Ali Shariq Imran
Background and activities
Ali Shariq Imran obtained his Ph.D. from University of Oslo (UiO), Norway in Computer Science and a Masters in Software Engineering and Computing from National University of Science & Technology (NUST), Pakistan. He specializes in applied research with a focus on deep learning technology and its application to images, videos, speech, and semantic web.
Research Interests
- Deep Learnig
- Speech analysis
- Image and video analysis
- Contextual and semantic understanding, segmentation, object identification, OCR and tracking
- eLearning
- video learning objects, LMS, and MOOC
- Semantic Web & OSN
Memberships
- Board member, HCI International Conference on Social Computing and Social Media.
- IEEE member, Norway section.
Guest Editor
- Effectiveness of Search Engine and Social Networking Data in healthcare Systems - Journal of Medical Imaging and Health Informatics (JMIHI) - Link
- Software Standards and Their Impact in Reducing Software Failures - IEEE Access - Link
Teaching
- IMT 4451 - Coding and compression of media data, Master level.
- IMT 4062 - Project Management & Software Engineering, Master level.
- IMT 1471 - Web Project 1, Bachelor level.
Awards
- HEC scholorship holder
- UIUC scholarship holder under Faculty Development Program
- Best Paper award: "Analysis of Online Social Networks Posts to Investigate Suspects Using SEMCON", HCI Intl., Los Angeles, California, USA, 2015.
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
2021
- (2021) School of the Future: A Comprehensive Study on the Effectiveness of Augmented Reality as a Tool for Primary School Children’s Education. Applied Sciences. vol. 11 (11).
- (2021) Evaluating Polarity Trend Amidst the Coronavirus Crisis in Peoples’ Attitudes toward the Vaccination Drive. Sustainability. vol. 13 (10).
- (2021) Sentiment Analysis of Students’ Feedback with NLP and Deep Learning: A Systematic Mapping Study. Applied Sciences. vol. 11 (9).
- (2021) An Adaptive Game-Based Learning Strategy for Children Road Safety Education and Practice in Virtual Space. Sensors.
- (2021) The Impact of Translating Resource-Rich Datasets to Low-Resource Languages Through Multi-Lingual Text Processing. IEEE Access.
- (2021) Human action recognition using attention based LSTM network with dilated CNN features. Future generations computer systems. vol. 125.
- (2021) Game-based digital quiz as a tool for improving students’ engagement and learning in online lectures. IEEE Access. vol. 9.
- (2021) A Two-Stage Deep Modeling Approach to Articulatory Inversion. Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing.
- (2021) Towards Improved Classification Accuracy on Highly Imbalanced Text Dataset Using Deep Neural Language Models. Applied Sciences.
- (2021) A Systematic Mapping Review on MOOC Recommender Systems. IEEE Access.
- (2021) Towards Smart Home Automation Using IoT-Enabled Edge-Computing Paradigm. Sensors. vol. 21 (14).
2020
- (2020) Cross-Cultural Polarity and Emotion Detection Using Sentiment Analysis and Deep Learning on COVID-19 Related Tweets. IEEE Access. vol. 8.
- (2020) Weakly Supervised Framework for Aspect-Based Sentiment Analysis on Students’ Reviews of MOOCs. IEEE Access. vol. 8.
- (2020) WET: Word embedding-topic distribution vectors for MOOC video lectures dataset. Data in Brief. vol. 28.
- (2020) A Review on Traditional Machine Learning and Deep Learning Models for WBCs Classification in Blood Smear Images. IEEE Access. vol. 9.
2019
- (2019) Performance analysis of machine learning classifiers on improved concept vector space models. Future generations computer systems. vol. 96.
- (2019) Integrating word embeddings and document topics with deep learning in a video classification framework. Pattern Recognition Letters. vol. 128.
- (2019) The impact of deep learning on document classification using semantically rich representations. Information Processing & Management. vol. 56 (5).
- (2019) A Comparative Study of Deep Learning Techniques on Frame-Level Speech Data Classification. Circuits, systems, and signal processing. vol. 38.
- (2019) A Phonetic-Level Analysis of Different Input Features for Articulatory Inversion. Interspeech (USB).