Job vacancies: Interdisciplinary Data Scientists

The Schools of Medicine and Computer Science are seeking to appoint three highly motivated data scientists with a passion for computer vision and deep learning, and specifically their application to medical imaging. The data scientists will be based in the Schools of Computer Science and Medicine at the University of St Andrews and will work on a national Innovate UK funded initiative to create a pan Scotland Industrial Centre for AI Research in Digital Diagnostics (iCAIRD).

The successful candidates will have the opportunity to work alongside and learn from clinicians, industrial experts from Philips Healthcare and academics to help develop artificial intelligence solutions for the automatic reporting of cancer diagnoses in endometrial and cervical cancer. The main duties of the role will involve being an active member of an interdisciplinary team of scientists to help develop deep learning algorithms, within industry standard guidelines, to analyse patient samples in a manner that allows rapid clinical transfer. This work will therefore have the opportunity to impact both patient welfare and relieve pathologist work burden.

Applicants should have experience in machine learning, demonstrable experience in computer programming languages and an interest in the medical applications of computer science. The candidates would benefit from a track record in scientific writing and working in interdisciplinary teams as well as experience in computer vision.

The posts are full time and over a period of 36 months.
Closing Date: 18 January 2019

Find out more about the vacancies further particulars on the recruitment website.

PhD viva success: Julian Petford

Congratulations to Julian Petford, who successfully defended his thesis today. He is pictured with internal examiner Professor Aaron Quigley and external examiner Dr Jason Alexander, from Lancaster University. Julian’s PhD research in Full Coverage Displays for Non-Immersive Applications was supervised by Dr Miguel Nacenta.

Image courtesy of Wendy Boyter

SRG Seminar: “Large-Scale Hierarchical k-means for Heterogeneous Many-Core Supercomputers” by Teng Yu

Event details

  • When: 1st November 2018 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Seminar, Talk
We present a novel design and implementation of k-means clustering algorithm targeting supercomputers with heterogeneous many-core processors. This work introduces a multi-level parallel partition approach that not only partitions by dataflow and centroid, but also by dimension. Our multi-level ($nkd$) approach unlocks the potential of the hierarchical parallelism in the SW26010 heterogeneous many-core processor and the system architecture of the supercomputer.
Our design is able to process large-scale clustering problems with up to 196,608 dimensions and over 160,000 targeting centroids, while maintaining high performance and high scalability, significantly improving the capability of k-means over previous approaches. The evaluation shows our implementation achieves performance of less than 18 seconds per iteration for a large-scale clustering case with 196,608 data dimensions and 2,000 centroids by applying 4,096 nodes (1,064,496 cores) in parallel, making k-means a more feasible solution for complex scenarios.
This work is to be presented in the International Conference for High Performance Computing, Networking, Storage, and Analysis (SC18).

SRG Seminar: “Using Metric Space Indexing for Complete and Efficient Record Linkage” by Özgür Akgün

Event details

  • When: 18th October 2018 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Seminar

Record linkage is the process of identifying records that refer to the same real-world entities, in situations where entity identifiers are unavailable. Records are linked on the basis of similarity between common attributes, with every pair being classified as a link or non-link depending on their degree of similarity. Record linkage is usually performed in a three-step process: first groups of similar candidate records are identified using indexing, pairs within the same group are then compared in more detail, and finally classified. Even state-of-the-art indexing techniques, such as Locality Sensitive Hashing, have potential drawbacks. They may fail to group together some true matching records with high similarity. Conversely, they may group records with low similarity, leading to high computational overhead. We propose using metric space indexing to perform complete record linkage, which results in a parameter-free record linkage process combining indexing, comparison and classification into a single step delivering complete and efficient record linkage. Our experimental evaluation on real-world datasets from several domains shows that linkage using metric space indexing can yield better quality than current indexing techniques, with similar execution cost, without the need for domain knowledge or trial and error to configure the process.

Distinguished Speaker Program Tour (Indonesia): Professor Aaron Quigley

Professor Quigley will engage in a lecture tour to three cities in Indonesia in March 2019 as part of the Distinguished Speaker Program (DSP) of the Association for Computing Machinery (ACM). The DSP brings together international thought leaders from academia, industry, and government.

Professor Quigley will speak at the 5th International HCI and UX Conference which will travel to Jakarta, Surabaya and Denpasar. He will present talks on Discreet Computing and Global Human Computer Interaction along with meeting with local academic and industry leaders in Human Computer Interaction. Professor Quigley will be on sabbatical in the National University of Singapore next year.

SRG Seminar: “Efficient Cross-architecture Hardware Virtualisation” by Tom Spink

Event details

  • When: 11th October 2018 13:00 - 14:00
  • Where: Cole 1.33b
  • Series: Systems Seminars Series
  • Format: Seminar, Talk

Virtualisation is a powerful tool used for the isolation, partitioning, and sharing of physical computing resources. Employed heavily in data centres, becoming increasingly popular in industrial settings, and used by home-users for running alternative operating systems, hardware virtualisation has seen a lot of attention from hardware and software developers over the last ten?fifteen years.

From the hardware side, this takes the form of so-called hardware assisted virtualisation, and appears in technologies such as Intel-VT, AMD-V and ARM Virtualization Extensions. However, most forms of hardware virtualisation are typically same-architecture virtualisation, where virtual versions of the host physical machine are created, providing very fast isolated instances of the physical machine, in which entire operating systems can be booted. But, there is a distinct lack of hardware support for cross-architecture virtualisation, where the guest machine architecture is different to the host.

I will talk about my research in this area, and describe the cross-architecture virtualisation hypervisor Captive that can boot unmodified guest operating systems, compiled for one architecture in the virtual machine of another.

I will talk about the challenges of full system simulation (such as memory, instruction, and device emulation), our approaches to this, and how we can efficiently map guest behaviour to host behaviour.

Finally, I will discuss our plans for open-sourcing the hypervisor, the work we are currently doing and what future work we have planned.

Dasip 2018 Keynote: Professor Simon Dobson

Head of School Simon Dobson will deliver a keynote at Dasip, the Conference on Design and Architectures for Signal and Image Processing in October in Porto. Dasip provides an international forum for innovation and developments in the field of embedded signal processing systems. Simon’s keynote will focus on making the transition from sensors to sensor systems software.

Abstract: Signal processing underpins everything we do with sensors. The physical limits of sensors, and the effects of their exposure to their environment, in turn constrain their accuracy, and therefore affect the trust we can place in sensor-driven systems. But this is a long pipeline, and it’s by no means clear how to trace from low-level errors and inaccuracies to their high-level consequences. In this talk I will try to tease-out some of the desiderata we might look for in such a pipeline, with a view to understanding how we can go about building sensor systems that deserve our trust.

An Academic’s Observations from a Sabbatical at Google

Professor Adam Barker is featured in this month’s Communications of the ACM Magazine (CACM) discussing his recent Visiting Faculty appointment at Google. The Viewpoints article summarises his experiences working in software engineering on the Borgmaster team, and some of the core lessons which can be brought back to academia.

Borg is Google’s cluster management framework, which runs hundreds of thousands of jobs, across a number of clusters each with up to tens of thousands of machines.

National University of Singapore

Professor Aaron Quigley has been appointed a Visiting Senior Research Fellow in the Smart Systems Institute in the National University of Singapore. As part of his next sabbatical Aaron will spend 6 months in the Creating Unique Technology for Everyone (CUTE) centre in Singapore [Video]. He will be collaborating with researchers there on next generation interfaces, discreet computing and new forms of interaction. The research and lessons learnt will help advance the field of HCI and will be incorporated in future teaching and research here in St Andrews.

Science and Innovation mission to Japan

Sue Kinoshita, Minister Counsellor economic affairs and Professor Quigley

This week Professor Quigley joined a mission to Japan with other academics from the University of Oxford, Edinburgh, UCL and Manchester. The week long event was organised by the UK’s Science and Innovation team in Japan, part of the Foreign and Commonwealth Office. Over five days the delegation visited and presented at seven companies along with three seminars and workshops. Across nine presentations Professor Quigley presented to hundreds of people and introduced some of the Human Computer Interaction research in SACHI, along with research from the AI research group. This mission has the goal to strengthen research collaboration and innovation partnership between the UK and Japan.

During his talks, Aaron provided examples from our engineering doctorate program, our MSc program, work on research interns, PhD students and academics from across Computer Science.

 

Sethu Vijayakumar, Edinburgh University, Sue Kinoshita, Minister Counsellor economic affairs, Professor Aaron Quigley, Seiichi Asano, Senior science Officer and Joesph Robertson, Science & Innovation Officer.

Griff Jones, First Secretary, science innovation & global challenges, Sethu Vijayakumar, Edinburgh University, Sue Kinoshita, Minister Counsellor economic affairs, Professor Aaron Quigley, Seiichi Asano, Senior science Officer and Joesph Robertson, Science & Innovation Officer.