Dr. Ashik is a lecturer working with the First Year College. He has over 5 years of teaching experience and has delivered a variety of IT and computing units and courses at Victoria University (VU), Australia, and North South University, Bangladesh.

Within VU, Dr. Ashik has also worked with the College of Arts, Business, Law, Education, and IT and VU College to deliver IT units. Apart from his teaching career, Dr. Ashik is also an active researcher involved in biomedical knowledge extraction and detection, machine learning, fuzzy logic, data mining, and image processing studies.

As an early AI-career researcher, Dr. Ashik has published 14 articles, including 5 Q1 journal papers, 4 book chapters, and 5 conference articles, in the fields of brain disease detection with deep learning, digital image quality enhancement, trend and pattern recognition, etc. He is also engaged with IEEE Transactions on Artificial Intelligence, IEEE Transactions on Emerging Topics in Computational Intelligence, IEEE Transactions on Big Data, IEEE Transactions on Instrumentation and Measurement, IEEE Transactions on Neural Systems and Rehabilitation Engineering, Knowledge-Based Systems, Health Information Science and Systems, Scientific Reports, Neural Networks, Brain Topography, Neuropsychiatric Disease and Treatment, Frontiers in Human Neuroscience, Sensors, etc. journals as a reviewer, and the International Conference on Health Information Science (HIS) and International Conference on Web Information Systems Engineering (WISE) as a Session Chair and PC Member.

Portfolios

Areas of expertise

  • Biomedical engineering
  • Machine Learning
  • Image processing
  • Fuzzy Logic
  • Pattern recognition

Contact details

+61 (3) 9919 4023
[email protected]

Research Grants

  • Internal funding grants (New Initiative Funding Request-CAPEX) from Victoria University in 2023, totalling $ 95,400.
  • Internal funding grants (New Initiative Funding Request-CAPEX) from Victoria University in 2020, totalling $110708.
     

Publications

Refereed Journal Articles 

  • Alvi, A. M., Siuly, S., Wang, H., Wang, K., & Whittaker, F. (2022). A deep learning based framework for diagnosis of mild cognitive impairment. Knowledge-Based Systems, 248, 108815.
  • Alvi, A. M., Siuly, S., & Wang, H. (2022). A long short-term memory based framework for early detection of mild cognitive impairment from EEG signals. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(2), 375-388.
  • Alvi, A. M., Siuly, S., & Wang, H. (2022). Neurological abnormality detection from electroencephalography data: a review. Artificial Intelligence Review, 55(3), 2275-2312.
  • Paul, S., Alvi, A. M., & Rahman, R. M. (2021). An analysis of the most accident prone regions within the Dhaka Metropolitan Region using clustering. International Journal of Advanced Intelligence Paradigms, 18(3), 294-315.
  • Alvi, A. M., Tasneem, N., Hasan, A., & Akther, S. B. (2020). Impacts of blockades and strikes in Dhaka: a survey. International Journal of Innovative Business Strategies, 6(1), 369-377.

Refereed Book Chapters

  • Alvi, A. M., Siuly, S., De Cola, M. C., & Wang, H. (2022, October). Dram-net: A deep residual alzheimer’s diseases and mild cognitive impairment detection network using eeg data. In International Conference on Health Information Science (pp. 42-53). Cham: Springer Nature Switzerland.
  • Alv.i, A M., Siuly, S., & Wang, H. (2022, August). Challenges in electroencephalography data processing using machine learning approaches. In Australasian Database Conference (pp. 177-184). Cham: Springer International Publishing.
  • Paul, S., Alvi, A. M., Nirjhor, M. A., Rahman, S., Orcho, A. K., & Rahman, R. M. (2017). Analyzing accident prone regions by clustering. Advanced Topics in Intelligent Information and Database Systems 9, 3-13.
  • Hasan, M. A., Tasneem, N., Akther, S. B., Das, K., & Alvi, A. M. (2019). An analysis on recent mobile application trend in Bangladesh. In Web, Artificial Intelligence and Network Applications: Proceedings of the Workshops of the 33rd International Conference on Advanced Information Networking and Applications (WAINA-2019) 33 (pp. 195-204). Springer International Publishing.

Conference Presentations

  • Alvi, A. M., Siuly, S., Wang, H., Sun, L., & Cao, J. (2020). An adaptive image smoothing technique based on localization. In Developments of Artificial Intelligence Technologies in Computation and Robotics: Proceedings of the 14th International FLINS Conference (FLINS 2020) (pp. 866-873).
  • Alvi, A. M., Siuly, S., & Wang, H. (2021, October). Developing a deep learning based approach for anomalies detection from EEG data. In International Conference on Web Information Systems Engineering (pp. 591-602). Cham: Springer International Publishing.
  • Alvi, A. M., Basher, S. F., Himel, A. H., Sikder, T., Islam, M., & Rahman, R. M. (2017, July). An adaptive grayscale image de-noising technique by fuzzy inference system. In 2017 13th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD) (pp. 1301-1308). IEEE.
  • Alvi, A. M., Tasneem, N., Hasan, M. A., & Akther, S. B. (2019). A study to find the impacts of strikes on students and local shopkeepers in Bangladesh. In World Congress on Sustainable Technologies (WCST-2019).
  • Alvi, A. M., Shaon, M. F. I., Das, P. R., Mustafa, M., & Bari, M. R. (2017, December). Automated course management system. In 2017 12th International Conference for Internet Technology and Secured Transactions (ICITST) (pp. 161-166). IEEE.

Industry Experience

Ashik worked with the Maribyrnong City Council on their Footscray Smart City project as a System Requirement Analyst.

Research

Ashik Alvi - Victoria University Research Repository (VURR).