customized information and communication technology for reducing social isolation and loneliness among older adults: Scoping review. JMIR Mental Health, 9(3).
20. Karni, L. , Jusufi, I. , Nyholm, D. , Klein, G. O. & Memedi, M. (2022). Toward improved treatment and empowerment of individuals with Parkinson's disease: Design and evaluation of an Internet of Things system. JMIR Formative Research, 6(6).
19. Aghanavesi, S. , Westin, J. , Bergquist, F. , Nyholm, D. , Askmark, H. , Aquilonius, S. M. , Constantinescu, R. , Medvedev, A. & et al. (2020). A multiple motion sensors index for motor state quantification in Parkinson's disease. Computer Methods and Programs in Biomedicine, 189.
18. Karni, L. , Dalal, K. , Memedi, M. , Kalra, D. & Klein, G. O. (2020). Information and communications technology-based interventions targeting patient empowerment: Framework development. Journal of Medical Internet Research, 22(8).
17. Aghanavesi, S. , Bergquist, F. , Nyholm, D. , Senek, M. & Memedi, M. (2020). Motion sensor-based assessment of Parkinson's disease motor symptoms during leg agility tests: results from levodopa challenge. IEEE Journal of Biomedical and Health Informatics, 24(1).
16. Johansson, D. , Thomas, I. , Ericsson, A. , Johansson, A. , Medvedev, A. , Memedi, M. , Nyholm, D. , Ohlsson, F. & et al. (2019). Evaluation of a sensor algorithm for motor state rating in Parkinson's disease. Parkinsonism & Related Disorders, 64.
15. Thomas, I. , Alam, M. , Bergquist, F. , Johansson, D. , Memedi, M. , Nyholm, D. & Westin, J. (2019). Sensor-based algorithmic dosing suggestions for oral administration of levodopa/carbidopa microtablets for Parkinson's disease: a first experience. Journal of Neurology, 266(3).
14. Thomas, I. , Memedi, M. , Westin, J. & Nyholm, D. (2019). The effect of continuous levodopa treatment during the afternoon hours. Acta Neurologica Scandinavica, 139(1).
13. Thomas, I. , Westin, J. , Alam, M. , Bergquist, F. , Nyholm, D. , Senek, M. & Memedi, M. (2018). A treatment-response index from wearable sensors for quantifying Parkinson's disease motor states. IEEE Journal of Biomedical and Health Informatics, 22(5).
12. Memedi, M. , Tshering, G. , Fogelberg, M. , Jusufi, I. , Kolkowska, E. & Klein, G. O. (2018). An interface for IoT: feeding back health-related data to Parkinson's disease patients. Journal of Sensor and Actuator Networks, 7(1).
11. Aghanavesi, S. , Nyholm, D. , Senek, M. , Bergquist, F. & Memedi, M. (2017). A smartphone-based system to quantify dexterity in Parkinson's disease patients. Informatics in Medicine Unlocked, 9.
10. Sadikov, A. , Groznik, V. , Možina, M. , Žabkar, J. , Nyholm, D. , Memedi, M. & Georgiev, D. (2017). Feasibility of spirography features for objective assessment of motor function in Parkinson's disease. Artificial Intelligence in Medicine, 81.
9. Senek, M. , Aquilonius, S. , Askmark, H. , Bergquist, F. , Constantinescu, R. , Ericsson, A. , Lycke, S. , Medvedev, A. & et al. (2017). Levodopa/carbidopa microtablets in Parkinson's disease: a study of pharmacokinetics and blinded motor assessment. European Journal of Clinical Pharmacology, 73(5).
8. Aghanavesi, S. , Memedi, M. , Dougherty, M. , Nyholm, D. & Westin, J. (2017). Verification of a method for measuring Parkinson's disease related temporal irregularity in spiral drawings. Sensors, 17(10).
7. Memedi, M. , Sadikov, A. , Groznik, V. , Zabkar, J. , Mozina, M. , Bergquist, F. , Johansson, A. , Haubenberger, D. & et al. (2015). Automatic spiral analysis for objective assessment of motor symptoms in Parkinson's disease. Sensors, 15(9).
6. Memedi, M. , Nyholm, D. , Johansson, A. , Pålhagen, S. , Willows, T. , Widner, H. , Linder, J. & Westin, J. (2015). Validity and responsiveness of at-home touch screen assessments in advanced Parkinson's disease. IEEE Journal of Biomedical and Health Informatics, 19(6).
5. Memedi, M. , Khan, T. , Grenholm, P. , Nyholm, D. & Westin, J. (2013). Automatic and objective assessment of alternating tapping performance in Parkinson's disease. Sensors, 13(12).
4. Memedi, M. , Westin, J. & Nyholm, D. (2013). Spiral drawing during self-rated dyskinesia is more impaired than during self-rated off. Parkinsonism & related Disorders, 19(5).
3. Westin, J. , Schiavella, M. , Memedi, M. , Nyholm, D. , Dougherty, M. & Antonini, A. (2012). Validation of a home environment test battery for supporting assessments in advanced Parkinson's disease. Neurological Sciences, 33(4).
2. Memedi, M. , Westin, J. , Nyholm, D. , Dougherty, M. & Groth, T. (2011). A web application for follow-up of results from a mobile device test battery for Parkinson's disease patients. Computer Methods and Programs in Biomedicine, 104(2).
1. Westin, J. , Ghiamati, S. , Memedi, M. , Nyholm, D. , Johansson, A. , Dougherty, M. & Groth, T. (2010). A new computer method for assessing drawing impairment in Parkinson's disease. Journal of Neuroscience Methods, 190(1).
Published conference proceedings
19. Thangavel, G., Memedi, M., Moll, J. & Hedström, K (2023). Management of social isolation and loneliness in Parkinson's disease: design principles. Forty-fourth International Conference on Information Systems (ICIS), Hyderabad, India.
18. Memedi, M. , Miclescu, A. , Katila, L. , Claesson, M. , Essermark, M. , Holm, P. , Klein, G. O. , Spira, J. & et al. (2022). Sensor-based measurement of nociceptive pain: An exploratory study with healthy subjects. In: Hadas Lewy; Refael Barkan, Pervasive Computing Technologies for Healthcare 15th EAI International Conference 2021, December 6-8, 2021, virtual event.
17. Memedi, M. & Aghanavesi, S. (2020). A partial least squares regression model to measure Parkinson's disease motor states using smartphone data. In: Proceedings of the 53rd Hawaii International Conference on Systems Sciences (HICSS), January 7-10, 2020, Maui, Hawaii, USA.
16. Memedi, M. , Aghanavesi, S. , Bergquist, F. , Nyholm, D. & Senek, M. (2019). A multimodal sensor fusion platform for objective assessment of motor states in Parkinson's disease. In: IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), May 19-22, 2019, Chicago, Illinois, USA.
15. Thangavel, G. , Memedi, M. & Hedström, K. (2019). A systematic review of Social Internet of Things: Concepts and application areas. In: Americas Conference on Information Systems (AMCIS), August 15-17, 2019, Cancun, Mexico.
14. Karni, L. , Memedi, M. & Klein, G. O. (2019). Targeting patient empowerment via ICT interventions: An ICT-specific analytical framework. In: Americas Conference on Information Systems (AMCIS), August 15-17, 2019, Cancun, Mexico.
13. Matić, T. , Aghnavesi, S. , Memedi, M. , Nyholm, D. , Bergquist, F. , Groznik, V. , Žabkar, J. & Sadikov, A. (2019). Unsupervised learning from motion sensors data to assess the condition of patients with Parkinson's disease. In: Conference of Artificial Intelligence in Medicine (AIME), June 26-29, 2019, Poznan, Poland.
12. Javed, F. , Thomas, I. & Memedi, M. (2018). A comparison of feature selection methods when using motion sensors data: a case study in Parkinson's disease. In: International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), July 17-21, 2018, Honolulu, Hawaii, USA.
11. Memedi, M. , Lindqvist, J. , Tunedal, T. & Duvåker, A. (2018). A study on pre-adoption of a self-management application by Parkinson's disease patients. In: International Conference on Information Systems (ICIS), December 13-16, 2018, San Francisco, California, USA.
10. Kolkowska, E. , Scandurra, I. , Avatare Nöu, A. , Sjölinder, M. & Memedi, M. (2018). A user-centered ethical assessment of welfare technology for elderly. In: International Conference on Human Computer Interaction (HCI), July 15-20, 2018, Las Vegas, Nevada, USA.
9. Karni, L. , Memedi, M. , Kolkowska, E. & Klein, G. O. (2018). EMPARK: Internet of Things for empowerment and improved treatment of patients with Parkinson's disease. In: International Congress of Parkinson's Disease, October 5-9, 2018, Hong Kong.
8. Jusufi, I. , Memedi, M. & Nyholm, D. (2018). TapVis: A data visualization approach for assessment of alternating tapping performance in patients with Parkinson's disease. In: European Conference on Visualization (EuroVis), June 4-18, 2018, Brno, Czech Republic.
7. Thomas, I. , Bergquist, F. , Constantinescu, R. , Nyholm, D. , Senek, M. & Memedi, M. (2017). Using measurements from wearable sensors for automatic scoring of Parkinson's disease motor state: Results from 7 patients. In: International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), July 11-15, 2017, Jeju island, South Korea.
6. Memedi, M. , Aghanavesi, S. & Westin, J. (2016). A method for measuring Parkinson's disease related temporal irregularity in spiral drawings. In: IEEE International Conference on Biomedical and Health Informatics (BHI), February 24-27, 2016, Las Vegas, Nevada, USA.
5. Memedi, M. , Aghanavesi, S. & Westin, J. (2015). Digital spiral analysis for objective assessment of fine motor timing variability in Parkinson's disease. In: International Congress of Parkinson's disease and Movement Disorders, June 14-18, 2015, San Diego, California, USA.
4. Sadikov, A. , Žabkar, J. , Možina, M. , Groznik, V. , Nyholm, D. & Memedi, M. (2015). Feasibility of spirography features for objective assessment of motor symptoms in Parkinson's disease. In: 15th Conference on Artificial Intelligence in Medicine (AIME), June 17-20, 2015, Pavia, Italy.
3. Memedi, M. , Aghanavesi, S. & Westin, J. (2015). Objective quantification of Parkinson's disease upper limb motor timing variability using spirography. In: 37th International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), August 25-29, 2015, Milan, Italy.
2. Khan, T. , Memedi, M. , Song, W. W. & Westin, J. (2014). A case study in healthcare informatics: a telemedicine framework for automated Parkinson's disease symptom assessment. In: Smart Health International Conference (ICSH), July 10-11, 2014, Beijing, China.
1. Jusufi, I. , Nyholm, D. & Memedi, M. (2014). Visualization of spiral drawing data of patients with Parkinson's disease. In: 18th International Conference on Information Visualization (IV), July 16-18, 2014, Paris, France.