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Mr. Usman Naseem

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Mr. Usman Naseem
Unit Coordinator and Lecturer

Usman’s teaching philosophy is to create a supportive educational environment where students with diverse backgrounds, interests, and learning styles can learn as productively and enjoyably as possible. As an active researcher, he has published many academic papers in his area. He is a member of different professional bodies, such as, IEEE, and the Association for Computing Machinery. He is also an academic reviewer of several reputed journals and has served as session chair/co-chair/TPC member of dozens of conferences.

Biography

Usman Naseem is a lecture and unit coordinator at Sydney International. He holds a BSc degree in Electrical Engineering and a Master in Analytics (Research). Usman has been teaching data science and analytics, data mining, and programming languages. He also has experience in supervising master level for their capstone projects. Before working in academia, Usman worked in leading ICT companies for more than ten years in various roles. Usman has published many peer-reviewed academic papers in well-reputed conferences and journals in this area as an active researcher. His research interests include natural language processing and data analytics in general, particularly in social media and healthcare analysis. As an academic, Usman is an active member of different professional bodies such as IEEE and the Association for Computing Machinery (ACM). He is also an academic reviewer of several reputed journals and served as session chair/co-chair/TPC member of dozens of conferences.

Teaching Philosophy

Usman’s teaching philosophy is to create a supportive educational environment where students with diverse backgrounds, interests, and learning styles can learn as productively and enjoyably as possible. He is committed to encouraging students to take an active role in their education, working with students to identify how they learn best, fostering excitement, exposing students to cutting-edge research as early as possible, supporting students in discovering and pursuing their interests, and reaching out to students to ensure they have a memorable learning experience.

Academic Qualifications
  • PhD Candidate at University of Sydney, Australia
  • Master in Analytics (Research), University of technology Sydney, Australia
Teaching Areas
  • Foundations of Data Science and Analytics
  • Programming Fundamentals
  • Data Engineering
  • Data Visualization
  • Python Programming
Scholarship and Research Areas

Scholarship

  • Recipient of RTP and RTPS – University of technology Sydney, Australia
  • Recipient of RTP and RTPS – University of Sydney, Australia
  • Receipt of scholarship top-up – University of Sydney, Australia

Research Areas

  • Natural Language Processing
  • Computer vision
  • Medical Image analysis
  • Social media analytics
  • Healthcare analytics
Grants and Awards
  • Recipient of “Quality Research Award 2021 NBMLHD
  • Best Performance Awards while working in Industry.
Publications

Book Chapters

  • Naseem U., Khan S.K., Razzak I., I Hameed: Hybrid Words Representation for Airlines Sentiment Analysis., The 32nd Australasian Joint Conference on Artificial Intelligence.
    Peer Reviewed Journal Papers
  • Naseem U., Razzak I., Musial K., Imran M.: Transformer based Deep Intelligent Contextual Embedding (DICE) for Twitter Sentiment Analysis; Future Generation Computer System.
  • U. Naseem, I. Razzak, M. Khushi, P. W. Eklund and J. Kim, “COVIDSenti: A Large-Scale Benchmark Twitter Data Set for COVID-19 Sentiment Analysis,” in IEEE Transactions on Computational Social Systems, doi: 10.1109/TCSS.2021.3051189.
  • Naseem, U., Razzak, I., & Eklund, P. W. (2020). A survey of pre-processing techniques to improve short-text quality: a case study on hate speech detection on twitter. Multimedia Tools and Applications, 1-28.
  • Naseem U., Khan S.K., Farasat M., Ali F.: Abusive language detection: A Comprehensive Review: Indian Journal of Science and Technology., IJST,2019, DOI: 10.17485/ijst/2019/v12i45/146538.
  • Naseem, U., Razzak, I., Khan, S. K., & Prasad, M. (2020). A Comprehensive Survey on Word Representation Models: From Classical to State-Of-The-Art Word Representation Language Models. arXiv preprint arXiv:2010.15036.
  • Naseem, U., Razzak, I., and Hameed, I. A. Deep Context-Aware Embedding for Abusive and Hate Speech detection on Twitter. Australian Journal of Intelligent Information Processing Systems, 69.
  • Naseem, U., Khushi, M., Khan, S. K., Shaukat, K., & Moni, M. A. (2021). A Comparative Analysis of Active Learning for Biomedical Text Mining. Applied System Innovation, 4(1), 23.
  • Khan S.K., Naseem U., Hussain J: Performance Evaluation of Next generation Wireless (5G) UAV relay; Wireless Personal Communications.
  • Samanta S., Jeong GL., Naseem U., and Khan SK: Coloring of Cluster Hypergraphs: Mathematical Problems in Engineering (MPE).
  • Hussain J., Naseem U., Khan S.K.: A Proposed Framework for the security of Financial Systems: Indian Journal of Science and Technology., IJST,2019, DOI: 10.17485/ijst/2019/v12i21/143891.
  • Naz, A. R. S., Naseem, U., Razzak, I., & Hameed, I. A. Deep AutoEncoder-Decoder Framework for Semantic Segmentation of Brain Tumor. Australian Journal of Intelligent Information Processing Systems, 53.
  • Khan S.K., Farasat M., Naseem U., Ali F: Performance Optimization for Next Generation UAV Relay with Millimeter-Wave Simultaneously in Access and Backhaul: Indian Journal of Science and Technology., IJST,2019.
  • Hussain J., Naseem U., Khan S.K.: A Systematic Overview and Comparative Analysis of Service Discovery Protocols and Middlewares; International Journal of Advanced Computer Science and Applications (IJACSA).
  • Das, K., Samanta, S., Khan, S. K., Naseem, U., & De, K. (2020). A Study on Discrete Mathematics: Sum Distance in Neutrosophic Graphs with Application. Neutrosophic Sets and Systems, 35(1), 13.
  • Qazi, A., Naseer, K., Qazi, J., AlSalman, H., Naseem, U., Yang, S., … & Gumaei, A. (2020). Conventional to online education during COVID-19 pandemic: Do develop and underdeveloped nations cope alike. Children and Youth Services Review, 119, 105582.
  • Samanta, S., Lee, J. G., Naseem, U., Khan, S. K., & Das, K. (2020). Concepts on Coloring of Cluster Hypergraphs with Application. Mathematical Problems in Engineering, 2020.
  • Khan, S. K., Farasat, M., Naseem, U., & Ali, F. (2019). Link‐level Performance Modelling for Next-Generation UAV Relay with Millimetre‐Wave Simultaneously in Access and Backhaul. Indian Journal of Science and Technology, 12(39), 1-9.
  • Das, K., Naseem, U., Samanta, S., Khan, S. K., & De, K. Fuzzy mixed graphs and its application to identification of COVID19 affected central regions in India. Journal of Intelligent & Fuzzy Systems, (Preprint), 1-14.
  • Qazi, A., Bhowmik, C., Hussain, F., Yang, S., Naseem, U., Adebayo, A. A., … & Al-Rakhami, M. (2021). Analyzing the Public Opinion as a Guide for Renewable-Energy Status in Malaysia: A Case Study. IEEE Transactions on Engineering Management.
  • Jaggi, M., Mandal, P., Narang, S., Naseem, U., & Khushi, M. (2021). Text Mining of Stocktwits Data for Predicting Stock Prices. Applied System Innovation, 4(1), 13.
  • Khan, S. K., Naseem, U., Siraj, H., Razzak, I., & Imran, M. (2021). The role of unmanned aerial vehicles and mmWave in 5G: Recent advances and challenges. Transactions on Emerging Telecommunications Technologies, e4241.
  • Qazi, A., Qazi, J., Naseer, K., Zeeshan, M., Qazi, S., Abayomi-Alli, O., Ahmad, I.S., Darwich, M., Talpur, B.A., Hardaker, G. and Naseem, U., 2021. Adaption of Distance Learning to Continue the Academic Year Amid COVID-19 Lockdown. Children and Youth Services Review, p.106038.
  • Mahapatra, R., Samanta, S., Pal, M., Lee, J. G., Khan, S. K., Naseem, U., & Bhadoria, R. S. (2021). Colouring of COVID-19 Affected Region Based on Fuzzy Directed Graphs. CMC-COMPUTERS MATERIALS & CONTINUA, 68(1), 1219-1233.
  • Qazi, A., Qazi, J., Naseer, K., Zeeshan, M., Qazi, S., Abayomi-Alli, O., Ahmad, I.S., Darwich, M., Talpur, B.A., Hardaker, G. and Naseem, U., 2021. Adaption of distance learning to continue the academic year amid COVID-19 lockdown. Children and Youth Services Review, 126, p.106038.
  • Awan, M. J., Khan, R. A., Nobanee, H., Yasin, A., Anwar, S. M., Naseem, U., & Singh, V. P. (2021). A Recommendation Engine for Predicting Movie Ratings Using a Big Data Approach. Electronics, 10(10), 1215.

Conference Proceedings

  • Naseem U., Khushi M., Reddy V., Rajendran S., Razzak I., Kim J.: BioALBERT: A Simple and Effective Pre- trained Language Model for Biomedical Named Entity Recognition; International Joint Conference on Neural Networks (IJCNN-21) (CORE/ERA Rank A).
  • Naseem U., Khushi M., Kim J., Dunn GA.: Classifying vaccine sentiment tweets by modelling domain-specific representation and commonsense knowledge into context-aware attentive GRU; International Joint Conference on Neural Networks (IJCNN-21) (CORE/ERA Rank A).
  • Jahan S., Islam MD R., Hasib K., Naseem U., Islam Md Saiful: Active Learning with an Adaptive Classifier for Inaccessible Big Data Analysis; International Joint Conference on Neural Networks (IJCNN-21) (CORE/ERA Rank A).
  • Naseem U., Musial K., DICE: Deep Intelligent Contextual Embedding for Twitter Sentiment Analysis, International Conference on Document Analysis and Recognition, ICDAR 2019, (CORE/ERA Rank A).
  • Naseem U., Musial K., Eklund P., Mukesh P.: Biomedical Named-Entity Recognition by Hierarchically Fusing BioBERT Representations and Deep Contextual-Level Word-Embedding; International Joint Conference on Neural Networks (IJCNN-20) (CORE/ERA Rank A).
  • Naseem U., Razzak I., Eklund P., Musial K.: Towards Improved Deep Contextual Embedding for the identification of Irony and Sarcasm; International Joint Conference on Neural Networks (IJCNN-20) (CORE/ERA Rank A).
  • Naseem U., Khan S.K., Razzak I., I Hameed: Hybrid Words Representation for Airlines Sentiment Analysis. The 32nd Australasian Joint Conference on Artificial Intelligence, (CORE/ERA Rank B).
  • Razzak I., Naseem U., Naz S., I Hameed: “Robust Nuclear Norm Minimization in Frequency Domain for Complex Noise”. 26th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society, ICONIP 2019, (CORE/ERA Rank A).
  • A. Panta, M. Khushi, D. Catchpoole, P. Kennedy, U. Naseem., Classification of Neuroblastoma Histopathological Images Using Machine Learning., “. 27th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society, ICONIP 2020, (CORE/ERA Rank A).
  • S. Thapa, S. Adhikari, U. Naseem, P. Singh, G. Bharathy, M. Prasad., Detecting Alzheimer’s Disease by Exploiting Linguistic Information from Nepali Transcript., 27th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society, ICONIP 2020, (CORE/ERA Rank A).
  • Naseem, U., Khushi, M., Khan, S. K., Waheed, N., Mir, A., Qazi, A., … & Poon, S. K. (2020, November). Diabetic Retinopathy Detection Using Multi-layer Neural Networks and Split Attention with Focal Loss. In International Conference on Neural Information Processing (pp. 26-37). Springer, Cham. (CORE/ERA Rank A).
  • U. Naseem, M. Khushi, S.K. Khan, N. Waheed, A. Mir, A. Qazi, B. Alshammari., Diabetic Retinopathy Detection Using Multi-layer Neural Networks and Split Attention with Focal Loss., 27th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society, ICONIP 2020, (CORE/ERA Rank A).
  • M. Khushi, U. Naseem, J. Du, A. Khan, S.K. Poon., Data mining ENCODE data predicts a significant role of SINA3 in human liver cancer., 27th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society, ICONIP 2020, (CORE/ERA Rank A).
  • Khan, S. K., Naseem, U., Sattar, A., Waheed, N., Mir, A., Qazi, A., & Ismail, M. (2020, November). UAV-aided 5G Network in Suburban, Urban, Dense Urban, and High-rise Urban Environments. In 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA) (pp. 1-4). IEEE. (CORE/ERA Rank A).
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