Acacia – The Smart Image Compressor

Today we are releasing Acacia – a machine learning enabled image compressor developed here in the School of Computer Science at the University of St Andrews. Acacia is the work of Oleksandr Murashko and Dr. John Thomson.


Acacia (Advanced Content-Adaptive Compressor of ImAges) is an image compression tool targeting at those who want the best compression under constrained energy or processing time scenarios – for instance a mobile device or a cloud image server. It allows users to target specific image quality or file size metrics when compressing an image with JPEG or WebP, with only minimal additional compression time. It does this by using machine learning to predict how an individual image will be compressed, and adjusts the aggressiveness of compression accordingly.

Acacia allows users to target compression to their file size or quality needs, significantly increasing the effectiveness of compression by adjusting to each individual image. It is available with a graphical interface, and with a CLI for batch processing.

Acacia is free and open source, runs on Windows, Linux and MacOS, and is available on Github as source, or as a Windows binary.

This software accompanies our paper, Predicting and Optimizing Image Compression, published in ACM Multimedia this week. The paper is available for free from John Thomson’s web site.

Funded PhD Research Studentships Closing Date 12th February

The School of Computer Science at the University of St Andrews has funding for students to undertake PhD research in any of the general research areas in the school:

We are looking for highly motivated research students with an interest in these exciting research areas. Our only requirements are that the proposed research would be good, we have staff to supervise it, and that you would be good at doing it. 

We have funded studentships, including industrial sponsored studentships, available for students interested in working towards a PhD. The studentships offer costs of fees and an annual tax-free maintenance stipend of about £14,057 per year for 3.5 years. Students should normally have or expect at least an upper-2nd class Honours degree or Masters degree in Computer Science or a related discipline.

For further information on how to apply, see our postgraduate web pages ( A non-exclusive list of potential PhD projects is provided at The closing date for applications is February 12th 2016 and we will make decisions on studentship allocation by March 4th 2016. Informal enquiries can be directed to or to potential supervisors.

The Results Delusion – Systems Seminar by John Thomson

Systems Seminar – by John Thomson

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The Results Delusion


It is often said that any subject which requires the word ‘science’ to be placed somewhere in its name, is unlikely to be very scientific. This is unfortunately far too true for systems research in general. Every systems conference, papers are presented which show significant speedups over previous approaches to problem X, but these improvements are rarely replicated in output from industry. Why? The unpalatable answer is that a significant amount of systems research is the result of self-delusion, bad science and, I suspect occasionally, fraud.

Standards of scientific rigour in CS often fall well below what would be taken for granted in other sciences – particularly with regard to measurement of results, statistical analysis and replicability of results. I would like to do something about this, and will be presenting the idea for a new CS journal, which focuses on this exact problem. Oh, and peer review is gone too! Pitfalls abound. Would love to hear your comments, objections and advice.

Event details

  • When: 27th March 2012 13:00 - 13:45
  • Where: Cole 1.33a
  • Format: Seminar