• KY16 9SS

    United Kingdom

Accepting Postgraduate Research Students

PhD projects

Metric search; metric indexing; data linkage; genealogical population reconstruction; synthetic population generation; operating systems; unikernel operating systems

Personal profile

Profile Keywords

Metric search; metric indexing; data linkage; genealogical population reconstruction; synthetic population generation; operating systems; unikernel operating systems

Research overview

Distributed systems; Operating Systems; Programming Languages Similarity Search; Data Linkage

My roots are in the confluence of databases, operating systems, programming languages.
For many years this was manifested in work on persistent systems.
Recently I have been working on three areas which still relate to the above themes.

The Digitising Scotland project is creating a linked pedigree of the Scottish people from the mid 1800s.
This is being created from digitised birth, deaths and marriage records.
A group at St Andrews. of which I am a part, is engaged in linking these records.
Related to this we are creating a population simulator to provide ground truth for linkage experiments.
This work is largely being conducted by Tom Dalton who is supervised by Graham Kirby and myself.

As part of the Digitising Scotland project we have found many problems with current approaches to linkage.
To address these deficiencies I have been working with Richard Connor from Stirling on Similarity Search.
We are developing new Similarity Search algorithms over Metric Spaces to enable efficient search for linkage matching.

Lastly my interest in Operating Systems is continuing with Ward Jaradat (now at Adobe) and Jon Lewis.
We are working on a UniKernel operating system called Stardust which is capable of supporting Java applications.
The Stardust Unikernel is now operational and supports a full networking stack and Posix threads.

Academic/Professional Qualification

B.Sc., University of St Andrews; Ph.D., University of St Andrews; British Computer Society; The Association for Computing Machinery

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

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Collaborations and top research areas from the last five years

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  • Comparative Analysis of Relevance Feedback Techniques for Image Retrieval

    Vadicamo, L., Scotti, F., Dearle, A. & Connor, R., 2025, MultiMedia Modeling - 31st International Conference on Multimedia Modeling, MMM 2025, Proceedings. Ide, I., Kompatsiaris, I., Xu, C., Yanai, K., Chu, W.-T., Nitta, N., Riegler, M. & Yamasaki, T. (eds.). Springer Science and Business Media, p. 206-219 14 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 15520 LNCS).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Correlations of cross-entropy loss in machine learning

    Connor, R., Dearle, A., Claydon, B. & Vadicamo, L., 30 May 2024, In: Entropy. 26, 6, 16 p., 491.

    Research output: Contribution to journalArticlepeer-review

    Open Access
    File
  • Demonstrating the efficacy of polyadic queries

    Claydon, B., Connor, R., Dearle, A. & Vadicamo, L., 25 Oct 2024, Similarity search and applications: 17th International conference, SISAP 2024, Providence, RI, USA, November 4–6, 2024, proceedings. Chávez, E., Kimia, B., Lokoč, J., Patella, M. & Sedmidubsky, J. (eds.). Cham: Springer, p. 49-56 (Lectures notes in computer science; vol. 15268).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • Scalable polyadic queries

    Connor, R., Dearle, A. & Claydon, B., 25 Oct 2024, Similarity search and applications: 17th International conference, SISAP 2024, Providence, RI, USA, November 4–6, 2024, proceedings. Chávez, E., Kimia, B., Lokoč, J., Patella, M. & Sedmidubsky, J. (eds.). Cham: Springer, p. 57-64 (Lecture notes in computer science; vol. 15268).

    Research output: Chapter in Book/Report/Conference proceedingConference contribution

  • An approach to population linkage using graph databases

    Dearle, A., Kirby, G. N. C. & Akgun, O., 5 Jul 2023, p. 291-302. 12 p.

    Research output: Contribution to conferencePaperpeer-review

    Open Access