Dr. Shahina Begum, Professor, deputy leader of the Artificial Intelligence and Intelligent Systems group at MDH. Shahina’s research focuses on developing intelligent systems in medical and industrial applications. Shahina Begum received her PhD in Computer Science/Artificial Intelligence in 2011, Mälardalen University. Her research areas are Decision Support Systems, Knowledge-based Systems, Multimodal Machine Learning, Big Data Analytics, and Intelligent Monitoring Systems.
Shahina has been the principal applicant and project manager for a number of research projects at MDH. She has received a Swedish Knowledge Foundation’s Prospect individual grant for prominent young researchers in 2011 and is today leading several research projects in the area of intelligent -monitoring and prediction systems in collaboration with industrial partners. Shahina has been listed amongst the 100 most relevant researchers in digitalization by the Royal Swedish Academy of Engineering Sciences 2020.
Shahina has been involved (as course main responsible/designer/teacher/examiner) of total 17 distant and campus-based courses/learning modules mainly in Artificial Intelligence and Machine learning at MDH both for regular students and industrial professionals. She is the co-applicant and main responsible for the Artificial Intelligence contents for the proposal “Bachelor program in Applied AI” at MDH. Shahina has been involved in several initiatives for lifelong learning at MDH for example,
Shahina Begum has an extensive involvement of both research and teaching activities driven by industry needs and collaborative initiatives with both the public and private sectors. Shahina is active in the research community and has served as a steering committee member, program chair, co-chair and organizer of international conferences and workshops.
Press:
http://www.byggnorden.se/projekt/mdh-forskning-ska-fa-rebygga-arbetsplatsolyckor-pa-byggen
https://www.fagersta-posten.se/logga-in/manga-olyckor-pa-byggen-nu-ska-mdh-gora-arbetet-sakrare
https://hallbartbyggande.com/mer-kunskap-om-maskininlarning-ska-forebygga-arbetsplatsolyckor/
https://maskinentreprenoren.se/ai-ska-hindra-dodliga-olyckor/
http://anlaggningsvarlden.se/ny-forskning-ska-forebygga-arbetsplatsolyckor-pa-byggen/
https://www.entreprenad.com/article/view/695175/ai_ska_forebygga_olyckor_pa_byggen
http://www.orebronyheter.com/mdh-forskning-ska-forebygga-arbetsplatsolyckor-pa-byggen/
https://twitter.com/NCC_AB/status/1219531303093252096
https://www.instagram.com/p/B2hK5bEjR-w/?igshid=10lp16ebrn2gm&fbclid=IwAR1RNz-hBEF-qmqgImb7PeDFUcsocVj0URzIhEkrExXFlcsVxmIKgAx0JC4
https://www.vlt.se/logga-in/forskning-om-hur-folk-mar-och-beter-sig-i-trafiken-ska-minska-olycksriskerna
https://www.mdh.se/en/malardalen-university/articles/free-ai-education-to-improve-production-in-swedish-process-industry
Artificial Intelligence in Predictive Maintenance: A Systematic Literature Review on Review Papers (Jul 2023) Md Rakibul Islam , Shahina Begum, Mobyen Uddin Ahmed 7th International Congress and Workshop on Industrial AI and eMaintenance (IAI)
Cognitive Digital Twin in Manufacturing: A Heuristic Approach (Jun 2023) Atiq Ur Rehman, Mobyen Uddin Ahmed, Shahina Begum 19th International Conference on Artificial Intelligence Applications and Innovations (AIAI)
Explaining the Unexplainable: Role of XAI for Flight Take-Off Time Delay Prediction (Jun 2023) Waleed Reafee Sbu Jmoona, Mobyen Uddin Ahmed, Mir Riyanul Islam, Shaibal Barua, Shahina Begum, Ana Ferreira , Nicola Cavagnetto 19th International Conference on Artificial Intelligence Applications and Innovations (AIAI)
Quantitative Performance Analysis of Machine Learning Model from Discrete Perspective: A CaseStudy of Chip Detection in Turning Process (Mar 2023) Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum 15th International Conference on Agents and Artificial Intelligence (ICAART2023)
A Systematic Literature Review on Multimodal Machine Learning: Applications, Challenges, Gaps and Future Directions (Mar 2023) Arnab Barua, Mobyen Uddin Ahmed, Shahina Begum Journal of IEEE Access (IEEE-Access)
Interpretable Machine Learning for Modelling and Explaining Car Drivers' Behaviour: An Exploratory Analysis on Heterogeneous Data (Feb 2023) Mir Riyanul Islam, Mobyen Uddin Ahmed, Shahina Begum 15th International Conference on Agents and Artificial Intelligence (ICAART2023)
Md Rakibul Islam
Mohammed Ghaith Altarabichi (former)
Shaibal Barua (former)
Arnab Barua
Hamidur Rahman (former)
Mir Riyanul Islam
Sara Abbaspour (former)
Sharmin Sultana Sheuly (former)
Taha Kahn (former)