قدِّم طلبك الآن 
الدكتور محمد عمران
عالم أول
الدكتور محمد عمران
عالم أول
المؤهلات العلمية
PhD in Computer Science
MSc. Computer Science
الكيان
معهد قطر لبحوث الحوسبة
Divison
الحوسبة الاجتماعية
السيرة الذاتية
Dr. Muhammad Imran is a Senior Scientist and Lead of the Crisis Computing team at Qatar Computing Research Institute. Dr. Imran received his Ph.D. in computer science from the University of Trento in 2013. He then worked as a Research Scientist at QCRI from 2015-2020.
Dr. Imran has published over 80 research papers in top-tier international conferences and journals, including ACL, SIGIR, ICDM, ICWSM, and WWW. Four of his papers received the "Best Paper Award" and two "Best Paper Runner-up Award." He has been serving as a co-chair of the Social Media Studies track of the ISCRAM international conference since 2014 and has served as Program Committee for many major conferences and workshops.
PhD in Computer Science
University of Trento; Trento, Italy
2013
MSc. Computer Science
Mohammad Ali Jinnah University; Islamabad, Pakistan
2007
BS Computer Science
Allama Iqbal Open University; Islamabad, Pakistan
2003
Senior Scientist
Qatar Computing Research Institute
Apr 2021 - Present
Scientist
Qatar Computing Research Institute
Dec 2014 - Apr 2021
Postdoc
Qatar Computing Research Institute
Apr 2013 - Dec 2014
Research Associate
Qatar Computing Research Institute
Jun 2012 - Sep 2012
Database Administrator & Developer
National Uniersity of Science and Technology, Pakistan
Jul 2007 - Aug 2008
- Processing Social Media Messages in Mass Emergency: A Survey; ACM Computing Surveys; https://dl.acm.org/citation.cfm?id=2771588
- Processing Social Media Images by Combining Human and Machine Computing During Crises; In the International Journal of Human-Computer Interaction (IJHCI); https://www.tandfonline.com/doi/abs/10.1080/10447318.2018.1427831?journalCode=hihc20
- Humanitarian Health Computing using Artificial Intelligence and Social Media: A Narrative Literature Review; In the International Journal of Medical Informatics (IJMI); https://www.sciencedirect.com/science/article/pii/S1386505618300212
- Classifying and Summarizing Information from Microblogs during Epidemics; Journal of Information Systems Frontiers; https://link.springer.com/article/10.1007/s10796-018-9844-9
- Domain Adaptation with Adversarial Training and Graph Embeddings; 56th Annual Meeting of the Association for Computational Linguistics (ACL); https://www.aclweb.org/anthology/P18-1099
- Identifying Sub-events and Summarizing Information during Disasters; 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR), https://dl.acm.org/citation.cfm?id=3210030
- From Situational Awareness to Actionability: Towards Improving the Utility of Social Media Data for Crisis Response; 21st ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW); https://dl.acm.org/citation.cfm?id=3274464
- Using AI and Social Media Multimodal Content for Disaster Response and Management: Opportunities, Challenges, and Future Directions. In the Information Processing and Management (IPM) journal, 2020. DOI: https://doi.org/10.1016/j.ipm.2020.102261
- Non-Traditional Data Sources: Providing Insights into Sustainable Development. Communications of the ACM (CACM), 2021. DOI: https://doi.org/10.1145/3447739.
- Deep Learning Benchmarks and Datasets for Social Media Image Classification for Disaster Response. In Proceedings of the IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM), 2020. DOI: https://doi.org/10.1109/ASONAM49781.2020.9381294
- Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets. In Proceedings of the 28th International Conference on Computational Linguistics (COLING), 2020. DOI: https://doi.org/10.18653/v1/2020.coling-main.550
- Detecting Natural Disasters, Damage, and Incidents in the Wild. In Proceedings of the 16th European Conference on Computer Vision (ECCV), 2020. DOI: https://doi.org/10.1007/978-3-030-58529-7_20
- GeoCoV19: A Dataset of Hundreds of Millions of Multilingual COVID-19 Tweets with Location Information. ACM SIGSPATIAL Special, May, 2020. DOI: https://doi.org/10.1145/3404111.3404114
- Rapid Damage Assessment Using Social Media Images by Combining Human and Machine Intelligence. In Proceedings of the 17th International Conference on Information Systems for Crisis Response and Management (ISCRAM), Virginia, USA, 2020. DOI: https://arxiv.org/abs/2004.06675
- Automatic Identification of Eyewitness Messages on Twitter During Disasters. In the Journal of Information Processing and Management (IP&M), 2020. DOI: https://doi.org/10.1016/j.ipm.2019.102107
- Summarizing Situational Tweets in Crisis Scenarios: An Extractive-Abstractive Approach. In IEEE Transactions on Computational Social Systems Journal (IEEE TCSS), 2019. DOI: https://doi.org/10.1109/TCSS.2019.2937899
- 2016; Best Paper Award; International Conference on Information Systems for Crisis Response and Management; Rio de Janeiro/Brazil
- 2013; Best Paper Award; International Conference on Information Systems for Crisis Response and Management; Baden-Baden/Germany
- 2017; Runner-up Best Paper Award; International Conference on Information Systems for Crisis Response and Management; Albi/France
- 2015; Grand Prize at the Open Source World Challenge; South Korea ICT ministry; South Korea
- 2016; WISH Innovation Competition; WISH organizers; Doha/Qatar
- 2017; World Intellectual Property Day award; The Ministry of Economy and Commerce Qatar; Doha/Qatar
- 2007; Distinguished Position holder in MSc; Mohammed Ali Jinnah University; Islamabad/Pakistan