Dr Ahsan Morshed is an ICT lecturer at CQ University in Melbourne, Australia, and a CML-NET Centre member, contributing significantly to the Artificial Intelligence and Image processing field.
His research areas of expertise include Artificial Intelligence, AI Safety, Deep Learning, Explainable AI, Quantum Computing, Machine learning, Image Processing, Big Data Understanding, Social Data Analysis, Knowledge Discovery, Big Data Management and analytics, Highly Heterogeneous Information Integration and Data Exchange, and Data Quality.
Dr. Morshed's academic background is as impressive as his professional journey. He holds a Ph. D. degree from the University of Trento, Italy, an MSc from the Royal Institute of Technology (KTH), Stockholm, Sweden, and a BSc. Degree from Ahsanullah University of Technology, Bangladesh. All in computer science. Dr. Morshed has awarded $638,544K in grants (including internal and external) at CQU.
Dr. Morshed's professional journey is marked by diverse roles and significant contributions. Before joining CQUniversity, he was a Research Fellow at the Swinburne Data Science Research Institute, Swinburne University of Technology. His multi-disciplinary Data Science projects in collaboration with different faculties and industries led to the acquisition of over 700K grants within the last two and half years at Swinburne University of Technology. He also worked as a data scientist at RMIT University and a postdoctoral fellow at Data61, CSIRO, Australia, focusing on sensor data integration and machine learning in the agricultural domain. His role as an Information Management Specialist in the OEKC division at the Food and Agriculture Organisation of the United Nations (FAO of UN), Rome, Italy, further enriched his experience. Dr. Morshed's extensive experience, reflected in his publication of over 50 peer-reviewed a book, three book chapters, journals, conferences, and workshop papers, instils confidence in his abilities. He is an affiliated ACM, IEEE, HISA, and ACS member, has served on program committees of many national and international conferences, and has been a reviewer for numerous international journals.
Databases: MySQL, Microsoft SQL Server, Oracle, SQLite, and Mogo DB (No SQL database),
Programming: Java, Python, and R
Data Analytics tool: Matlab, BigML, Tableau, Power BI, Weka, spaCy(NLP) and KEA
Programming Environments: JDeveloper, Eclipse, Visual Studio. Net, Net beans and Anaconda
Cloud Platforms: Amazon AWS, and Microsoft Azure
Big Data Technologies: Apache Storm, Hadoop, Mahout (working knowledge), Amazon Web Services platform (AWS, Simple DB, Amazon S3) (hands-on experience), and HBase.
Semantic and Graph Technologies: SPARQL, Ontologies, and Virtuoso.
Build/Support Tools: Ant, Maven, SVN, and GitHub.
I am currently accredited for supervision in the following:
Artificial intelligence - Artificial intelligence not elsewhere classified
Artificial Intelligence and Image Processing - Image Processing
Artificial Intelligence and Image Processing - Neural, Evolutionary and Fuzzy Computation
Deep Learning
Artificial Intelligence and Image Processing - Pattern Recognition and Data Mining
Information Systems - Conceptual Modelling
Information Systems - Database Management
Information Systems - Information Systems Management
Machine learning - Deep learning
Machine learning - Neural networks