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.
- Deep Learnig
- Speech analysis
- Image and video analysis
- Contextual and semantic understanding, segmentation, object identification, OCR and tracking
- video learning objects, LMS, and MOOC
- Semantic Web & OSN
- Board member, HCI International Conference on Social Computing and Social Media.
- IEEE member, Norway section.
- 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
- 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.
- 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
- (2020) WET: Word embedding-topic distribution vectors for MOOC video lectures dataset. Data in Brief.
- (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) Predicting Student Dropout in a MOOC: An Evaluation of a Deep Neural Network Model. ICCAI '19 Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence.
- (2019) Evaluating Acoustic Feature Maps in 2D-CNN for Speaker Identification. ICMLC '19 Proceedings of the 2019 11th International Conference on Machine Learning and Computing.
- (2019) Text-Independent Speaker ID for Automatic Video Lecture Classification Using Deep Learning. ICCAI '19 Proceedings of the 2019 5th International Conference on Computing and Artificial Intelligence.
- (2019) A Study on the Performance Evaluation of Machine Learning Models for Phoneme Classification. ICMLC '19 Proceedings of the 2019 11th International Conference on Machine Learning and Computing.
- (2019) Transfer Learning to Timed Text Based Video Classification Using CNN. WIMS2019 Proceedings of the 9th International Conference on Web Intelligence, Mining and Semantics.
- (2018) MOOC dropout prediction using machine learning techniques: Review and research challenges. EDUCON 2018 - Emerging Trends and Challenges of Engineering Education Education.
- (2016) Towards Understanding the MOOC Trend: Pedagogical Challenges and Business Opportunities. Lecture Notes in Computer Science (LNCS). vol. 9753.
- (2016) Sub-Nyquist sampling and detection in Costas coded pulse compression radars. EURASIP Journal on Advances in Signal Processing. vol. 2016 (125).
- (2016) Automatic annotation of lecture videos for multimedia driven pedagogical platforms. Knowledge Management & E-Learning: An International Journal. vol. 8 (4).
- (2016) Pedagogical Document Classification and Organization Using Domain Ontology. Lecture Notes in Computer Science (LNCS). vol. 9753.
- (2016) An analysis of social collaboration and networking tools in eLearning. Lecture Notes in Computer Science (LNCS). vol. 9753.
- (2016) Mel Frequency Cepstral Coefficients Based Similar Albanian Phonemes Recognition. Lecture Notes in Computer Science (LNCS). vol. 9734.
- (2016) SEMCON: A semantic and contextual objective metric for enriching domain ontology concepts. International Journal on Semantic Web and Information Systems (IJSWIS). vol. 12 (2).
- (2011) Blackboard content classification for lecture videos. IEEE Transactions on Image Processing.