Dr Saiful Islam
Senior Lecturer
School of Information and Physical Sciences (Data Science and Statistics)
Career Summary
Biography
His research interest is in the field of big data, data management, AI, predictive analytics, and medical/health informatics. He has published extensively in these areas with more than 75 journal and conference papers, and book chapters. He has an H-index (current at 2022) of 22 with more than 1800 total citations (Google Scholar). He is a senior member of the IEEE (SMIEEE) and a fellow of higher education academy (FHEA).
Research profile:
Google Scholar: https://scholar.google.com.au/citations?hl=en&user=ZZUtmJ0AAAAJ
DBLP: https://dblp.uni-trier.de/pid/04/3572-3.html
LinkedIn: https://www.linkedin.com/in/saifulit/
Qualifications
- DOCTOR OF PHILOSOPHY, Swinburne University of Technology
- BACHELOR OF SCIENCE WITH HONOURS IN COMPUTER SCI AND ENG, University of Dhaka - Bangladesh
- MASTER OF SCIENCE IN COMPUTER SCIENCE AND ENGINEERING, University of Dhaka - Bangladesh
Keywords
- Artificial Intelligence
- Big Data
- Data Analytics
- Data Science
- Predictive Analytics
- Security Analytics
Languages
- English (Fluent)
- Bengali (Mother)
Fields of Research
Code | Description | Percentage |
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460506 | Graph, social and multimedia data | 20 |
460501 | Data engineering and data science | 40 |
460503 | Data models, storage and indexing | 40 |
Professional Experience
UON Appointment
Title | Organisation / Department |
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Senior Lecturer | University of Newcastle School of Information and Physical Sciences Australia |
Academic appointment
Dates | Title | Organisation / Department |
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20/2/2017 - 2/12/2022 |
Lecturer Lecturer in Big Data Analytics |
Griffith University School of Information and Communication Technology Australia |
20/5/2016 - 17/2/2017 |
Research Fellow Research Fellow |
La Trobe University School of Engineering and Mathematical Sciences Australia |
19/3/2014 - 19/5/2016 |
Research Associate Research Fellow |
Swinburne University of Technology Department of Computing Technologies Australia |
Awards
Award
Year | Award |
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2017 |
Best Paper Award 29th International Conference on Scientific and Statistical Database Management |
Member
Year | Award |
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2021 |
IEEE Senior Membership IEEE |
Recognition
Year | Award |
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2020 |
Fellow of Higher Education Academy Advance HE (UK) Higher Education Academy |
Research Award
Year | Award |
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2019 |
Best Paper Runner-up Award 24th International Conference on Database Systems for Advanced Applications |
2019 |
Best Paper Runner-up Award 15th International Conference on Advanced Data Mining and Applications |
Grant Reviews
Year | Grant | Amount |
---|---|---|
2018 |
ARC Discovery Projects C1200 - Aust Competitive - ARC - 1200, C1200 - Aust Competitive - ARC - 1200 Review ARC discovery projects. |
$0 |
Publications
For publications that are currently unpublished or in-press, details are shown in italics.
Chapter (11 outputs)
Year | Citation | Altmetrics | Link | |||||
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2021 |
Islam MS, 'Neighborhood Query Processing and Surrounding Objects Retrieval in Spatial Databases: Applications and Algorithms', Web and Big Data. APWeb-WAIM 2020 International Workshops, Springer Nature, Singapore 3-13 (2021) [B1]
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2020 |
Shen B, Islam MS, Taniar D, Wang J, 'Retrieving Text-Based Surrounding Objects in Spatial Databases', Advanced Information Networking and Applications, Springer Nature, Cham, Switzerland 927-939 (2020) [B1]
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2020 |
Ohira R, Islam MS, Jo J, Stantic B, 'AMGA: An Adaptive and Modular Genetic Algorithm for the Traveling Salesman Problem', Advances in Intelligent Systems and Computing, Springer International Publishing 1096-1109 (2020) [B1]
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2020 |
Wang J, Anirban S, Amagasa T, Shiokawa H, Gong Z, Islam MS, 'A Hybrid Index for Distance Queries', Web Information Systems Engineering WISE 2020, Springer Nature, Cham, Switzerland 227-241 (2020) [B1]
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2019 |
Anirban S, Wang J, Islam MS, 'Multi-level Graph Compression for Fast Reachability Detection', Database Systems for Advanced Applications, Springer Nature, Cham, Switzerland 229-246 (2019) [B1]
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2019 |
Ohira R, Islam MS, Jo J, Stantic B, 'LCS based diversity maintenance in adaptive genetic algorithms', Data Mining, Springer Nature, Singapore 56-68 (2019) [B1]
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2019 |
Kayesh H, Islam MS, Wang J, 'A Causality Driven Approach to Adverse Drug Reactions Detection in Tweets', , SPRINGER INTERNATIONAL PUBLISHING AG 316-330 (2019) [B1]
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Show 8 more chapters |
Journal article (39 outputs)
Year | Citation | Altmetrics | Link | |||||
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2023 |
Dipongkor AK, Islam MS, Hussain I, Yongchareon S, Mistry S, 'On Fusing Artificial and Convolutional Neural Network Features for Automatic Bug Assignments', IEEE Access, 11 49493-49508 (2023) [C1]
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Nova | ||||||
2023 |
Kayesh H, Islam MS, Wang J, 'Answering Binary Causal Questions Using Role-Oriented Concept Embedding', IEEE Transactions on Artificial Intelligence, 4 1426-1436 (2023) [C1]
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2022 |
Ngamakeur K, Yongchareon S, Yu J, Islam S, 'Passive infrared sensor dataset and deep learning models for device-free indoor localization and tracking', PERVASIVE AND MOBILE COMPUTING, 88 (2022) [C1]
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2022 |
Kayesh H, Islam MS, Wang J, Kayes ASM, Watters PA, 'A deep learning model for mining and detecting causally related events in tweets', Concurrency and Computation: Practice and Experience, 34 (2022) [C1]
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2022 |
Allheeib N, Adhinugraha K, Taniar D, Islam MS, 'Computing reverse nearest neighbourhood on road maps', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 25 99-130 (2022) [C1]
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2022 |
Kayesh H, Islam MS, Wang J, Ohira R, Wang Z, 'SCAN: A shared causal attention network for adverse drug reactions detection in tweets', NEUROCOMPUTING, 479 60-74 (2022) [C1]
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2022 |
Hasan K, Chowdhury MJM, Biswas K, Ahmed K, Islam MS, Usman M, 'A blockchain-based secure data-sharing framework for Software Defined Wireless Body Area Networks', COMPUTER NETWORKS, 211 (2022) [C1]
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2021 |
Mashrur FR, Islam MS, Saha DK, Islam SMR, Moni MA, 'SCNN: Scalogram-based convolutional neural network to detect obstructive sleep apnea using single-lead electrocardiogram signals', COMPUTERS IN BIOLOGY AND MEDICINE, 134 (2021) [C1]
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2021 |
Islam MR, Islam MM, Rahman MM, Mondal C, Singha SK, Ahmad M, et al., 'EEG Channel Correlation Based Model for Emotion Recognition', COMPUTERS IN BIOLOGY AND MEDICINE, 136 (2021) [C1]
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2021 |
Ohira R, Islam MS, Kayesh H, 'Speedup vs. quality: Asynchronous and cluster-based distributed adaptive genetic algorithms for ordered problems', PARALLEL COMPUTING, 103 (2021) [C1]
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2021 |
Anirban S, Wang J, Islam MS, Kayesh H, Li J, Huang ML, 'Compression techniques for 2-hop labeling for shortest distance queries', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 25 151-174 (2021) [C1]
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2021 |
Allheeib N, Islam MS, Taniar D, Shao Z, Cheema MA, 'Density-based reverse nearest neighbourhood search in spatial databases', JOURNAL OF AMBIENT INTELLIGENCE AND HUMANIZED COMPUTING, 12 4335-4346 (2021) [C1]
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2021 |
Saha SK, Riazul Islam SM, Saha T, Nishat A, Biswas PK, Gil M, et al., 'Prognostic role of EGR1 in breast cancer: A systematic review', BMB Reports, 54 497-504 (2021) [C1] EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, ... [more] EGR1 (early growth response 1) is dysregulated in many cancers and exhibits both tumor suppressor and promoter activities, making it an appealing target for cancer therapy. Here, we used a systematic multi-omics analysis to review the expression of EGR1 and its role in regulating clinical outcomes in breast cancer (BC). EGR1 expression, its promoter methylation, and protein expression pattern were assessed using various publicly available tools. COSMIC-based somatic mutations and cBioPortal-based copy number alterations were analyzed, and the prognostic roles of EGR1 in BC were determined using Prognoscan and Kaplan-Meier Plotter. We also used bc-GenEx-Miner to investigate the EGR1 co-expression profile. EGR1 was more often downregulated in BC tissues than in normal breast tissue, and its knockdown was positively correlated with poor survival. Low EGR1 expression levels were also associated with increased risk of ER+, PR+, and HER2-BCs. High positive correlations were observed among EGR1, DUSP1, FOS, FOSB, CYR61, and JUN mRNA expression in BC tissue. This systematic review suggested that EGR1 expression may serve as a prognostic marker for BC patients and that clinicopathological parameters influence its prognostic utility. In addition to EGR1, DUSP1, FOS, FOSB, CYR61, and JUN can jointly be considered prognostic indicators for BC. [BMB Reports 2021; 54(10): 497-504]
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2021 |
Islam MR, Moni MA, Islam MM, Rashed-Al-Mahfuz M, Islam MS, Hasan MK, et al., 'Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques', IEEE ACCESS, 9 94601-94624 (2021) [C1]
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2020 |
Shen B, Islam MS, Taniar D, 'Direction-based Spatial Skyline for Retrieving Arbitrary-Shaped Surrounding Objects', COMPUTER JOURNAL, 63 1668-1688 (2020) [C1]
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2020 |
Anwar T, Liu C, Vu HL, Islam MS, Yu D, Hoang N, 'Influence ranking of road segments in urban road traffic networks', COMPUTING, 102 2333-2360 (2020) [C1]
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2020 |
Hasan K, Ahmed K, Biswas K, Islam MS, Sianaki OA, 'Software-defined application-specific traffic management for wireless body area networks', FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 107 274-285 (2020) [C1]
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2020 |
Islam MS, Shen B, Wang C, Taniar D, Wang J, 'Efficient processing of reverse nearest neighborhood queries in spatial databases', INFORMATION SYSTEMS, 92 (2020) [C1]
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2020 |
Shen B, Islam MS, Taniar D, Wang J, 'Direction-based spatial skyline for retrieving surrounding objects', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 23 207-239 (2020) [C1]
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2020 |
Allheeib N, Taniar D, Al-Khalidi H, Islam MS, Adhinugraha KM, 'Safe Regions for Moving Reverse Neighbourhood Queries in a Peer-to-Peer Environment', IEEE ACCESS, 8 50285-50298 (2020) [C1]
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2020 |
Ohira RJ, Islam MS, Kayesh H, Islam SMR, 'MSGM: A Markov Model Based Similarity Guide Matrix for Optimising Ordered Problems by Balanced-Evolution Genetic Algorithms', IEEE ACCESS, 8 210286-210300 (2020) [C1]
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2020 |
Kaur S, Singla J, Nkenyereye L, Jha S, Prashar D, Joshi GP, et al., 'Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives', IEEE ACCESS, 8 228049-228069 (2020) [C1]
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2020 |
Kayes ASM, Islam MS, Watters PA, Ng A, Kayesh H, 'Automated measurement of attitudes towards social distancing using social media: A COVID-19 case study', First Monday, [C1]
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2020 |
Kayes ASM, Kalaria R, Sarker IH, Islam MS, Watters PA, Ng A, et al., 'A Survey of Context-Aware Access Control Mechanisms for Cloud and Fog Networks: Taxonomy and Open Research Issues', SENSORS, 20 (2020) [C1]
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2020 |
Hasan K, Ahmed K, Biswas K, Islam MS, Kayes ASM, Islam SMR, 'Control Plane Optimisation for an SDN-Based WBAN Framework to Support Healthcare Applications', SENSORS, 20 (2020) [C1]
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2019 |
Kayes ASM, Han J, Rahayu W, Dillon T, Islam MS, Colman A, 'A policy model and framework for context-aware access control to information resources', Computer Journal, 62 670-705 (2019) [C1] In today's dynamic ICT environments, the ability to control users' access to information resources and services has become ever important. On the one hand, it should pro... [more] In today's dynamic ICT environments, the ability to control users' access to information resources and services has become ever important. On the one hand, it should provide flexibility to adapt to the users' changing needs, while on the other hand, it should not be compromised. The user is often faced with different contexts and environments that may change the user's information needs. To allow for this, it is essential to incorporate the dynamically changing context information into the access control policies to reflect different contexts and environments through the use of a new context-aware access control (CAAC) approach with both dynamic associations of user-role and role-permission capabilities. Our proposed CAAC framework differs from the existing access control frameworks in that it supports context-sensitive access control to information resources and dynamically re-evaluates the access control decisions when there are dynamic changes to the context. It uses the dynamic context information to specify the user-role and role-permission assignment policies. We first present a formal policy model for our framework, specifying CAAC policies. Using this model, we then introduce a policy ontology for modeling CAAC policies and a policy enforcement architecture which supports access to resources according to the dynamically changing context information. In addition, we demonstrate the feasibility of our framework by considering (i) the completeness, correctness and consistency of the ontology concepts through application to healthcare scenarios and (ii) the performance and usability testing of the framework when using desktop and mobile-based prototypes.
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2019 |
Naseriparsa M, Islam MS, Liu C, Chen L, 'XSnippets: Exploring semi-structured data via snippets', DATA & KNOWLEDGE ENGINEERING, 124 (2019) [C1]
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2019 |
Hasan K, Biswas K, Ahmed K, Nafi NS, Islam MS, 'A comprehensive review of wireless body area network', Journal of Network and Computer Applications, 143 178-198 (2019) [C1] Recent development and advancement of information and communication technologies facilitate people in different dimensions of life. Most importantly, in the healthcare industry, t... [more] Recent development and advancement of information and communication technologies facilitate people in different dimensions of life. Most importantly, in the healthcare industry, this has become more and more involved with the information and communication technology-based services. One of the most important services is monitoring of remote patients, that enables the healthcare providers to observe, diagnose and prescribe the patients without being physically present. The advantage of miniaturization of sensor technologies gives the flexibility of installing in, on or off the body of patients, which is capable of forwarding physiological data wirelessly to remote servers. Such technology is named as Wireless Body Area Network (WBAN). In this paper, WBAN architecture, communication technologies for WBAN, challenges and different aspects of WBAN are illustrated. This paper also describes the architectural limitations of existing WBAN communication frameworks. blueFurthermore, implementation requirements are presented based on IEEE 802.15.6 standard. Finally, as a source of motivation towards future development of research incorporating Software Defined Networking (SDN), Energy Harvesting (EH) and Blockchain technology into WBAN are also provided.
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2019 |
Haryanto AA, Islam MS, Taniar D, Cheema MA, 'IG-Tree: an efficient spatial keyword index for planning best path queries on road networks', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 22 1359-1399 (2019) [C1]
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2019 |
Naseriparsa M, Liu C, Islam MS, Zhou R, 'XPloreRank: exploring XML data via you may also like queries', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 22 1727-1750 (2019) [C1]
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2019 |
Anirban S, Wang J, Islam MS, 'Modular Decomposition-Based Graph Compression for Fast Reachability Detection', Data Science and Engineering, 4 193-207 (2019) [C1] Fast reachability detection is one of the key problems in graph applications. Most of the existing works focus on creating an index and answering reachability based on that index.... [more] Fast reachability detection is one of the key problems in graph applications. Most of the existing works focus on creating an index and answering reachability based on that index. For these approaches, the index construction time and index size can become a concern for large graphs. More recently query-preserving graph compression has been proposed, and searching reachability over the compressed graph has been shown to be able to significantly improve query performance as well as reducing the index size. In this paper, we introduce a multilevel compression scheme for DAGs, which builds on existing compression schemes, but can further reduce the graph size for many real-world graphs. We propose an algorithm to answer reachability queries using the compressed graph. Extensive experiments with four existing state-of-the-art reachability algorithms and 12 real-world datasets demonstrate that our approach outperforms the existing methods. Experiments with synthetic datasets ensure the scalability of this approach. We also provide a discussion on possible compression for k-reachability.
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2018 |
Anwar T, Liu C, Vu HL, Islam MS, Sellis T, 'Capturing the Spatiotemporal Evolution in Road Traffic Networks', IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 30 1426-1439 (2018) [C1]
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2018 |
Naseriparsa M, Islam MS, Liu C, Moser I, 'No-but-semantic-match: computing semantically matched xml keyword search results', WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 21 1223-1257 (2018) [C1]
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2016 |
Islam MS, Liu C, 'Know your customer: computing k-most promising products for targeted marketing', VLDB JOURNAL, 25 545-570 (2016) [C1]
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Show 36 more journal articles |
Conference (26 outputs)
Year | Citation | Altmetrics | Link | |||||
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2023 |
Anirban S, Wang J, Islam MS, 'Experimental Evaluation of Indexing Techniques for Shortest Distance Queries on Road Networks', 2023 IEEE 39th International Conference on Data Engineering (ICDE), Anaheim, CA (2023) [E1]
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2023 |
Nahar L, Islam MS, Awrangjeb M, Verhoeve R, Tuxworth G, 'DeepCornerNet: A Deep Learning Approach for Automated Corner Grading in Trading Cards', 2023 International Conference on Digital Image Computing: Techniques and Applications, DICTA 2023, Port Macquarie, Australia (2023) [E1]
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Nova | ||||||
2021 |
Jahan S, Islam MR, Hasib KM, Naseem U, Islam MS, 'Active Learning with an Adaptive Classifier for Inaccessible Big Data Analysis', Proceedings of the International Joint Conference on Neural Networks, Shenzhen, China (2021) [E1]
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2021 |
Dipongkor AK, Islam MS, Kayesh H, Hossain MS, Anwar A, Rahman KA, Razzak I, 'DAAB: Deep Authorship Attribution in Bengali', 2021 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), ELECTR NETWORK (2021) [E1]
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2020 |
Kayesh H, Islam MS, Wang J, Anirban S, Kayes ASM, Wafters P, 'Answering Binary Causal Questions: A Transfer Learning Based Approach', 2020 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN), ELECTR NETWORK (2020) [E1]
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2020 |
Ohira R, Islam MS, 'GPU Accelerated Genetic Algorithm with Sequence-based Clustering for Ordered Problems', 2020 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC), ELECTR NETWORK (2020) [E1]
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2019 |
Ohira R, Islam MS, 'A distributed genetic algorithm with adaptive diversity maintenance for ordered problems', Proceedings - 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019, Gold Coast, QLD (2019) [E1]
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2019 |
Kayesh H, Islam MS, Wang J, 'Event causality detection in tweets by context word extension and neural networks', Proceedings - 2019 20th International Conference on Parallel and Distributed Computing, Applications and Technologies, PDCAT 2019 (2019) Twitter has become a great source of user-generated information about events. Very often people report causal relationships between events in their tweets. Automatic detection of ... [more] Twitter has become a great source of user-generated information about events. Very often people report causal relationships between events in their tweets. Automatic detection of causality information in these events might play an important role in prescriptive event analytics. Existing approaches include both rule-based and data-driven supervised methods. However, it is challenging to identify event causality accurately using linguistic rules due to the unstructured nature and grammatical incorrectness of social media short text such as tweets. Also, it is difficult to develop a data-driven supervised method for event causality detection in tweets due to insufficient contextual information. This paper proposes a novel event context word extension technique based on background knowledge. To demonstrate the effectiveness of our event context word extension technique, we develop a feed-forward neural network based approach to detect event causality from tweets. Extensive experiments demonstrate the superiority of our approach.
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2018 |
Hashim-Jones J, Wang C, Islam MS, Stantic B, 'Interdependent Model for Point-of-Interest Recommendation via Social Networks', DATABASES THEORY AND APPLICATIONS, ADC 2018, AUSTRALIA, Gold Coast (2018) [E1]
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2017 |
Islam MS, Rahayu W, Liu C, Anwar T, Stantic B, 'Computing Influence of a Product through Uncertain Reverse Skyline', SSDBM 2017: 29TH INTERNATIONAL CONFERENCE ON SCIENTIFIC AND STATISTICAL DATABASE MANAGEMENT, Chicago, IL (2017) [E1]
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2016 |
Islam MS, Liu C, Li J, 'Efficient Answering of Why-Not Questions in Similar Graph Matching', 2016 32ND IEEE INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE), Helsinki, FINLAND (2016) [E1]
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2016 |
Islam MS, Liu C, Rahayu W, Anwar T, 'Q plus Tree: An Efficient Quad Tree based Data Indexing for Parallelizing Dynamic and Reverse Skylines', CIKM'16: PROCEEDINGS OF THE 2016 ACM CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, IUPUI, Indianapolis, IN (2016) [E1]
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2016 |
Anwar T, Liu C, Vu HL, Islam MS, 'Tracking the Evolution of Congestion in Dynamic Urban Road Networks', CIKM'16: PROCEEDINGS OF THE 2016 ACM CONFERENCE ON INFORMATION AND KNOWLEDGE MANAGEMENT, IUPUI, Indianapolis, IN (2016) [E1]
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Show 23 more conferences |
Grants and Funding
Summary
Number of grants | 9 |
---|---|
Total funding | $291,451 |
Click on a grant title below to expand the full details for that specific grant.
20235 grants / $139,243
Deep learning and Edge Computing for Compliance and Traceability in Agriculture Supply Chain and Logistics Operations$106,638
Deep learning and Edge Computing for Compliance and Traceability in Agriculture Supply Chain and Logistics Operations. |
Funding body: AusIndustry Innovations
Funding body | AusIndustry Innovations |
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Project Team | Francisco Oliveri, Elizabeth Chang, Saiful Islam, Ashley Jensen |
Scheme | Innovation Connections Business Researcher Placement |
Role | Lead |
Funding Start | 2023 |
Funding Finish | 2023 |
GNo | |
Type Of Funding | C2120 - Aust Commonwealth - Other |
Category | 2120 |
UON | N |
Developing and Validating a Data-Driven AI Algorithm for Rugby Collision Intensity$15,000
Funding body: The University of Newcastle
Funding body | The University of Newcastle |
---|---|
Project Team | Mitch Naughton, Dan Weaving, Saiful Islam |
Scheme | The University of Newcastle and The University of Waikato Partnership Seed Fund |
Role | Investigator |
Funding Start | 2023 |
Funding Finish | 2024 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
Start - up support$10,000
Funding body: College of Engineering, Science and Environment, University of Newcastle
Funding body | College of Engineering, Science and Environment, University of Newcastle |
---|---|
Project Team | Saiful Islam |
Scheme | Start-up support |
Role | Lead |
Funding Start | 2023 |
Funding Finish | 2023 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
WTUN Exchange Programme 2022 - 2023$3,855
Funding body: World Technology Universities Network
Funding body | World Technology Universities Network |
---|---|
Project Team | Saiful Islam |
Scheme | Word Technology Universities Network |
Role | Lead |
Funding Start | 2023 |
Funding Finish | 2024 |
GNo | |
Type Of Funding | External |
Category | EXTE |
UON | N |
Course Development Grant$3,750
Funding body: College of Engineering, Science and Environment, University of Newcastle
Funding body | College of Engineering, Science and Environment, University of Newcastle |
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Project Team | Saiful Islam and Philipp Rouast |
Scheme | Course Development Funding 2023 |
Role | Lead |
Funding Start | 2023 |
Funding Finish | 2023 |
GNo | |
Type Of Funding | Internal |
Category | INTE |
UON | N |
20221 grants / $35,000
Data61 Top-Up (Biprodip Pal): Decentralised Federated Learning for Field Robotics$35,000
Decentralised Federated Learning for Field Robotics
Funding body: CSIRO - Commonwealth Scientific and Industrial Research Organisation
Funding body | CSIRO - Commonwealth Scientific and Industrial Research Organisation |
---|---|
Project Team | Saiful Islam, Alan Liew |
Scheme | Postgraduate Scholarship |
Role | Lead |
Funding Start | 2022 |
Funding Finish | 2025 |
GNo | |
Type Of Funding | External |
Category | EXTE |
UON | N |
20211 grants / $92,500
Top-up Scholarship in Doctor of Philosophy$92,500
Media8 HDR Stipend Scholarship
Funding body: Media8 Pty. Ltd.
Funding body | Media8 Pty. Ltd. |
---|---|
Project Team | Saiful Islam, Mohammad Awrangjeb |
Scheme | Media8 Pty. Ltd. |
Role | Lead |
Funding Start | 2021 |
Funding Finish | 2025 |
GNo | |
Type Of Funding | External |
Category | EXTE |
UON | N |
20191 grants / $14,981
Prediction of the likelihood of Patient Readmission after Hospital Discharge$14,981
Collaborative Research - Griffith University and Healthcare Logic Pty. Ltd.
Funding body: Healthcare Logic Pty Ltd
Funding body | Healthcare Logic Pty Ltd |
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Project Team | Saiful Islam |
Scheme | Collaborative grant between Griffith University Australia and Health Care Logic Pty. Ltd. |
Role | Lead |
Funding Start | 2019 |
Funding Finish | 2021 |
GNo | |
Type Of Funding | External |
Category | EXTE |
UON | N |
20181 grants / $9,727
Framework for Computing Top-k Most Important Targets/Aspects from Tourism Opinions$9,727
New Researcher Grant in Griffith University
Funding body: Griffith University
Funding body | Griffith University |
---|---|
Project Team | Saiful Islam |
Scheme | Griffith University, Australia |
Role | Lead |
Funding Start | 2018 |
Funding Finish | 2018 |
GNo | |
Type Of Funding | External |
Category | EXTE |
UON | N |
Research Supervision
Number of supervisions
Current Supervision
Commenced | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2024 | PhD | Reliable IoT Attack Detection Using Artificial Metacognition and Deep Learning | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2024 | PhD | Ethical AI for Enhanced Health Insurance Risk Assessment and Decision-Making | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2024 | PhD | Next-Level Predictions: Transforming Tabular Data for High-Dimensional Precision | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2024 | Masters | Dynamic Auto-Retraining MLOps Framework for Big Data Predictive Models | M Philosophy(Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2023 | PhD | Classification and Fault Inspection of Powerline Components from Aerial Optical Imagery Using Deep Neural Networks | Computer Science, Griffith University | Co-Supervisor |
2023 | PhD | Deep Transformation of Tabular Categorical Data for Enhanced Predictive Analytics in Health Informatics | PhD (Computer Science), College of Engineering, Science and Environment, The University of Newcastle | Principal Supervisor |
2020 | PhD | Reliable Deep Learning for Internet of Things and Robot Teams | Computer Science, Griffith University | Principal Supervisor |
Past Supervision
Year | Level of Study | Research Title | Program | Supervisor Type |
---|---|---|---|---|
2023 | PhD | Compression Techniques for Reachability and Shortest Distance Queries over Large Graphs | Computer Science, Griffith University | Co-Supervisor |
2022 | PhD | Deep Learning for Causal Discovery in Texts | Computer Science, Griffith University | Principal Supervisor |
2021 | PhD | Reverse Nearest Neighbourhood Search in Spatial Databases | Computer Science, Monash University | Co-Supervisor |
2020 | PhD | A Secure and Efficient Communication Framework for Software-Defined Wireless Body Area Network | Computer Science, Griffith University | Principal Supervisor |
2019 | PhD | Finding Best Paths in Spatio-Textual Queries | Computer Science, Monash University | Co-Supervisor |
2018 | PhD | On Improving the Usability of Exploration over Semi-Structured Data | Computer Science, Swinburne University of Technology | Co-Supervisor |
Research Opportunities
Trustworthy and Dependable AI for Internet of Things and Cyber Physical Systems
Data is central to the success of data to decision (D2D) based systems. Every year, thousands, if not millions, of deep learning-based AI models are created to solve a wide range of problems. Model engineering has received far more attention than systematically engineering the data used to build an AI system. Furthermore, less research has been conducted to address the challenge of keeping a learned model relevant for constantly evolving data. Implementing trustworthy and dependable AI models is essential for the successful deployment of AI systems in practical applications, such as Internet of Things (IoTs) and Cyber Physical Systems (CPSs), in order to strike a balance between model and data engineering. This project will develop trustworthy and dependable AI models for IoTs and CPSs. Prerequisites: The student/intern needs to be familiar with deep learning and machine learning algorithms. Tensorflow, PyTorch, and fastText coding proficiency in Python is required.
Honours
School of Information and Physical Sciences
2/1/2023 - 31/12/2024
Contact
Doctor Saiful Islam
University of Newcastle
School of Information and Physical Sciences
saiful.islam@newcastle.edu.au
AI-based Calibration of Digital Twin Parameters to Track the Efficacy of Cyberphysical Systems
A digital twin is a digital representation of a real-world, cyber-physical system or process that acts as the system's practically identical digital counterpart for tasks like monitoring, testing, integration, and maintenance. As part of this project, theories and models for digital twins will be created. Additionally, AI-based algorithms will be created to track and manage the performance of real-world cyberphysical systems. Prerequisites: The student or intern needs to be familiar with deep learning and machine learning algorithms. Tensorflow, PyTorch, and fastText coding proficiency in Python is required.
Honours
School of Information and Physical Sciences
2/1/2023 - 31/12/2027
Contact
Doctor Saiful Islam
University of Newcastle
School of Information and Physical Sciences
saiful.islam@newcastle.edu.au
AI-Driven CSP Optimization for HTML Injection Attack Detection in Web Applications
HTML injection attacks are a common form of web application attacks that enable attackers to insert malicious code into a web page, potentially leading to a range of security vulnerabilities. Content Security Policy (CSP) is a security feature that allows web developers to control the sources of content that their web applications can load, helping to mitigate the risk of HTML injection attacks. However, despite CSP safeguards, an attacker can still inject malicious code into a web page. In this project, we will develop an innovative AI algorithm to learn attack patterns by training it on a dataset of benign and malicious HTML injection attacks. Specifically, we will create a novel graph-theoretic and graph neural network (GNN)-based approach to analyze web traffic patterns. This approach will help identify the most frequently requested content sources and recommend CSP policies that allow those sources while blocking others that are less frequently requested. In summary, the goal of this project is to develop an alert system that combines AI and CSP to help enhance the security of web applications. The system will automatically detect and prevent HTML injection attacks, while optimizing the CSP policies to improve their effectiveness. Pre-requisites: The student/intern needs to be familiar with deep learning and machine learning algorithms. Tensorflow, PyTorch, and fastText coding proficiency in Python is required.
Honours
School of Information and Physical Sciences
16/2/2023 - 31/12/2025
Contact
Doctor Saiful Islam
University of Newcastle
School of Information and Physical Sciences
saiful.islam@newcastle.edu.au
Uncertainty Calibration and Trustworthy AI Model Development
Thousands, if not millions, of deep learning-based AI models are created each year to solve a variety of problems. Model engineering has gained far more attention than data engineering, which is used to build an AI system. Furthermore, less research has been conducted to address the problem of keeping a learned model relevant in the face of constantly changing data. This project will look into the foundations of uncertainty in AI models. As part of the project, a solid theory will be developed to estimate and calibrate the uncertainty in AI models, as well as a framework or tools for trustworthy AI models. Prerequisites: The prospective student needs to be familiar with deep learning and machine learning algorithms. Tensorflow, PyTorch, and fastText coding proficiency in Python is required.
PHD
School of Information and Physical Sciences
2/1/2023 - 31/12/2027
Contact
Doctor Saiful Islam
University of Newcastle
School of Information and Physical Sciences
saiful.islam@newcastle.edu.au
Dr Saiful Islam
Position
Senior Lecturer
Data Science and Statistics
School of Information and Physical Sciences
College of Engineering, Science and Environment
Focus area
Data Science and Statistics
Contact Details
saiful.islam@newcastle.edu.au | |
Mobile | 0424422409 |
Office
Room | SR212 |
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Building | SR Building |
Location | Callaghan University Drive Callaghan, NSW 2308 Australia |