Shahina Begum, Associate Professor
Dr. Shahina Begum, Associate 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 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 vehicle driver-monitoring and prediction systems in collaboration with industrial partners.
Shahina has been involved (as course main responsible/designer/teacher/examiner) of total 15 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 need 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:
Deep Learning for Automatic EEG Feature Extraction: An Application in Drivers' Mental Workload Classification (Nov 2019) Mir Riyanul Islam, Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum, Gianluca Di Flumeri The 3rd International Symposium on Human Mental Workload: Models and Applications (H-WORKLOAD 2019)
Non-contact-based Driver's Cognitive Load Classification using Physiological and Vehicular Parameters (Nov 2019) Hamidur Rahman, Mobyen Uddin Ahmed, Shaibal Barua, Shahina Begum Biomedical Signal Processing and Control (BSPC)
A Vision based Indoor Navigation System for Individual with Visual Impairment (Sep 2019) Mobyen Uddin Ahmed, Mohammed Ghaith Altarabichi, Shahina Begum, Fredrik Ginsberg , Robert Glaes , Magnus Östgren , Hamidur Rahman, Magnus Sörensen International Journal of Artificial Intelligence (IJAI)
Hypothyroid Disease Diagnosis with Causal Explanation using Case-based Reasoning and Domain-specific Ontology (Sep 2019) Mir Riyanul Islam, Shaibal Barua, Shahina Begum, Mobyen Uddin Ahmed Workshop on CBR in the Health Science (WHS ICCBR 2019)
Non-contact Physiological Parameters Extraction using Facial Video considering Illumination, Motion, Movement and Vibration (May 2019) Hamidur Rahman, Mobyen Uddin Ahmed, Shahina Begum IEEE Transactions on Biomedical Engineering (TBME)
Drivers' Sleepiness Classification using Machine Learning with Physiological and Contextual data (Mar 2019) Shaibal Barua, Mobyen Uddin Ahmed, Shahina Begum First International Conference on Advances in Signal Processing and Artificial Intelligence (ASPAI' 2019)
Hamidur Rahman
Mir Riyanul Islam
Mohammed Ghaith Altarabichi
Shaibal Barua (former)
Sara Abbaspour (former)
Taha Kahn (former)