Profile image of Sunil Aryal

Dr Sunil Aryal

STAFF PROFILE

Position

Lecturer in Information Technology

Faculty

Faculty of Sci Eng & Built Env

Department

School of Info Technology

Campus

Geelong Waurn Ponds Campus

Qualifications

Doctor of Philosophy, Monash University, 2017
Master of Information Technology, Monash University, 2013

Biography

My research interests are in the areas of data mining and machine learning, particularly in their applications to solve real-world problems in defence, intelligence, cybersecurity, and healthcare. I work in similarity measures, anomaly detection, clustering, classification, ensemble learning, learning from small subsamples of data, and robust and explainable machine learning. I received my PhD (Data Mining) from Monash University in 2017. I have published more than 30 scientific papers in top tier conferences and journals in the field of data mining and machine learning. I have been a named investigator on research grants and contracts of over $1.9 million, where I am the lead (sole) CI in two of those. My research is supported by the US Airforce Office of Scientific Research (AFOSR) and Office of Naval Research (ONR) Global; and Australian Office of National Intelligence (ONI) and Defence Science and Technology (DST) Group. I am actively collaborating with researchers at other universities in Australia, USA, China and Japan. I am serving as a topic editor in the MDPI Applied System Innovation (ASI) journal. I regularly review research articles and papers for top-tier journals and conferences. I have supervised one PhD and eight master’s thesis students to completion and am currently supervising two PhD students and two master by research student. Before coming to academia and research, I worked as a software developer and data engineer for four years.

Read more on Sunil's profile

Research 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

SIT223 Professional Practice in IT

SIT306 IT Internship

SIT740 Research & Development in IT

SIT790 Major Thesis

SIT750 Mastery of IT

SIT720 Machine Learning

SIT772/SIT103 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

Smart Data Networks Lab and Machine Intelligence Lab under the Centre for Data to Learning at Deakin School of IT. 

Awards

  • 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

Filter by

2021

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, San Diego, Calif., C1

journal article

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, pp. 1-29, Artificial Intelligence, Amsterdam, The Netherlands, C1

journal article

Scene image representation by foreground, background and hybrid features

Chiranjibi Sitaula, Yong Xiang, Sunil Aryal, Xuequan Lu

(2021), Vol. 182, pp. 1-10, Expert systems with applications, Amsterdam, The Netherlands, C1

journal article

New bag of deep visual words based features to classify chest x-ray images for COVID-19 diagnosis

Chiranjibi Sitaula, Sunil Aryal

(2021), Vol. 9, pp. 1-12, Health information science and systems, Cham, Switzerland, C1

journal article

Spectral-Spatial Anomaly Detection of Hyperspectral Data Based on Improved Isolation Forest

Xiangyu Song, Sunil Aryal, Kai Ting, Zhen Liu, Bin He

(2021), pp. 1-16, IEEE Transactions on Geoscience and Remote Sensing, Piscataway, N.J., C1

journal article

Content and context features for scene image representation

Chiranjibi Sitaula, Sunil Aryal, Yong Xiang, Anish Basnet, Xuequan Lu

(2021), Vol. 232, pp. 1-12, Knowledge-Based Systems, Amsterdam, The Netherlands, C1

journal article

Ensemble of Local Decision Trees for Anomaly Detection in Mixed Data

Sunil Aryal, Jonathan Wells

(2021), Vol. 12975, pp. 687-702, Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2021, Bilbao, Spain, E1

conference

SPAD+: An Improved Probabilistic Anomaly Detector based on One-dimensional Histograms

Sunil Aryal, Arbind Agrahari Baniya, Muhammad Razzak, K Santosh

(2021), 2021 International Joint Conference on Neural Networks (IJCNN), Shenzhen, China, E1

conference
2020

A comparative study of data-dependent approaches without learning in measuring similarities of data objects

Sunil Aryal, Kai Ting, Takashi Washio, Gholamreza Haffari

(2020), Vol. 34, pp. 124-162, Data mining and knowledge discovery, Cham, Switzerland, C1

journal article

Simple supervised dissimilarity measure: Bolstering iForest-induced similarity with class information without learning

Jonathan Wells, Sunil Aryal, Kai Ting

(2020), Vol. 62, pp. 3203-3216, Knowledge and Information Systems, Berlin, Germany, C1

journal article

Fusion of whole and part features for the classification of histopathological image of breast tissue

Chiranjibi Sitaula, Sunil Aryal

(2020), Vol. 8, pp. 1-12, Health Information Science and Systems, New York, N.Y., C1

journal article

usfAD: a robust anomaly detector based on unsupervised stochastic forest

S Aryal, K Santosh, R Dazeley

(2020), pp. 1-14, International journal of machine learning and cybernetics, Cham, Switzerland, C1

journal article

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

conference

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

conference
2019

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

journal article

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

conference

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

conference

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

conference
2018

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

conference

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

conference

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

conference

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

conference

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

conference
2017

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

book chapter

Defying the gravity of learning curve: a characteristic of nearest neighbour anomaly detectors

Kai Ting, Takashi Washio, Jonathan Wells, Sunil Aryal

(2017), Vol. 106, pp. 55-91, Machine learning, New York, N.Y., C1-1

journal article

Data-dependent dissimilarity measure: an effective alternative to geometric distance measures

Sunil Aryal, Kai Ting, Takashi Washio, Gholamreza Haffari

(2017), Vol. 53, pp. 479-506, Knowledge and information systems, New York, N.Y., C1-1

journal article
2016

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

journal article

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

conference
2015

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

book chapter

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

conference
2014

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

book chapter

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

conference

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

conference
2013

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

journal article

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

conference

Funded Projects at Deakin

Other Public Sector Funding

Ensemble Learning for Outlier Detection.

Dr Sunil Aryal

  • 2021: $5,000
  • 2020: $15,000

Modeling Adversary Intent Using Multiobjective Reinforcement Learning.

A/Prof Richard Dazeley, Dr Sunil Aryal

  • 2021: $53,728

A competency-aware multi-agent framework for human-machine teams in adversarial environments.

A/Prof Richard Dazeley, Dr Sunil Aryal, A/Prof Tim Wilkin

  • 2021: $115,124

Industry and Other Funding

Developing robust framework for practical data mining.

Dr Sunil Aryal

  • 2021: $70,214
  • 2020: $70,828

Supervisions

Associate Supervisor
2021

Chiranjibi Sitaula

Thesis entitled: Developing New Image Features for Scene Image Classification

Doctor of Philosophy (Information Technology), School of Information Technology