Coding and programming can be invaluable skills for scientists and engineers, but it’s important to know how to use them appropriately. How do we identify problems which may benefit from these tools? How can we choose which coding languages to learn, and how to best apply them to our research? Join us in this webinar to find out how researchers with little to no coding experience can build their skills and enhance their work!
Dr Douglas Houston
KISS: Teaching Python to Absolute Novices
Our Introduction to Python Programming for Data Science is aimed at Data Science Technology and Innovation MSc students with no prior experience of programming. Therefore, the course consists of introductory learning material presented in the Python language. All teaching is delivered online through Learn, Collaborate and Jupyter Notebooks hosted on the CoCalc in-browser platform. Weekly online pair-programming sessions provide live interaction, and online discussion forums allow asynchronous communication. A strong emphasis is placed on self-guided learning, and the use of web resources such as search, Stack Exchange, Git Hub, Quora and various mailing lists.
Coding for Machine Learning In Science
The future of STEM is written in computer code. This is true for education, for academic research and technological industries. Indeed, after graduation, current STEM students will likely spend a significant portion of their careers coding. I’m a 3rd year PhD student focusing on machine learning, and one of the organisers of the ‘Machine Learning in Science’ at the University of Glasgow. So, in this talk, I will discuss some practical aspects of machine learning coding. We will focus on Python practices, data management, adapting online resources for your needs, and commenting and sharing your own code.
Dr Aleksandra Nenadic
The Carpentries, and giving researchers the basic skills they need to tackle their data and computing challenges
Making research methods, data and results more accessible and reproducible can contribute to better science. Taking even small steps towards being more open, reproducible or even a bit better organised than the last time will make you more efficient in your work but will also help make the life easier for your future self or the person that comes to your group/lab after you. The Carpentries is a big international community of enthusiastic volunteers teaching foundational computational skills (version control, basic programming, command line, data organisation, cleaning, analysis and visualisation) founded on best practices (building modular and reusable code, using data structures, reproducibility) for researchers across disciplines. The emphasis is not on advanced, enterprise workflows or tools, but basic “toolbox” skills for everyday use that can be mastered in a relatively short period of time giving researchers the data organisation and computing skills they didn’t even know they needed.
Despite our best intentions, biases – be they from our subconscious, or influenced by culture and history – can find their way into our work. In this webinar, we’ll look at examples of how unintentional biases are detected and avoided in the things we design and engineer.
Dr Renate Baumgartner
Bias in Technology
Technology may seem objective, at least more objective than humans. From a socio-technical point of view, however, we know that people inscribe their values and norms in technologies. This talk will explain what we mean by cultural/social/historical bias, how it permeates technologies and what we should be wary about, when developing and employing technologies. Drawing on examples from artificial intelligence, we will also learn some ways in which bias can be mitigated.
Dr Patricia Xavier
Can dissonance between engineering mindsets and justice impede responsible decision making?
Inherent in any engineering system are issues of power and oppression, who benefits and who is impacted. Consider cases of data bias driving discrimination and the lack of action in the sector proportionate to the threat from the deteriorating climate. This presentation discusses how well engineers are trained to engage in discussions of justice, power and discrimination by interrogating the values and norms of engineering culture. In exploring the ontological gaps between engineering and justice, we can see how some engineering teaching methods can damage our ability to practice inclusively, and find ways to incorporate more justice into our work.
Race and Gender Bias in Medical Devices, case: Pulse Oximetry Technology
The current COVID-19 pandemic has shown us that the pulse oximeter is a key medical device for monitoring blood-oxygen levels non-invasively in patients with chronic or acute illness. It has also emphasized limitations in accuracy for individuals with high skin pigmentation and woman, calling for new methods to provide better oxygen measurements. Is it possible to eradicate racial and gender bias in the clinical application?
Wearable sensing technologies – whether fitness trackers, continuous glucose monitoring, or smart textiles – have the potential to revolutionise healthcare by providing more information to patients and medical professionals, moving towards a more personalised and patient-centric model of healthcare.
CISMA is delighted to present our annual conference on the Future of Intelligent Sensing and Measurement 2021: Wearable Sensing Technologies for Healthcare Monitoring. Join us in Glasgow on Tuesday 23rd November 2021 to hear from a panel of experts on the future of wearables in medicine and health. This full-day in-person conference will cover four themes in the broad field of wearable sensing technologies:
Materials, Textiles, and Design
Power Systems and Communication
Registration is available now, and please check back soon for speaker information and presentation abstracts!
Session 1: Sensor Technology
Session 2: Data Processing
Session 3: Materials, Textiles and Design
Session 4: Power Systems and Communication
This event has been fully funded the EPSRC Centre for Doctoral Training in Intelligent Sensing and Measurement (https://www.cdt-ism.org/)
This quiz is for students aged 10-12 and is intended as an informal assessment to evaluate knowledge/learning as part of a climate change unit. The quiz is most fun if social distancing allows for teams, but individual students can play as well.
How does it work?
There are 25 questions divided into five rounds, which should take about 60 minutes to complete and discuss. Each round can be played separately over several classes if time is a factor (this may also be a good option to jump start individual lessons in your unit). The first four rounds consist of six questions each, and the single question in Round Five is intended to introduce students to COP 26 and/or the Paris Agreement.
There are additional resources in the slide notes for further information and activities for specific topics, and a printable answering sheet is included.
Can technology end our reliance on unsustainable fossil fuels? How can we ensure a stable global economy for food production and supply? How will our ageing population affect society? What impacts, good or bad, will robots and AI have on our future lifestyles?
CISMA would like to present S2HF: Symposium for a Sustainable Human Future. In this event, we aim to bring some of the most pressing societal and environmental challenges to light, and to discuss potential solutions to those challenges. We will be addressing four topics: Long-term Models for Global Food Security,Sustainable Energy Harvesting, Future Demands of an Ageing Society, and the Impact of AI and Robots on our Lifestyle.
Who is coming to S2HF?
Long-term Models for Global Food Security
Sustainable Energy Harvesting
Future Demands of an Ageing Society
Impact of AI and Robots on our Lifestyle
With our speakers’ bright minds leading us towards new solutions, the future of humanity is not entirely uncertain. What is certain, however, is CISMA’s excitement to be present for the inception of these ideas, and that you will be there to witness them with us. The Symposium for a Sustainable Human Future will consist of open panel discussions between the speakers, followed by Q&A sessions.
The full-day symposium will be held on Tuesday 28th September 2021, at the Royal College of Physicians (Edinburgh). S2HF is a hybrid event: Tickets are available for in-person attendance and online streaming for those who want to attend virtually – both options free of cost! Registration can be found here.
Even after peer-review and publication, science papers could still contain undetected errors or even fraudulent data. In addition, authors might have undisclosed conflicts of interest, false affiliations, or hidden agendas. If not addressed post-publication, papers containing incorrect or even falsified data could lead to wasted time and money spent by other researchers trying to reproduce those results. In this talk, I will show several examples of research papers containing problematic and fraudulent data, fake affiliations, predatory journals, and paper mill productions.
Dr Elisabeth Bik is a science integrity consultant who specializes in finding image duplications in scientific papers. After receiving her PhD in Microbiology at Utrecht University in The Netherlands, she worked 15 years at the Stanford University School of Medicine and two years at two microbiome startup companies, after which she left her job to become a science integrity volunteer and occasional consultant. She has reported over 4,000 papers for issues with image duplication or other concerns. Her work has been featured in Nature, Science, Wall Street Journal, New York Times, Washington Post, Le Monde, and The Times (UK). In April 2021 she was awarded the Peter Wildy Prize by the UK Microbiology Society for her contributions in science communication.
Dr Stuart Ritchie
Correcting bad scientific research
There are few more thankless tasks than trying to correct bad research. Although we all hope that the scientific literature is an as-objective-as-possible record of research, and that it contains built-in mechanisms for self-correction, we all know that (a) research can still be suffused with biases, careless errors – and worse; and (b) it often takes an absurd amount of time for that self-correction process to work. In this talk, I’ll discuss some of the attempts I’ve made over the years to correct objective errors in scientific papers, discuss my varying degrees of success, and describe the–often quite dispiriting–lessons I’ve learned.
Dr Stuart Ritchie graduated with a PhD in Psychology from the University of Edinburgh in 2014 and has held a Lecturer position at the Institute of Psychiatry, Psychology and Neuroscience at King’s College London since 2018. His research primarily focuses on the development of cognitive abilities and the causes and consequences of cognitive differences between individuals. He is the author of ‘Intelligence: All That Matters’ (2016) and ‘Science Fictions: How Fraud, Bias, Negligence, and Hype Undermine the Search for Truth’ (2020) and was awarded the 2015 Rising Star award from the Association for Psychological Science.