My research interests are focussed on Data Mining, Machine Learning and Data Analytics. I have been conducting research in this area since 1997 (prior to this my research interests were in AI of which machine learning can be argued to be a sub-set). Current work is directed at: (i) Big Data, (ii) the application of data mining in the context of unusual data sets, (iii) graph and network data sets, (iv) ontology learning and (v) data analytics over encrypted data. More specificxally:

1. Big Data Analytics: Data mining and visualisation in the context of Big Data Analytics (UOL Big Data SIG).
2. Retina Image Mining: Classification of 2D and 3D retina image sets to support screening programmes for conditions such as Age-related Macular Degeneration (AMD) and Diabetic Retinopathy (DR).
3. MRI Scan Mining: Classification of 2D and 3D MRI brain scan data according to particular objects that appear within such data (corpus callosum, ventricles, etc.) so as to identify conditions such as epilepsy and handedness.
4. Satellite Image Mining: Objective is to use image minimg techniques to automatically collect sensus data from satellite imagery.
5. Multi Agent Data Mining (MADM), or Agent Enriched Data Mining (AEDM): The creation of a generic MAS (Multi-Agent System) platforms for distributed data mining, both as a research tool and to support applied data mining.
6. Trend Mining and Temporal data mining: Two Applications: (i) trend analysis within patient medical records and (ii) change point detection in animal movement databases (such as DEFRA's cattle movement database).
7. Brand Reputation Mining: The use of sentiment mining techniques to to identify the "polarity" of opinions expressed within electronic media with respect to particular companies and institutions.
8. Client-Customer Matching: The use of data mining techniques to for B2B customer-client matching.
9. Web mining and Web Usage Mining: Particularly the identification of WWW site boundaries using data mining techniques.
10. Text Mining: Generic text mining algorithms that are independent of the language that text base documents are written in, and rule induction with negation for text mining with dynamic rule refinement.
11. Questionnaire Mining: The application of data mining algorithms, especially text mining algorithms, to automatically extract information from the free text element of questionnaire data.
12. Data mining supported argumentation: Instead of using a knowledge base to support argumentation work is directed at using classification techniques to support the argumentation process.
13. Graph Mining: All types of graph mining including: (i) weighted graph mining, (ii) distributed graph mining, (iii) large scale graph mining and (iv) applied graph mining.
14. Secure Data Analytics: The usage homomorphic and order preserving encrypted schemes for data analytics purposes.
15. Ontology Learning: The proposes of learning ontologies from encrypted data.
16. Time series Analys: Especially the analysis of PCG sound waves.
17. Applied Data Mining: The broad application of data mining techniques in the context of large, challenging and unusual datasets.

Flyers for download (pdf), 2009-2013

	I am very pleased to have originated the UK KDD (Knowledge Discovery in Data) symposium series: UK KDD Symposium (UKKDD'14), Wednesday 16 June 2014, BCS Headquarters, London. UK KDD Symposium (UKKDD'11), Friday 23 September 2011, BCS Headquarters, London. UK KDD Symposium (UKKDD'09), Wednesday 22 April 2009, University of Salford. UK KDD Symposium (UKKDD'08), Wednesday 16 April 2008, University of Bristol. UK KDD Symposium (UKKDD'07), Wednesday 25 April 2007, University of Kent. Association Rule Mining in The Wider Context of Text, Images and Graphs presentation slides. UK KDD Symposium (UKKDD'06), Wednesday 26 April 2006, UEA. UK KDD Symposium (UKKDD'05), Wednesday 6 April 2005.
	I am also very pleased to have presented the Cuba-UK (Liverpool) School of data Mining, a two week seminar series held in Havana, Cuba, in January 2007.
	Big Data: Big Data share point homepage.
	I am (or have been) a member of a great many Data Mining Conference (workshops and symposia) programme committees. I have been area chair for IEEE ICDM (one of the top, if not the top, conference in my field) for the last four years (2014, 2015, 2916 and 2017) and am a Senor Programme Committee member for IEEE Big Data 2017. More specifically: KDH-2019: The 4th International Workshop on Knowledge Discovery in Healthcare Data, ECML PKDD 17 (Senor Programme Committee member), IEEE ICDM'17 (Area Chair), AI'17, ICCBDC'17 (Programme Chair), AI Applications in Law (co-chair), ECML PKDD 16, IEEE ICDM'16 (Area Chair), IEEE Big Data 16, AI'16, IEEE ICDM'15 (Area Chair), IEEE Big Data 15, ECML PKDD 15, DaWak'15, AI'15, IEEE ICDM'14 (Area Chair), IEEE Big Data 14, ECML PKDD 14, ADMI'14 (Co-Chair), BigData'14, DaWak'14, AI'14, ADMA, DaWaK'13, IEEE ICDM'13, IEEE Big Data 13, AI'13, DMO'12 (Data Mining and Optimisation), ECML/PKDD'12, DaWaK'12, PAKDD'12, AI'12, ECML/PKDD'11, ADMI'11, DaWaK'11, AI'11, ICCBR'11 Workshop 6: Argumentation and Case Based Reasoning, ADMA'10, AI'10, DaWaK'10, IEEE ICDM'10 (Admin), 6th IFIP Intelligent Information Processing Conference, ibia ICDM'10, SIGKDD'09 (Admin), IEEE ICDM'09, ADMA'09, DaWaK'09, DMIN'09, IEEE ICDM'08, IEEE Workshop on Data Mining and AI (DMAI 2008), ADMA'08, UKKDD'08, DaWaK'08, DMIN'08, DEXA'08, ibia ICDM'08, IEEE ICDM'07, DMIN'07, DEXA'07, DaWak'07, ADMA'07, UKKDD'07, IADIS European Conference on Data Mining, IEEE ICDM'06, PMKD'06 Workshop, DMIN'06, DaWak'06, UKKDD'06, DEXA'06, IEEE ICDM'05, UKKDD'05, PMKD'05 Workshop (Philosophies and Methodologies for Knowledge Discovery).
	I am a member of IFIP WG12.2: Machine Learning and Data Mining.
	Opportunities for KDD research (and potential PhD projects).
	Notes on many aspects of KDD (restricted access).

RESEARCH IN ARTIFICIAL INTELLIGENCE

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I have also spent many years (starting with my PhD. in 1986!) working in the field of Artificial Intelligence (AI). Activities include:

	BCS-SGAI: (from 1998 to 2009) I was a committee member of the SGAI --- Specialist Group on Artificial Intelligence (Formerly SGES). I am still on the programme committee for the AI series of conferences.
	Expert Update: Editorship (1998-2005) of Expert Update (see below for sample covers), see also.
	BCS-SGAI Annual Conference: Conf. Chair ES'99, ES'00 and ES'02; Dep. Conf. Chair ES'98, Tech. Prog. Chair ES'2001 and AI2003; Dep. Tech. Prog. Chair AI2004, AI2005, AI2006, AI2007, AI2008, AI2009.
	FAIRS: Forum for AI Research Students: FAIRS'07, FAIRS'08.

1. Invited Talk 3rd International Conference on Cloud and Big Data Computing (ICCBDC 2019), Oxford, (28-30 August 2019).
2. The Discovery of Knowledge in mage Data: A Study in Automated Population Estimation Using The Google Static Maps Service, Keynote at The British Computer Society's AI Conference (AI'17), Cambridge (14 December 2017).
3. A Brief History of AI and Law, Presentation Application of AI and Law workshop at The British Computer Society's AI Conference (AI'17), Cambridge (12 December 2017).
4. PhDs in Computer Science, presented at Fairs, Monday 10 December 2017.
5. Image Representation for Image Mining: A Study Focusing on Census Prediction using Satellite Image Data, Keynote at International Conference on Cloud and Big Data Computing (ICCBDC), London (18-20 September 2017).
6. Census Data Collection From Satellite Images: A Study in Image Mining, Keynote at ICITR'16, Columbo, Sri Lanka (Thursday 15 December 2016).
7. Mining Satellite Images for Census Data Collection: A Study Using the Google Static Maps Service, Keynote at IC3K, Porto, Portugal (Friday 11 November 2016).
8. Knowledge Discovery in Image Data: A Practitioners View, Presented at the Big Data Workshop hosted by IIT Colombo, Sri-Lanka (Thursday 12 May 2016).
9. The Application of Knowledge Discovery to Medical Image Data: A Practitioners View, keynote presentation at 2015 International Conference on Fuzzy Systems and data Mining (FSDM’15), Shanghai, China (Saturday 5 December 2015).
10. The Practical Application of Knowledge Discovery to Image Data: A Practitioners View in The Context of Medical Image Diagnostics Invited seminar, University of Mauritius (Tuesday 16 June 2016).
11. The Practical Application of Knowledge Discovery to Image Data: A Practitioners View in The Context of Medical Image Mining, Presented at the joint 10th International Conference on Natural Computation (ICNC 2014) and 11th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2014), Xiamen, China (Tuesday 10 August 2014).
12. The Practical Application of Knowledge Discovery to Image Data: A Practitioners View in The Context of Medical Image Mining, presented at the 7th UK Knowledge and Discovery in Data (UKDDD'11) Symposium, Headquarters of the British Computer Society (BCS), London (Monday 16 June 2014).
13. Image Mining in The Medical Domain, presented at the 6th UK Knowledge and Discovery in Data (UKDDD'11) Symposium, Headquarters of the British Computer Society (BCS), London (Friday 23 September 2011).
14. Data Mining: A Gentle Introduction, presented to University of Liverpool Pre-sessional English cohort (Wednesday 17 August 2011).
15. PhDs in Computer Science, FAIRS, Cambridge (Monday 13 December 2010).
16. Data Mining in the Medical Domain: A Review of Some Current Work at The University of Liverpool, presented at The Liverpool Medical Imaging Network (LMI-Net) Ophthalmic Imaging Workshop: Imaging Analysis, Automated Grading and Analysis of large Datasets (30 November 2010).
17. Data Mining: A Gentle Introduction, presented to University of Liverpool Pre-sessional English cohort (18 August 2010).
18. End to End Data Mining: The Next Challenge, presented at ASC, Imperial (Tuesday 21 April 2009).
19. Avoiding The Overfit and Prune Cycle in Classification Association Association Rule Mining, presented at University of Salford (Wednesday 14 March 2007). (Other related seminars/tutorials).
20. Getting a PhD (in Computer Science) - Doing Good Research, presented at BCS-SGAI (British Computer Society Specialist Group in AI) Student Event, Cambridge (Monday 10 December 2007).

The LUCS-KDD group has developed a great deal of data mining software of all kinds which we are happy to make available for non-commercial usage.

	Data generators: LUCS-KDD ARM data generator, Random image generator.
	Data preprocessing software: ARM LUCS-KDD-DN, CARM LUCS-KDD-DN.
	Data Sets: UCI-ML Discretised datasets, 20 NewsGroup Sample.
	ARM Software: Apriori-T demo (Demonstrator created for students taking on-line CS programmes), Apriori-T, Apriori-T GUI (Include DIC algorithm and negative boarder ARM approach), TFP (Total From Partial), TFP GUI (Includes FP-growth), FP-growth, Fuzzy ARM, Weighted Fuzzy ARM.
	CARM (and CRM) Software: TFPC, FOIL, PRM and CPAR, CMAR, CBA, Decision Trees.
	Text Mining: TFPC Text Miner (and text preprocessor).

Biographies.

List of my published research papers many of which are available for download.

UoL WWW Page.

Department WWW Page.

E-Mail:

<Coenen@liverpool.ac.uk>

Phone:

+44 151 795 4253

Fax:

+44 151 795 4235

Snail Mail:

Department of Computer Science
School of Electrical Engineering and Computer Science
Ashton Building, Ashton St.
University of Liverpool
P.O. Box 147, Liverpool L69 3BX
United Kingdom