Back to normal

The School will be fully open as normal from around 0800 tomorrow, Thursday 14 February.  We’re running on generator power as a result of the weekend’s fire in Chemistry, but this will be sufficient to run all our lights, alarms, systems, and other equipment. There may need to be some restrictions in 24-hour lab access, but we’re hopeful that this won’t be necessary.

Thank you everyone for your patience and understanding, as well as to all the staff in the School and the wider University who’ve both minimised the disruption and got us back into operation so quickly.

 

Prof Simon Dobson
Head of School for Computer Science

Reduced service because of fire

As you may be aware, there was a fire over the weekend in the School of Chemistry. While this has not led to any physical damage in Computer Science, it has meant we’ve lost all power and access to our main Jack Cole building.

The School is still open and functioning as normally as possible. Classes are being relocated to other rooms in the University whenever possible. However, staff have no access to their offices (or phones), and we will be cancelling all non-essential meetings or events.

We’re sorry for any inconvenience. We expect to be back running again as normal by the end of the week. I’m happy to (try to) answer any questions you may have.

 

Prof Simon Dobson
Head of School for Computer Science

 

Paul-Olivier Dehaye: From Cambridge Analytica to the future of online services: a personal journey (School Seminar)

Event details

  • When: 19th March 2019 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

Abstract:

2018 was a crazy year for privacy. The General Data Protection Regulation came into force in May, and new revelations on the personal data ecosystem were making headlines on a weekly basis. I will give the behind the scenes for a lot of these events, question why they didn’t happen earlier, and offer some thoughts on the necessary future of online services. This will include a brief discussion of topics such as semantic alignment, interpretable machine learning, or new privacy-preserving data processing techniques.

Speaker Bio:

Paul-Olivier Dehaye is a mathematician by training. Affiliated to the University of Zurich as a SNSF Assistant Professor until 2016, his career then took a turn towards data protection activism and social entrepreneurship. He was the researcher on several news articles who have reached millions of readers (including many with Carole Cadwalladr), and testified in front of the UK and EU Parliaments on multiple occasions. He is on the board of MyData Global, has founded the NGO PersonalData.IO, and the project MyData Geneva.

Dr Juan Ye: Lifelong Learning in Human Activity Recognition

Dr Juan Ye will be running an online event for IEEE SMC (Systems, Man and Cybernetics Society) on Lifelong Learning. The technical seminar, designed to focus on future research trends in human activity recognition, will take place on Friday 1st February from 2.00pm – 3.00pm.


Seminar Details: Human activity recognition systems will be increasingly deployed in real-world environments and for longer periods of time. This significantly challenges current approaches to human activity recognition, which have to account for changes in activity routines, evolution of situations, and of sensing technologies. Driven by these challenges, this webinar will argue the need to move beyond learning to lifelong machine learning – with the ability to incrementally and continuously adapt to changes in the environment being learned. We will introduce a conceptual framework for lifelong machine learning to structure various relevant proposals in the area, and identify some key research challenges that remain.

Read more about the event and joining instructions through IEEE online.

Tom Kelsey appointed Associate Editor of Human Reproduction Update

Arne Sunde, the incoming Editor-in-Chief, has appointed Tom Kelsey as Associate Editor of Human Reproduction Update.

Human Reproduction Update is the leading journal in Reproductive Medicine, with an Impact Factor of 11.852. The journal publishes comprehensive and systematic review articles in human reproductive physiology and medicine, and is published on behalf of the European Society of Human Reproduction and Embryology (ESHRE). The Associate Editor system at Human Reproduction Update has been in place since the beginning of 2001 and it has a significant positive effect on the quality and dynamism of the journal.

In the ISI JCR Global Ranking for 2017, Human Reproduction Update is ranked first of 29 journals in Reproductive Biology, and first of 82 journals in Obstetrics & Gynecology.

Tom Kelsey has published extensively in Human Reproduction Update and its sister journals Human Reproduction (impact factor 4.949) and Molecular Human Reproduction (impact factor 3.449). He is also Associate Editor for the Open Access journals Frontiers in Endocrinology and Frontiers in Physiology. He is a regular reviewer for these journals and also the British Medical Journal, BMJ Open, Health Education Journal, Nature Scientific Reports, PLOS One, Mathematical Medicine and Biology, Systems Biology in Reproductive Medicine, and the European Journal of Obstetrics & Gynecology and Reproductive Biology.

A new vision

In an unexpected addition to his skill set the School’s resident gadget expert, Marwan Fayed, has started a sideline in cleaning glasses with his new ultrasonic cleaning-thingy, as found in quality opticians everywhere.

After a successful demonstration on the Head of School’s eyewear a long queue of glasses-wearing computer scientists formed around the School’s coffee area. Who knows how much this will improve our creativity?

Rachel Menzies (Dundee): Unlocking Accessible Escape Rooms: Is Technology the Key? (School Seminar)

Event details

  • When: 2nd April 2019 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

Abstract:

Escape rooms are popular recreational activities whereby players are locked in a room and must solve a series of puzzles in order to ‘escape’. Recent years have seen a large expansion technology being used in these rooms in order to provide ever changing and increasingly immersive experiences. This technology could be used to minimise accessibility issues for users, e.g. with hearing or visual impairments, so that they can engage in the same way as their peers without disabilities. Escape room designers and players completed an online questionnaire exploring the use of technology and the accessibility of escape rooms. Results show that accessibility remains a key challenge in the design and implementation of escape rooms, despite the inclusion of technology that could be used to improve the experience of users with disabilities. This presentation will explore the lack of accessibility within Escape Rooms and the potential for technology to bridge this gap.

Speaker Bio:

Dr Rachel Menzies is the Head of Undergraduate Studies for Computing at the University of Dundee and is the current SICSA Director of Education (https://www.sicsa.ac.uk/education/). She co-directs the UX’d research group (https://www.ux-d.co.uk/) and her research interests include user centred design with marginalised user groups, such as users with disabilities, as well as exploring novel interfaces, data visualisation and CS education. Her most recent work focusses on accessibility is in escape rooms, in particular how users with varied disabilities can access and enjoy the experience alongside typical users.

Marina Romanchikova (NPL): How good are our data? Measuring the data quality at National Physical Laboratory (School Seminar)

Event details

  • When: 12th March 2019 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

Abstract:

From mapping the spread of disease to monitoring climate change, data holds the key to solving some of the world’s biggest challenges. Dependable decisions rely on understanding the provenance and reliability of data. Historically, only a small fraction of the generated data was shared and re-used, while the majority of data were used once and then erased or archived. At NPL Data Science we are defining best practice in measurement data reuse and traceability by developing metadata standards and data storage structures to locate and interpret datasets and make them available for sharing, publication and data mining.

The talk will shed light on the most burning issues in the scientific data management, and illustrate it with examples from industrial and academic practices. It will present several NPL Data Science projects that focus on delivering confidence in data obtained from life science imaging, medicine, geosciences and fundamental physics.

Speaker Bio:

Dr Marina Romanchikova joined the NPL Data Science team in 2017 to work on data quality and metadata standards. She obtained an MSc in Medical Informatics at University of Heidelberg, Germany, where she specialised in medical image processing and in management of hospital information systems. In 2010 she received a PhD on Monte Carlo dosimetry for targeted radionuclide therapy at the Institute of Cancer Research in Sutton, UK. Marina worked six years as a radiotherapy research physicist at Cambridge University Hospitals where she developed methods for curation and analysis of medical images.

Current interests

– Quantitative quality assessment of medical images and medical image segmentation
– Harmonisation of medical and healthcare data from heterogeneous sources
– Applications of machine learning in healthcare
– Automated data quality assurance

Lauren Roberts & Peter Michalák (Newcastle): Automating the Placement of Time Series Models for IoT Healthcare Applications (School Seminar)

Event details

  • When: 26th February 2019 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

Abstract:

There has been a dramatic growth in the number and range of Internet of Things (IoT) sensors that generate healthcare data. These sensors stream high-dimensional time series data that must be analysed in order to provide the insights into medical conditions that can improve patient healthcare. This raises both statistical and computational challenges, including where to deploy the streaming data analytics, given that a typical healthcare IoT system will combine a highly diverse set of components with very varied computational characteristics, e.g. sensors, mobile phones and clouds. Different partitionings of the analytics across these components can dramatically affect key factors such as the battery life of the sensors, and the overall performance. In this work we describe a method for automatically partitioning stream processing across a set of components in order to optimise for a range of factors including sensor battery life and communications bandwidth. We illustrate this using our implementation of a statistical model predicting the glucose levels of type II diabetes patients in order to reduce the risk of hyperglycaemia.

Speaker Bios:

Lauren and Peter are final year PhD students at the CDT in Cloud Computing for Big Data at Newcastle University. Peter has a background in Computer Engineering from University of Žilina, Slovakia and a double-degree in Computer Software Engineering from JAMK University of Applied Sciences, Jyväskylä, Finland. His research interests are within distributed event processing, edge computing and Internet of Things with a special focus on energy and bandwidth constrains. Lauren has an MMath degree from Newcastle University and her research interests lie in statistical modelling of time series data.