Shahina Begum, Professor
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, 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,
- IntoDeep (Project leader for MDH, AI and Deep learning materials for Process industries), https://aiclass.se
- KIT (WP: AI and Big Data for Production Industries, leader for MDH ),
- Prompt (Main responsible for the courses, 'Machine Learning with Big Data course' with more than 500 applicants in HT 2018, MOOC course: Basic Knowledge on ML),
- FutureE (Main responsible for the course: Predictive Data Analytics, Developer and teacher: Deep Learning for Industrial Imaging)
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
When a CBR in Hand is Better than Twins in the Bush (Sep 2022) Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum, Mir Riyanul Islam, Rosina O Weber Fourth Workshop on XCBR: Case-Based Reasoning for the Explanation of Intelligent Systems (XCBR)
Machine Learning Based Digital Twin in Manufacturing: A Bibliometric Analysis and Evolutionary Overview (Jul 2022) Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum Applied Sciences- Computing and Artificial Intelligence(Special issue:Artificial Intelligence and Optimization in Industry 4.0) (applsci)
A Systematic Review of Explainable Artificial Intelligence in terms of Different Application Domains and Tasks (Jan 2022) Mir Riyanul Islam, Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum Applied Sciences - Computing and Artificial Intelligence (Special Issue: Explainable Artificial Intelligence (XAI)) (ApplSci XAI)
A Survey on Artificial Intelligence (AI) and eXplainable AI in Air Traffic Management: Current Trends and Development with Future Research Trajectory (Jan 2022) Augustin Degas , Mir Riyanul Islam, Christophe Hurter , Shaibal Barua, Hamidur Rahman, Minesh Poudel , Daniele Ruscio , Mobyen Uddin Ahmed, Shahina Begum, Md Aquif Rahman, Stefano Bonelli , Giulia Cartocci , Gianluca Di Flumeri , Gianluca Borghini , Fabio Babiloni , Pietro Aricò Applied Sciences - Computing and Artificial Intelligence (Special Issue: Explainable Artificial Intelligence (XAI)) (ApplSci XAI)
Dilemmas in designing e-learning experiences for professionals (Dec 2021) Mobyen Uddin Ahmed, Ioanna Aslanidou, Jakob Axelsson, Shahina Begum, Leo Hatvani, Anders Olsson, Sebastian Schwede, Carina Sjödin, Jan Skvaril, Valentina Zaccaria 20th European Conference on e-Learning (ECEL)
Explainable Machine Learning to Improve Assembly Line Automation (Dec 2021) Sharmin Sultana Sheuly, Mobyen Uddin Ahmed, Shahina Begum, Michael Osbakk 4th International Conference on Artificial Intelligence for Industries (ai4i 2021)
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)