Biography
Dr Sunil Aryal is a Senior Lecturer in Data Science the School of Information Technology at Deakin University Australia. Prior to joining Deakin University in 2019, he was a lecturer at Federation University and a sessional lecturer at various institutions in Australia. Before moving to academia, He worked in industry for several years as a Software Developer and Data Engineer. He received his PhD and Master by Research degrees from Monash University Australia. His research interests are in the areas of Artificial Intelligence (AI), Machine Learning (ML) and Data Mining (DM). He is particularly interested in the application of AI/ML/DM models to solve real-world problems in applications such as Defence, National Intelligence, Engineering, Manufacturing, Healthcare and Education. Currently, he is working on making ML/DM algorithms robust and flexible to handle heterogenous, noisy and uncertain data in real-world problems. He is working on anomaly detection, clustering, kernel/similarity-based learning, ensemble methods, learning from heterogenous, noisy and limited/small data, reinforcement learning, natural language processing, computer vision, and remote sensing. He co-leads the Machine Learning for Decision Support (MLDS) Research Group at the Deakin University School of Information Technology at the Geelong Waurn Ponds campus. He has published over 49 papers in top-tier international venues in AI, ML and DM. He has secured over AUD 4 million in external research funding. His research is supported by US and Australia Defence Agencies, Australian Office of National Intelligence, Worksafe Victoria, Victorian State Department of Education and Training, and Technology Innovation Institute UAE.
Read more on Sunil's profileResearch interests
Data Mining and Machine Learning — Practical and Robust Data Mining, Similarity Measures, Classification, Clustering, Anomaly Detection, Ensemble-based and Random Methods, Learning from small subsamples of data, Learning from mixed (numeric and categorical) data, Explainable AI, Autonomous Systems, and Health Informatics
Affiliations
- Australian Computer Society [2008 - ]
- IEEE Computer Society [2014 - ]
- IEEE Young Professionals [2014 - ]
Teaching interests
Data Mining, Machine Learning, Artificial Intelligence, Database, Programming, Professional Practice, Placement and Internship, Capstone Projects
Units taught
SIT103 Data and Information Management
SIT223 Professional Practice in IT
SIT306 IT Internship
SIT740 Research & Development in IT
SIT790 Major Thesis
SIT750 Mastery of IT
SIT720 Machine Learning
SIT772 Database and Information Retrieval
Knowledge areas
Data Mining, Machine Learning, Artificial Intelligence and Health Informatics
Professional activities
- Fellow of the UK Higher Edication Academy (FHEA)
- Topic Editor for the MDPI Applied System Innovation (ASI) journal [2021 - ]
- PC Member - Conferences such as IJCAI, AAAI, ECML/PKDD, PAKDD, IJCNN and ICONIP, etc.
- Journal Reviewer - ACM Transactions on Knowledge Discovery from Data (TKDD), Journal of Artificial Intelligence Research (JAIR), IEEE Intelligent Systems
Research groups
Machine Learning for Decision Support (MLDS) Resaerch Group under the Machine Intelligence Lab and Centre for Data to Learning at Deakin School of IT.
Awards
- Deakin School of IT Research Award for Industry Engagement [2022]
- Deakin Faculty of Science, Enginering and Built Environment Teaching and Learning Award [2022]
- Deakin School of IT Research Award for Excellence in Early Career Research Performance [2021]
- Deakin School of IT Teaching and Learning Award for Excellence in unit leadership and supporting student learning [2021]
- Four student travel awards during PhD candidaure [2013-2016]
- Australian Postgraduate Award (APA) for PhD at Monash University [2013]
- Research student stipend for MIT (Research) at Monash University [2011]
- Research trainee scholarship by Katholieke University of Leuven, Belgium [2009]
- Dean’s award for outstanding academic achievement by University of Southern Queensland [2007]
Publications
Omnidirectional Video Super-Resolution Using Deep Learning
A Agrahari Baniya, T Lee, P Eklund, S Aryal
(2024), Vol. 26, pp. 540-554, IEEE Transactions on Multimedia, C1
Shine: A deep learning-based accessible parking management system
D Neupane, A Bhattarai, S Aryal, M Bouadjenek, U Seok, J Seok
(2024), Vol. 238, pp. 1-14, Expert Systems with Applications, Amsterdam, The Netherlands, C1
M Talukder, M Layek, M Kazi, M Uddin, S Aryal
(2024), Vol. 168, pp. 107789-107789, Computers in Biology and Medicine, United States, C1
Elastic step DQN: A novel multi-step algorithm to alleviate overestimation in Deep Q-Networks
A Ly, R Dazeley, P Vamplew, F Cruz, S Aryal
(2024), Vol. 576, pp. 1-13, Neurocomputing, Amsterdam, The Netherlands, C1
Priority based energy and load aware routing algorithms for SDN enabled data center network
M Pathan, M Muntaha, S Sharmin, S Saha, M Uddin, F Nur, S Aryal
(2024), Vol. 240, pp. 110166-110166, Computer Networks, C1
ML-CKDP: Machine learning-based chronic kidney disease prediction with smart web application
R Halder, M Uddin, M Uddin, S Aryal, S Saha, R Hossen, S Ahmed, M Rony, M Akter
(2024), Vol. 15, pp. 1-16, Journal of Pathology Informatics, Amsterdam, The Netherlands, C1
A Agrahari Baniya, T Lee, P Eklund, S Aryal
(2024), Vol. 5, SN Computer Science, C1
MLSTL-WSN: machine learning-based intrusion detection using SMOTETomek in WSNs
M Talukder, S Sharmin, A Uddin, M Islam, S Aryal
(2024), pp. 1-20, International Journal of Information Security, Berlin, Germany, C1
Detection of Anomalies and Explanation in Cybersecurity
D Samariya, J Ma, S Aryal, X Zhao
(2024), Vol. 1967, pp. 414-426, ICONIP 2023 : Proceedings of the 30th International Conference on Neural Information Processing, Changsha, China, E1
Overcoming weaknesses of density peak clustering using a data-dependent similarity measure
Z Rasool, S Aryal, M Bouadjenek, R Dazeley
(2023), Vol. 137, pp. 109287-109287, Pattern Recognition, C1
R Halder, M Uddin, M Uddin, S Aryal, M Islam, F Hossain, N Jahan, A Khraisat, A Alazab
(2023), Vol. 14, pp. 582-582, Genes, Switzerland, C1
Detection and explanation of anomalies in healthcare data
Durgesh Samariya, Jiangang Ma, Sunil Aryal, Xiaohui Zhao
(2023), Vol. 11, pp. 1-23, Health Information Science and Systems, Berlin, Germany, C1
A Novel Approach Utilizing Machine Learning for the Early Diagnosis of Alzheimer's Disease
Khandaker Uddin, Mir Alam, Jannat-E-Anawar, Md Uddin, Sunil Aryal
(2023), Vol. 1, pp. 882-898, Biomedical Materials and Devices, Berlin, Germany, C1
An efficient deep learning model to categorize brain tumor using reconstruction and fine-tuning
M Talukder, M Islam, M Uddin, A Akhter, M Pramanik, S Aryal, M Almoyad, K Hasan, M Moni
(2023), Vol. 230, pp. 120534-120534, Expert Systems with Applications, C1
Online Video Super-resolution using Information Replenishing Unidirectional Recurrent Model
A Agrahari Baniya, T Lee, P Eklund, S Aryal, A Robles-Kelly
(2023), Vol. 546, Neurocomputing, C1
Machine Learning Based Diabetes Detection Model for False Negative Reduction
Md Uddin, Md Islam, Md Talukder, Md Hossain, Arnisha Akhter, Sunil Aryal, Maisha Muntaha
(2023), pp. 1-17, Biomedical Materials and Devices, Berlin, Germany, C1
A robust and clinically applicable deep learning model for early detection of Alzheimer's
M Rana, M Islam, M Talukder, M Uddin, S Aryal, N Alotaibi, S Alyami, K Hasan, M Moni
(2023), IET Image Processing, C1
Rabea Khatun, Maksuda Akter, Md Islam, Md Uddin, Md Talukder, Joarder Kamruzzaman, A Azad, Bikash Paul, Muhammad Almoyad, Sunil Aryal, Mohammad Moni
(2023), Vol. 14, pp. 1-24, Genes, Basel, Switzerland, C1
M Islam, M Uddin, S Aryal, G Stea
(2023), Vol. 78, Journal of Information Security and Applications, C1
An ensemble machine learning based bank loan approval predictions system with a smart application
N Uddin, M Uddin Ahamed, M Uddin, M Islam, M Talukder, S Aryal
(2023), Vol. 4, pp. 327-339, International Journal of Cognitive Computing in Engineering, C1
M Rahman, J Chakma, A Momin, S Islam, M Uddin, M Islam, S Aryal
(2023), Vol. 23, pp. 8472-8472, Sensors (Basel, Switzerland), Switzerland, C1
Abida Sultana, Sadia Mitu, Md Pathan, Mohammed Uddin, Md Uddin, Sunil Aryal
(2023), Vol. 107, pp. 1-12, Computational Biology and Chemistry, Amsterdam, The Netherlands, C1
An overview of Eulerian video motion magnification methods
A Ahmed, M Abdelrazek, S Aryal, T Nguyen
(2023), Vol. 117, pp. 145-163, Computers and Graphics (Pergamon), C1
Elastic step DDPG: Multi-step reinforcement learning for improved sample efficiency
A Ly, R Dazeley, P Vamplew, F Cruz, S Aryal
(2023), Vol. 2023-June, pp. 1-6, IJCNN 2023 : Proceedings of the International Joint Conference on Neural Networks, Gold Coast, Queensland, E1
Data-dependent and Scale-Invariant Kernel for Support Vector Machine Classification
Vinayaka Malgi, Sunil Aryal, Zafaryab Rasool, David Tay
(2023), Vol. LNAI,volume 13935, pp. 171-182, PAKDD 2023: Advances in Knowledge Discovery and Data Mining, Osaka, Japan, E1
Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest
X Song, S Aryal, K Ting, Z Liu, B He
(2022), Vol. 60, IEEE Transactions on Geoscience and Remote Sensing, C1
Jagannath Aryal, Chiranjibi Sitaula, Sunil Aryal
(2022), Vol. 11, pp. 1-21, Land, Basel, Switzerland, C1
Thanh Nguyen, Mohamed Abdelrazek, Dung Nguyen, Sunil Aryal, Duc Nguyen, Sandeep Reddy, Quoc Nguyen, Amin Khatami, Thanh Nguyen, Edbert Hsu, Samuel Yang
(2022), Vol. 8, pp. 1-12, Machine Learning with Applications, Amsterdam, The Netherlands, C1
K Santosh, Nicholas Rasmussen, Muntasir Mamun, Sunil Aryal
(2022), Vol. 8, pp. 1-20, PeerJ Computer Science, London, Eng., C1
STIFS: Spatio-Temporal Input Frame Selection for Learning-based Video Super-Resolution Models
A Agrahari Baniya, T Lee, P Eklund, S Aryal
(2022), SIGMAP 2022 : Proceedings of the Signal Processing and Multimedia Applications conference 2022, Lisbon, Portugal, E1
sGrid++: Revising Simple Grid Based Density Estimator for Mining Outlying Aspect
D Samariya, J Ma, S Aryal
(2022), Vol. 13724, pp. 194-208, WISE 2022 : Proceedings of the Web Information Systems Engineering 2022 international conference, Biarritz, France, E1
usfAD: a robust anomaly detector based on unsupervised stochastic forest
S Aryal, K Santosh, R Dazeley
(2021), Vol. 12, pp. 1137-1150, International Journal of Machine Learning and Cybernetics, C1
Vector representation based on a supervised codebook for Nepali documents classification
C Sitaula, A Basnet, S Aryal
(2021), Vol. 7, pp. 1-18, PeerJ Computer Science, United States, C1
Levels of explainable artificial intelligence for human-aligned conversational explanations
R Dazeley, P Vamplew, C Foale, C Young, S Aryal, F Cruz
(2021), Vol. 299, Artificial Intelligence, C1
Scene image representation by foreground, background and hybrid features
C Sitaula, Y Xiang, S Aryal, X Lu
(2021), Vol. 182, Expert Systems with Applications, C1
New bag of deep visual words based features to classify chest x-ray images for COVID-19 diagnosis
C Sitaula, S Aryal
(2021), Vol. 9, Health Information Science and Systems, England, C1
Content and context features for scene image representation
C Sitaula, S Aryal, Y Xiang, A Basnet, X Lu
(2021), Vol. 232, Knowledge-Based Systems, C1
C Sitaula, T Shahi, S Aryal, F Marzbanrad
(2021), Vol. 11, Scientific Reports, England, C1
Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data
Sunil Aryal, Jonathan Wells
(2021), Vol. 12975, pp. 687-702, ECML PKDD 2021 : Machine Learning and Knowledge Discovery in Databases. Research Track, Bilbao, Spain, E1
SPAD+: An Improved Probabilistic Anomaly Detector based on One-dimensional Histograms
Sunil Aryal, Arbind Agrahari Baniya, Muhammad Razzak, K Santosh
(2021), pp. 1-7, IJCNN 2021 : Proceedings of the International Joint Conference on Neural Networks, Shenzhen, China, E1
Sunil Aryal, Kai Ting, Takashi Washio, Gholamreza Haffari
(2020), Vol. 34, pp. 124-162, Data mining and knowledge discovery, Cham, Switzerland, C1
Jonathan Wells, Sunil Aryal, Kai Ting
(2020), Vol. 62, pp. 3203-3216, Knowledge and Information Systems, Berlin, Germany, C1
Fusion of whole and part features for the classification of histopathological image of breast tissue
C Sitaula, S Aryal
(2020), Vol. 8, Health Information Science and Systems, England, C1
HDF: Hybrid deep features for scene image representation
Chiranjibi Sitaula, Yong Xiang, Anish Basnet, Sunil Aryal, Xuequan Lu
(2020), pp. 1-8, IJCNN 2020 : Proceedings of the 2020 International Joint Conference on Neural Networks, Online from Glasgow, Scotland, E1
A New Effective and Efficient Measure for Outlying Aspect Mining
Durgesh Samariya, Sunil Aryal, Kai Ting, Jiangang Ma
(2020), Vol. 12343, pp. 463-474, WISE 2020 : Proceedings of the 2020 International Conference on Web Information Systems Engineering, Amsterdam, The Netherlands, E1
Indoor image representation by high-level semantic features
C Sitaula, Y Xiang, Y Zhang, X Lu, S Aryal
(2019), Vol. 7, pp. 84967-84979, IEEE access, Piscataway, N.J., C1
Unsupervised deep features for privacy image classification
C Sitaula, Y Xiang, S Aryal, X Lu
(2019), Vol. 11854, pp. 404-415, Image and video technology : 9th Pacific-Rim Symposium, PSIVT 2019, Sydney, NSW, Australia, November 18-22, 2019, Proceedings, Sydney, N.S.W., E1
Tag-based semantic features for scene image classification
C Sitaula, Y Xiang, A Basnet, S Aryal, X Lu
(2019), Vol. 11955, pp. 90-102, ICONIP 2019 : Proceedings of the 26th International Conference on Neural Information Processing of the Asia-Pacific Neural Network Society 2019, Sydney, N.S.W., E1
A novel data pre-processing technique robust to units and scales of measurement
Arbind Baniya, Sunil Aryal, K Santosh
(2019), Vol. 16, pp. 1-8, Special Issue of the Australian Journal of Intelligent Information Processing Systems: 26th International Conference on Neural Information Processing, Sydney, New South Wales, E1
Modeling neurocognitive reaction time with gamma distribution
Meena Santhanagopalan, Madhu Chetty, Cameron Foale, Sunil Aryal, Britt Klein
(2018), pp. 1-10, ACSW '18: Proceedings of the Australasian Computer Science Week Multiconference, Brisbane, Qld., E1-1
Anomaly detection technique robust to units and scales of measurement
Sunil Aryal
(2018), Vol. 10937, pp. 589-601, PAKDD 2018: Pacific-Asia Conference on Advances in Knowledge Discovery and Data Mining, Melbourne, Victoria, E1-1
Relevance of frequency of heart-rate peaks as indicator of 'biological' stress level
Meena Santhanagopalan, Madhu Chetty, Cameron Foale, Sunil Aryal, Britt Klein
(2018), Vol. 11307, pp. 598-609, ICONIP 2018: International Conference on Neural Information Processing, Siem Reap, Cambodia, E1-1
Image clustering using a similarity measure incorporating human perception
H Shojanazeri, S Aryal, S Teng, D Zhang, G Lu
(2018), pp. 1-6, IVCNZ 2018 : International Conference on Image and Vision Computing New Zealand, Auckland, New Zealand, E1-1
A novel perceptual dissimilarity measure for image retrieval
H Shojanazeri, D Zhang, S Teng, S Aryal, G Lu
(2018), pp. 1-6, IVCNZ 2018 : International Conference on Image and Vision Computing New Zealand, Auckland, New Zealand, E1-1
Application of e-government principles in anti-corruption framework
Arjun Neupane, Jeffrey Soar, Kishor Vaidya, Sunil Aryal
(2017), pp. 56-74, Digital Governance and E-Government Principles Applied to Public Procurement, Hershey, Pa., B1-1
Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors
K Ting, T Washio, J Wells, S Aryal
(2017), Vol. 106, pp. 55-91, Machine Learning, C1-1
Data-dependent dissimilarity measure: an effective alternative to geometric distance measures
S Aryal, K Ting, T Washio, G Haffari
(2017), Vol. 53, pp. 479-506, Knowledge and Information Systems, C1-1
A generic ensemble approach to estimate multidimensional likelihood in bayesian classifier learning
Sunil Aryal, Kai Ting
(2016), Vol. 32, pp. 458-479, Computational intelligence, Chichester, Eng., C1-1
Revisiting attribute independence assumption in probabilistic unsupervised anomaly detection
Sunil Aryal, Kai Ting, Gholamreza Haffari
(2016), Vol. 9650, pp. 73-86, PAISI 2016 : Proceedings of the 11th Pacific Asia Workshop on Intelligence and Security Informatics 2016, Auckland, N.Z., E1-1
The potential for ICT tools to promote public participation in fighting corruption
A Neupane, J Soar, K Vaidya, S Aryal
(2015), Vol. 4, pp. 2291-2307, Public affairs and administration: concepts, methodologies, tools, and applications, Hershey, Pa., B1-1
Beyond tf-idf and cosine distance in documents dissimilarity measure
Sunil Aryal, Kai Ting, Gholamreza Haffari, Takashi Washio
(2015), Vol. 9460, pp. 400-406, AIRS 2015 : Information Retrieval Technology: Proceedings of the 11th Asia Information Retrieval Societies Conference, Brisbane, Queensland, E1-1
The potential for ICT tools to promote public participation in fighting corruption
Arjun Neupane, Jeffrey Soar, Kishor Vaidya, Sunil Aryal
(2014), pp. 175-191, Human Rights and the Impact of ICT in the Public Sphere: Participation, Democracy, and Political Autonomy, Hershey, Pa., B1-1
Mp-dissimilarity: a data dependent dissimilarity measure
S Aryal, K Ting, G Haffari, T Washio
(2014), pp. 707-712, ICDM 2014 : Proceedings of the 14th IEEE International Conference on Data Mining 2014, Shenzhen, China, E1-1
Improving iForest with relative mass
Sunil Aryal, Kai Ting, Jonathan Wells, Takashi Washio
(2014), Vol. 8444, pp. 510-521, PAKDD 2014 : Proceedings of the 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining, Tainan, Taiwan, E1-1
DEMass: a new density estimator for big data
Kai Ting, Takashi Washio, Jonathan Wells, Fei Liu, Sunil Aryal
(2013), Vol. 35, pp. 493-524, Knowledge and information systems, Berlin, Germany, C1-1
MassBayes: a new generative classifier with multi-dimensional likelihood estimation
Sunil Aryal, Kai Ting
(2013), Vol. 7818, pp. 136-148, PAKDD 2013 : Proceedings of the 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining 2013, Gold Coast, Qld., E1-1
Funded Projects at Deakin
Other Public Sector Funding
Ensemble Learning for Outlier Detection.
Dr Sunil Aryal
DSTO contract
- 2021: $5,000
- 2020: $15,000
Modeling Adversary Intent Using Multiobjective Reinforcement Learning.
Prof Richard Dazeley, Dr Sunil Aryal
DSTO Grant - Research - Defence Science & Technology Organisation
- 2021: $53,728
A competency-aware multi-agent framework for human-machine teams in adversarial environments.
Prof Richard Dazeley, Dr Sunil Aryal, A/Prof Tim Wilkin
DSTO Grant - Research - Defence Science & Technology Organisation
- 2022: $26,118
- 2021: $125,124
Utilizing Extractive - Abstractive Summarization for Understanding the Narrative of Social Media Users from Multimodal Data.
Dr Imran Razzak, Dr Mohamed Reda Bouadjenek, Dr Sunil Aryal
The Office of National Intelligence
- 2022: $5,000
- 2021: $15,000
Application of Generic Actual Argument Model to represent complex decisions and generate narratives.
Prof Richard Dazeley, Dr Sunil Aryal, Dr Bahadorreza Ofoghi, Prof John Yearwood
Department of Defence
- 2022: $30,000
Design and delivery of a Graduate Certificate of Secondary Digital Technologies.
A/Prof Julianne Lynch, Prof Andrew Cain, Dr Jo Raphael, Dr George Aranda, Dr Sunil Aryal, A/Prof Chathu Ranaweera, Dr Carly Sawatzki, A/Prof Matthew Thomas, Dr Guy Wood-Bradley, A/Prof Glenn Auld, Dr John Cripps Clark, Prof Linda Hobbs
DETVic Grant - Research - Department of Education and Training Victoria
- 2024: $101,948
- 2023: $529,906
Industry and Other Funding
Developing robust framework for practical data mining.
Dr Sunil Aryal
Asian Office of Aerospace Research and Development
- 2022: $76,207
- 2021: $70,214
- 2020: $70,828
Machine Learning in Heterogeneous Data from Multiple Sources
Dr Sunil Aryal, Dr Mohamed Reda Bouadjenek
Air Force Office of Scientific Research United States of America
- 2023: $228,919
Contributions to Edge and Multimodal Machine Learning.
Dr Mohamed Reda Bouadjenek, Dr Sunil Aryal, Dr Muna Al-Hawawreh
Technology Innovation Institute - Sole Proprietorship LLC
- 2023: $66,697
- 2022: $162,113
Empowering Agents with Human Feedback: Integrating Implicit and Explicit Signals in Deep Reinforcement Learning
Dr Bahareh Nakisa, Dr Naim Rastgoo, Prof Richard Dazeley, Dr Sunil Aryal
Asian Office of Aerospace Research and Development
- 2023: $256,742
Intelligent Table Tennis Match Analysis: Automated Insights Extraction through Machine Learning and Computer Vision.
Dr Sunil Aryal, Dr Bahareh Nakisa, Prof Richard Dazeley
Table Tennis Australia Ltd
- 2023: $20,000
SummerTech Live Program 2024
Dr Mohamed Reda Bouadjenek, Dr Sunil Aryal, Dr Michael Hobbs, Dr Anh Dinh, Dr Anuroop Gaddam, Dr Muna Al-Hawawreh, Dr Aaron Spence, Dr Imali Dias
Victorian Chamber of Commerce and Industry
- 2024: $77,500
- 2023: $27,500
Supervisions
Arbind Agrahari Baniya
Thesis entitled: Super-Resolution of Conventional and Emerging Videos Using Deep Learning
Doctor of Philosophy (Information Technology), School of Information Technology
Chiranjibi Sitaula
Thesis entitled: Developing New Image Features for Scene Image Classification
Doctor of Philosophy (Information Technology), School of Information Technology