Past Events

Risk Institute Online:

Anne Michiels van Kessenich: Risk is a tool, not a problem: communicating risk to make confident decision makers

In this lecture Anne presents the guiding material and principles that undergird the idea of risk as a communicative tool. In a nutshell, Anne’s research has observed a category error which is consistently made when thinking about the risk-concept: risk if often conceptualised as a threat in-of-itself within the general population due to how it has been communicated from early infancy, a perception which may result in decision-making avoidance and potentially exacerbate the effect of hazards. A successful shift in perception away from risk-as-a-threat requires new frames of communication: risk is a sign that asks you to pay close attention, like a traffic sign. There is no point in fearing a traffic sign; instead, you should learn to understand what it means and to use it wisely. Attendees are encouraged to share their views and ideas surrounding the problems and solutions regarding effective risk communication, and are asked to think one question in particular: is there a “silver bullet” with which we can help grown-ups lose their fear and avoidance of real engagement with the concept?

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Risk Institute Online:

Ullrika Sahlin: Precise Versus Bounded Probability

Ullrika Sahlin is an Associate Professor in Environmental Science at Lund University, Sweden. She is doing research on the use of methods to treat uncertainty in scientific assessments with applications on environmental assessments and evidence-based decision making. Ullrika is leading the research group Uncertainty and Evidence Lab at Lund University.

What does it mean to quantify epistemic uncertainty by probability? Can there be more than one way to do it? In this discussion seminar I will compare precise and bounded probability as measures for epistemic uncertainty. I look for criteria for suitable quantitative measures of epistemic uncertainty such as a coherent theory, interpretation, the ability to learn from data in different types of situations, the ability to in a transparent way integrate expert knowledge and the ability to propagate epistemic uncertainty in a model. We focus the discussion to Bayesian inference (for precise probability) and Robust Bayesian inference (for bounded probability) and Confidence theory (for confidence boxes).

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Risk Institute Online:

Ottone Scammacca: Risk assessment of mining projects at the territory level: the case of gold mining in French Guiana

Ottone Scammacca is a geographer and soil scientist working at the GeoRessources Laboratory, Université de Lorraine. He is currently completing his thesis on the development of a methodology for the assessment of gold mining risks at the territory level for land planning-purposes. His research interests concern as well soil ecosystem services, soil contamination, land reclamation and land-planning. He has been a researcher at the French National Institute for Agriculture, Food, and Environment (INRAE) in soil science and cartography, developing a spatially explicit indicator approach for quantifying soil ecosystem services to support urban planning. He was educated in soil science at the AgroParisTech and in geography at the Université de Paris 1 Panthéon-Sorbonne where he studied the socio-environmental impacts of nickel mining in New Caledonia. He also has a degree in law and juridical sciences from Università Degli Studi Roma Tre (Italy).

Mining is the source and target of various positive and negative risks, that generally exceed the mine-site perimeter, and might impact the socio-ecological system where mining is performed. However current mandatory risk and impact assessment methodologies are often project-centered, performed on one project at a time and sometimes neglecting the cumulative dimension of risks, the great variability of mining activities and the socio-ecological vulnerability in which mining is performed.

Therefore, since a mining project should be considered as a matter of land-planning and territorial management rather than a simple industrial object, the current PhD (2017-2020) aims to develop a methodology that has the goal to propose and compare different mining development strategies for land-planning purposes, based on the risk assessment of given scenarios. The methodology is applied on the case of gold mining in French Guiana as a demonstrative example. In this French region in the Amazon, gold exploitation plays a critical role within territory dynamics, taking a great variety of forms in a very sensitive socio-ecological context. Furthermore, gold commodities are still underexploited, incresing public debates and the urgent needs for public authorities to develop future strategies that might integrate the development of gold mining activities at a regional level.

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Risk Institute Online:

Bruno Merk: Nuclear Technology - A High Risk Technology? or What Happens if Risk Communication Fails?

Prof Bruno Merk is a highly recognized expert and thought leader in advanced nuclear reactor technologies and nuclear waste management strategies. He is currently involved in several national nuclear innovation projects sponsored by the Department for Business, Energy & Industrial Strategy and represents innovative technologies like iMAGINE – a nuclear energy system operating on spent nuclear fuel. Before coming to the UK, he was PI in the German National Programme on Nuclear Waste Management, Safety and Radiation Research (NUSAFE) and advised the German government on Nuclear Waste Management Strategies.

The seminar will introduce nuclear reactor safety to non-specialists by surveying the fundamentals and basic principles of safety in terms of historical examples and describing the safety design approach and engineering principles for controlling high-risk technologies. It will review how the perception of nuclear technologies and nuclear energy production has changed with time in Germany and what impact perception might have on new and old technologies and their acceptability, comparing examples of projects that failed in Germany although similar projects precipitated no major discussions in France or the UK. The presentation will lead into an open discussion on several fundamental questions. Why is risk communication important for engineering? What went wrong to cause the historical failures? How could we do better in the future?

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Risk Institute Online:

Dominik Hose: The Embarrassingly Simple Calculus of Possibility Theory

Dominik Hose received his bachelor's and master's degree in Simulation Technology from the University of Stuttgart (Germany) in 2015 and 2017. Currently, he is a phd student under the supervision of Michael Hanss at the University of Stuttgart. Most importantly, the REC-Workshop hosted by the Risk Institute in 2018 was his first UQ conference ever to attend and it sparked his passion for imprecise probabilities. Dominik's research focuses on solutions to inverse problems in possibility theory and their numerical implementation.

Possibility theory is the mathematically rigorous heir to fuzzy set theory and can be used very efficiently for the quantification of polymorphic uncertainty in both forward and inverse problems.
We discuss how a possibility measure can be derived from an axiomatic basis, and how - equipped with some suitable principles - this provides a mathematical framework for imprecise probabilities. We then see how possibility distributions arise very naturally in many situations and which techniques are available for modeling possibilistic membership functions. Finally, many problems of possibilistic calculus may be expressed in a simple and general manner for which we consider several numerical solution approaches. Special emphasis is put on the intuitiveness, applicability, and simplicity of the presented results.

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Risk Institute Online:

Michael Balch: Beyond False Confidence

For those who take frequentist notions of reliability seriously, normative statistical inference remains an unresolved challenge. For any one problem, there are multiple solutions that satisfy the Martin-Liu validity criterion. Some of these are obviously more efficient than others, but the vigorous pursuit of efficient and reliable inference can yield counter-intuitive results. This presentation explores three counter-intuitive phenomena that can arise in the use of confidence curves. Two of these phenomena hint at the need for additional constraints on statistical inference, beyond simple reliability.

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Risk Institute Online:

Alan Calder: Resolving Thermonuclear Supernovae

Thermonuclear (Type Ia) supernovae are bright stellar explosions distinguished by light curves that can be calibrated to allow for their use as "standard candles" for measuring cosmological distances. While many fundamental questions remain, it is accepted that the setting of these events involves a white dwarf star (or two), and that the explosion is powered by explosive thermonuclear burning under degenerate conditions. Modeling these events presents a challenge because the outcome of an event sensitively depends on the details of the physics occurring on scales orders of magnitude smaller than the star. Such "microphysics" includes nuclear burning, fluid instabilities, and turbulence. I will give an overview of our understanding of thermonuclear supernovae and describe our approach to capturing these sub-grid-scale processes in macroscopic simulations.

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Risk Institute Online:

Jürgen Hackl: ABM simulations of epidemic spreading in urban areas

Human mobility is a key element in the understanding of epidemic spreading. Thus, correctly modeling and quantifying human mobility is critical for studying large-scale spatial transmission of infectious diseases and improving epidemic control. In this study, a large-scale agent-based transport simulation (MATSim) is linked with a generic epidemic spread model to simulate the spread of communicable diseases in an urban environment. The use of an agent-based model allows reproduction of the real-world behavior of individuals’ daily path in an urban setting and allows the capture of interactions among them, in the form of a spatial-temporal social network. This model is used to study seasonal influenza outbreaks in the metropolitan area of Zurich, Switzerland. The observations of the agent-based models are compared with results from classical SIR models. The model presented is a prototype that can be used to analyze multiple scenarios in the case of a disease spread at an urban scale, considering variations of different model parameters settings. The results of this simulation can help to improve comprehension of the disease spread dynamics and to take better steps towards the prevention and control of an epidemic.

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Risk Institute Online:

Ryan Martin: False confidence, imprecise probabilities, and valid statistical inference

Dr. Ryan Martin is a Professor in the Department of Statistics at North Carolina State University, USA. His research interests include asymptotics, empirical Bayes analysis, high- and infinite dimensional inference problems, foundations of statistics, imprecise probability, mixture models, etc. He is co-author of the monograph Inferential Models and co-founder of the Researchers.One peer review and publication platform.

Despite remarkable advances in statistical theory, methods, and computing in the last 50+ years, fundamental questions about probability and its role in statistical inference remain unanswered. There is no shortage of ways to construct data-dependent probabilities for the purpose of inference, Bayes being the most common, but none are fully satisfactory. One concern is the recent discovery that, for any data-dependent probability, there are false hypotheses about the unknown quantity of interest that tend to be assigned high probability -- a phenomenon we call false confidence -- which creates a risk for systematically misleading inferences. Here I argue that these challenges can be overcome by broadening our perspective, allowing for uncertainty quantification via imprecise probabilities. In particular, I will demonstrate that it is possible to achieve valid inference, free of false confidence and the associated risks of systematic errors, by working with a special class of imprecise probabilities driven by random sets. Examples will be given to illustrate the key concepts and results, and connections between this new framework and familiar things from classical statistics will be made.

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Risk Institute Online:

Michael Balch: Numerical Methods for Propagating Confidence Curves

Michael Balch is the Technical Lead at Alexandria Validation Consulting, LLC. He designs the algorithms underpinning our software and renders all consulting services personally. Dr. Balch has twelve years of experience as a research-practitioner specializing in uncertainty quantification. He has worked on applications spanning engineering, medicine, defense, and finance. His career has included time as a contractor at both NASA Langley and AFRL Wright-Patterson. He received his Doctorate in Aerospace Engineering from Virginia Tech in 2010.

Confidence curves—aka consonant confidence structures, aka inferential models—fuse the comprehensiveness and flexibility of Bayesian inference with the statistical performance and rigor of classical frequentist inference. Rooted in possibility theory, these structures visualize the long-known connection between confidence intervals and significance testing. More importantly, they enable the statistically reliable assignment of belief to propositions (or sets, hypotheses, etc.) about a fixed parameter being inferred from random data. This presentation explores a Monte Carlo approach to propagating these structures through black-box functions, a necessity if these methods are to be widely applied in engineering work.

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Risk Institute Online:

Noémie Le Carrer: Making sense of ensemble predictions in weather forecasting: Can possibility theory overcome the limitations of standard probabilistic interpretations?

Ensemble forecasting is widely used in weather prediction to reflect uncertainty about high-dimensional, nonlinear systems with extreme sensitivity to initial conditions. Results are generally interpreted probabilistically but this interpretation is not reliable because of the chaotic nature of the dynamics of the atmospheric system as well as the fact that the ensembles were not actually generated probabilistically. We show that probability distributions are not the best way to extract the information contained in ensemble prediction systems. A more workable possibilistic interpretation of ensemble predictions takes inspiration from fuzzy and possibility theories. This framework also integrates other sources of information such as the insight on the local system’s dynamics provided by the analog method and provides more meaningful quantitative results.

Risk Institute Online:

Jurgen Hackl: ABM simulations of epidemic spreading in urban areas

Dr Jürgen Hackl is a Lecturer at the University of Liverpool and a member of the Data Analytics Group at the University of Zurich. He received his doctorate in Engineering Science from the ETH Zurich in July 2019. His research interests lie in complex urban systems and span both computational modelling and network science. Much of his work has been on improving the understanding, design, and performance of complex interdependent infrastructure systems, affected by natural hazards. Presently, he works on getting a better understanding of how the topology of the system influences dynamic processes and how this can be used to decrease the complexity of computational models. In order to transfer this knowledge to the industry, he co-founded the start-up Carmentae Infrastructure Management, helping infrastructure managers in their decision-making processes. Furthermore, he has a long history of supporting a sustainable digital world by developing and maintaining various open-source projects.

Dr Hackls' presentation focuses on complex infrastructure systems (such as transportation and supply chains), intelligent risk and resilience assessments for climate change, and integrated solutions to future challenges facing our cities and society. To gain a deeper understanding of such complex systems, new mathematical approaches and computational models are needed. In order to achieve this, we have to go beyond the classical boundaries of the individual disciplines and work in an interdisciplinary team. In this sense, research on smart mobility and smart cities have been developed as new research areas.

The aim of this presentation is to give an overview how complex infrastructure systems are currently modelled; how novel network analytic methods for spatial-temporal networks can be utilized to gain a better understanding of our complex urban environment; how advances in data analytics and machine learning provide us new ways to extract knowledge and support decision-making processes; as well as how cloud-based simulations might offer a solution for computational risk and resilience assessments of complex infrastructure systems.

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Risk Institute Online:

Yan Wang: Generalized Interval Probability and Its Applications in Engineering

Yan Wang, Ph.D. is a Professor of Mechanical Engineering at Georgia Institute of Technology. He is interested in multiscale systems engineering, modeling and simulation, and uncertainty quantification, and has published over 90 archived journal papers and 80 peer-reviewed conference papers. He recently edited the first book of its kind on uncertainty quantification in multiscale materials modeling

Uncertainty in engineering analysis is composed of two components. One is the inherent randomness because of fluctuation and perturbation as aleatory uncertainty, and the other is epistemic uncertainty due to lack of perfect knowledge about the system. Imprecise probability provides a compact way to quantify and differentiate the two components, where the probability measures randomness and the interval range quantifies the imprecision associated with the probability. Several forms of imprecise probability have been proposed such as Dempster-Shafer theory, coherent lower prevision, p-box, possibility theory, fuzzy probability, and random set. To simplify the computation for engineering analysis, we introduced generalized interval probability where the interval bounds take the form of directed or modal interval instead of classical set-based interval. Interval calculation is based on the more intuitive Kaucher interval arithmetic. Generalized interval probability has been applied in studying stochastic dynamics, hidden Markov model, Kalman filter, random set sampling, and molecular dynamics simulation.

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Risk Institute Online:

Dan Rozell: Technological Risk Attitudes in Science Policy

Daniel Rozell has two decades of experience in the fields of engineering and science working in private industry and for public regulatory agencies. Dr. Rozell holds an affiliation as Research Professor in the Department of Technology and Society at Stony Brook University in New York. His recent book, Dangerous Science: Science Policy and Risk Analysis for Scientists and Engineers is available open access at Ubiquity Press

Science and technology policy decisions must often be made before there is sufficient data, widely accepted theories, or consensus in the scientific community. Furthermore, what constitutes credible science is sometimes itself a contentious issue. The result is that we frequently encounter science and technology policy debates where well-intentioned and reasonable individuals can arrive at different conclusions. In the face of inconclusive data, people tend to evaluate new information using heuristics that include their pre-existing attitudes about science and technology.

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Dispersal interactions in a changing world

Cristina Garcia Perez

Dispersal represents a formidable challenge for sessile organisms such as plants, yet the persistence of plant populations in a changing world largely depends on their ability to reach suitable sites to germinate and establish. Most plants require the assistance of dispersal mutualisms provided by animals to disperse their pollen grains and/or their seeds. Therefore, the activity of pollinators and frugivores is fundamental to maintain highly levels of connectivity and gene flow among populations across the landscape, as well as to expand their distribution range to track environmental changes, such as increasing warming. Yet, in an increasingly defaunated and warming world the dispersal ability of plants is critically compromised and, therefore, the persistence of plant populations might be threatened. Here I will expose the main advances in the study of plant dispersal ecology in the latest decades and illustrate the importance of dispersal processes for plants based on my research work. I will end this talk suggesting future lines of collaboration with members of the Institute for Risk and Uncertainty.

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Imprecise Tuesdays: Humane Algorithms

We are in the age of the algorithm. Artificial intelligence ideas have been emerging within engineering in recent years. Novel ideas, such as digital twins, promise to revolutionise engineering by collecting vast amounts of data and applying machine learning techniques. Computer vision will undoubtedly be the basis of much of the technology behind autonomous vehicles and is being used for monitoring systems.

However, the use of these techniques in different fields has not been without problems. For instance, the use of big data within the criminal justice system has been beset by racial bias and accuracy problems. Facial recognition technology is unreliable, able to be manipulated and again has racial bias problems, yet is increasingly being used by police forces.

In this talk we will discuss the potential pitfalls that can occur with the increased use of algorithms in engineering and discuss how uncertainty can play a key role in mitigating some of these issues.

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Winter School: Machine Learning

The Institute for Risk and Uncertainty at the University of Liverpool is planning to host a multidisciplinary symposium and workshop on uncertainty in image processing. Tentatively over two days, the symposium will introduce and explore issues from multiple perspectives, from uses in biomedical research to remote sensing and computer vision. Envisioned as a collaborative event, the symposium will feature a series of talks aiming to fostering collaboration, detailing common problems, and sharing solutions.

If you would be interested in attending and speaking or otherwise participating in these events, please let us know your availability/preferences via an email to meeting@riskinstitute.uk.

Find out more here, or register here

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Artificial Intelligence Initiative Symposium

Artificial Intelligent (AI) has become a pervasive term in the modern world. Society is immersed in an AI fever permeating every sector of society and in some instances prophesying their demise. At the centre of the AI debate is the role of Higher Education (HE) & the economy. Are these sector prepared for this onslaught, what role will they play and moreover, what impact will this technology have on the future? Building on the prior work of the University of Liverpool’s Management School arising from a pump priming grant to examine the role of intelligent agents in HE, the symposium seeks to explore the role, challenges and opportunities for advancement & implementation of AI within these sectors. In order to do so, the symposium brings together the University of Liverpool’s Risk Institute and Management School for a combined effort to engage with this complex topic.

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Symposium and Workshop: Ocean Cleanup

The Institute for Risk and Uncertainty at the University of Liverpool is planning to host a symposium and workshop on risk tradeoffs, with the removal of plastic pollution from oceans such as by The Ocean Cleanup project as the main example.

There will be two related events over three days. The symposium will introduce and explore the issues from many perspectives, including those of proponents from environmental groups and ocean ecologists. The workshop will be a collaborative event in which we will articulate risk analyses to address those issues. These analyses will employ stochastic demography, including uncertainty propagation for abundances, vital rates, and other variables that are known imprecisely.

We believe that finding quantitative answers to the questions of whether and by how much the benefits from plastics removal outweigh the potential risks to ocean organisms, and how they compare with harms from unabated accumulation of oceanic microplastics, can only be answered by modern quantitative environmental risk analysis at the interface between engineering and ecology.

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Should we remove plastics from the ocean's surface?

Is skimming off the top of the ocean a good idea? The startup firm Ocean Cleanup is already at work collecting plastics from the ocean's surface. Are we over-engineering this? Is the effect on plants and animals there benign or adverse? Is this greenwashing? Matt Spencer will present his model for the effects on sea life. This is a warm-up event for the symposium in December.

Lunch will be provided. Please register to attend by submitting your name below or email if you want to receive email relevant notifications.

Imprecise Tuesday: Risk Governance in China

Visiting Professor Cao Huimin will discuss risk governance next Tuesday, 2pm, in Risk Institute Seminar Room in the Chadwick Building.

Governance refers to the actions and institutions by which decisions are taken and authority is exerted. Risk governance refers to identifying, characterising, mitigating and communicating risks via governance mechanisms. Good risk governance lets societies minimise negative consequences of risks such as storms, technological failures, economic disruption, or civil unrest.

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MATLAB Onramp, an on-line course for beginners and experienced MATLAB users

If you want to learn how to use MATLAB or get better at using it, come to the Risk Institute at 5-7pm on 7 November for the MATLAB Onramp shortcourse

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Showcase Conference 2019

In this conference our Students will present their research progress to step up onto their PhD status. Further, there will be a poster competition open to all PhD students of the Risk Institute. This is an opportunity to see the current research pursued at the CDT and Institute for Risk and Uncertainty.

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Imprecise Tuesdays: Hannah Forbes

Harnessing the Power of the Crowd: Crowdsourcing in Product Design and Development

The pressure to innovate in the current business climate is exceptionally high. Competitive advantage through incremental improvement alone is no longer possible and organisations must consider new and disruptive approaches to product development in order to enhance their market position. Crowdsourcing has been described as one of these disruptive approaches, allowing organisations to expand their capability to innovate by involving and incorporating external knowledge. Despite high profile and successful examples of crowdsourcing, such as Procter and Gamble’s Connect and Develop and DARPA’s Network Challenge, academic literature on crowdsourcing in product development is still limited. Furthermore, crowdsourcing initiatives can fail in a number of ways including failing to attract enough responses or attracting poor-quality submissions. In this presentation, the existing state of crowdsourcing in academia is presented, along with the crowdsourcing challenges that face product development organisations and the proposed solutions. This presentation will also include a discussion on the future of work and the role crowdsourcing can play in the democratization of design, manufacture, and innovation.

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RUC-APS University of Liverpool Cross-Faculty Research Workshop

A cross-faculty RUC-APS project workshop on Wednesday 28th August. The workshop is titled “Current Challenges, Trends and Experiences for Enhancing Agriculture Value Chain Decisions under Uncertainty”.

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Risk Communication: Lying over raw milk

The Institute for Risk and Uncertainty at the University of Liverpool will host this second event in our three-part Raw Milk series. These day-long events are open to the public and feature invited speakers, proffered presentations and posters, session on collaborations and proposal opportunties, and open discussion on the advantages and risks of raw milk, use and misuse of statistics, consumer protection regulations, and the challenges of balancing costs and benefits in any decision.

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RiskCom Study Group

The Risk Institute is launching a risk communication study group (RiskCom), headed by Scott Ferson. We will be looking at ways in which risk and uncertainty can be communicated amongst the general population in many varied scenarios and applications. We are going to have approximately biweekly meetings starting on Thursday 1st August, 2pm. The meeting will likely take place in the seminar room although this is subject to change dependant on numbers.

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Institute for Risk and Uncertainty Spring School

Reliability Analysis. Will it work? Will it last?

This year’s spring school is a week-long short course and practicum on Reliability Analysis. It will feature a series of lectures presented by Professor Chandrasekhar Putcha (California State University Fullerton) and Mohamed Sallak (Université de Technologie de Compiègne). There will also be ancillary lectures and workshops by researchers from the Risk Institute.

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Cossanthon July 2019

A Hackfest dedicated to the development of the Cossan software

A Hackfest dedicated to the development of the Cossan software, organised in collaboration with the Institut für Risiko und Zuverlässigkeit and the Centre for Doctorate Training. This is an event open to all.

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LGBT+ in STEM

This event celebrates LGBT+ folk working within STEM fields, with an aim to promote visibility & representation whilst providing insight into the work done at the university.

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Thinkover: Humane Algorithms

Autonomous vehicles are just around the corner, and computers already make many of the important decisions in our daily lives. Yet algorithms can make serious errors and misjudgements. They have been accused of formalising racial bias and prejudice in social media and in the justice system itself. Facebook's algorithms seem to have swung recent elections. The computers on the Boeing 737 Max overrode human decisions in the disasters in the Java Sea and in Ethiopia. Can algorithms be designed to interact more smoothly with human users? What would a humane algorithm be? How should algorithms address diversity and uncertainty? How should they balance risks? Can algorithms be designed to recognise fairness in automated decision making? How could this even be assessed? Can they be designed to fail in ways that avoid catastrophic outcomes? This thinkover will focus on developing a useful definition for a humane algorithm, and a series of check points that will implement and make meaningful the definition in practical applications. The work will go into a conference presentation. All interested students and faculty members from all institutions, business people and industrialists are welcome to attend.

Collaborative Google site

Imprecise Tuesdays: Dominik Fahrner

Tidewater glacier change in Greenland: linear climate responses and application of machine learning Abstract: Greenlandic tidewater glaciers (TWGs) have been undergoing widespread retreat since the mid-1990s and contribute up to 50% of mass loss from the Greenland Ice Sheet (GrIS), though a comprehensive annual record of their retreat during the satellite age is currently lacking. We present a Greenland-wide data set of annual terminus positions for 220 TWGs for the period 1984-2017 based on Landsat 4-8/Sentinel 2 imagery (n = 3833). These were manually digitised using the Google Earth Engine Digitisation Tool (GEEDiT), and their changes quantified using the Margin Change Quantification Tool (MaQiT; Lea, 2018). Results were analysed alongside regional climate data, and with the supervised machine learning method Random Forests to determine the existence of threshold-type behaviour that may influence terminus stability. Our analysis highlights distinct linear trends in the regional response of TWG termini. The south-east, south-west and north-west regions are found to behave comparably (advance/stability until the mid-1990s followed by sustained retreat). However, in the north-east sustained retreat occurred since the mid-1980s, which then accelerated in 2008/2009. The generated data set enables the identification of regional linear trends of TWG behaviour for the first time and has allowed the application of Random Forests to determine the relative influence of climate forcings on termini positions.

Risk clinic: stochasticising a train control model
Hongbo Ye, School of Engineering, University of Liverpool

Abstract: Transportation engineers have created a Matlab code for controlling the movement of a train along its scheduled route for optimum efficiency, but their model is deterministic with no accounting for the stochastic variation in the passenger load or local weather conditions that influence performance. This thinkover will explore how we can edit the model within Matlab to take account of these stochastic factors to test and evaluate the movement controller in a more realistic setting

Downloadable Matlab files can be found here

Options and Opportunies for after your degree
Dr Alexis Nolan Webster

This lecture will provide an overview of the landscape of opportunities available to Ph.D. students in academia as well as industry to foster their career prospects. Also the dos and don'ts of editing a successful CV will be discussed.

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Liverpool Pint of Science 2019

Pint of Science returns to Liverpool for a third year, as part of an international, three-day festival that will see thousands of scientists simultaneously standing up and telling the public about their research in over 100 cities across 12 countries. Day three (Wednesday 22nd) features three speakers from the Risk Institute

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An evening of Fake News

"Fake News is a growing phenomenon, and, as Donald Trump himself said "Fake News has never been more voluminous or more inaccurate"... or did he? With social media giants and news corporations failing to stop the spread of incorrect information, it is now a daily feature in our lives, and here at the Risk Institute we think it’s about time we had a (free) pint and a discussion about just what Fake News is! Dr Paul Christiansen from the department of Psychology will start off the evening introducing the history of fake news, and our cognitive bias’s towards believing it. Next, James Butterworth from the department of Computer Science will talk about applications of Machine Learning in fake news, and finally Michael ‘Marsh’ Marshall from the Merseyside Skeptic Society will talk about what drives people to become part of a pseudoscientific movement, and in particular, the flat earth movement. Finally our event will come to a close with a Pub Quiz, - can you tell what’s fake and what’s real?"

Career advice: some important aspects
Michael Beer

Going for an academic career means to set out for a dynamic pathway with often unexpected obstacles and restrictions and also chances. Getting prepared early helps to reduce uncertainties and to increase chances significantly. The presentation will highlight a number of facts that are crucial for success but are often not considered or considered too late. It will be explained how to develop an impactful CV as a basis for applying for academic jobs worldwide. It will also be explained how applications are assessed, and how to prepare them to make the most imporatnt items clear to the panels and referees. This presentation is based on own experience in different academic systems and on experience from assessing applications and writing and assessing reference letters.

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Uncertainty quantification and management using cossan software

In collaboration with the Institute for Risk and Uncertainty (UK) and Institut für Risiko und Zuverlässigkeit (Germany), we are offering a 3-day training course on Uncertainty Quantification using COSSAN Software.

Each day focuses on a specific topic. This allows the participants to attend a specific training day.

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# Hashcode Solved 2019: A guide to algorithms and data structures for engineers
Jonathan Sadeghi

Google Hashcode is a competitive programming competition where the aim is to solve an algorithmic engineering challenge from Google in 4 hours, using a programming language of your choice. For the last 4 years the Risk Institute has entered teams into the competition and performed successfully. In each of these years we have encountered algorithmic challenges which are not commonly discussed in Engineering and non-computer science programming classes. The aim of this talk is to describe the solution to this year’s challenge (finding the optimal slideshow from a set of images, judged by a function provided by Google). We will discuss general tips for these types of coding competitions (and coding interviews!). The talk will be of interest to researchers who wish to learn more about high-dimensional optimisation problems which can’t be tackled with the more general numerical optimisation techniques, and students who wish to be well prepared for coding style interviews.

A multi-disciplinary approach to optimise flood mitigation strategies on road infrastructure in Hanoi, Vietnam

Vietnam is ranked globally as the country with fourth highest exposure to flooding. In Hanoi, Vietnam's capital city, flood risk is especially acute due to climate change, fast urbanisation and an aging drainage system. A social and economic impact assessment carried out in Hanoi during July 2018 showed that the most important flood impacts are felt along the city roads. This talk presents some preliminary findings of the GCRF-OSIRIS project, a Global Challenges Research Fund project funded by the British Academy's Cities and Infrastructure Programme. The projects aims at minimising the impact of floods on urban road networks over different flood scenarios by developing a multi-period optimisation model strategic, long-term planning of mitigation measures. Mitigation measures, such as lake rehabilitation and construction of manholes, can be implemented independently over a discrete planning horizon. The problem of identifying a schedule of interventions which minimises road infrastructure damage and congestion level during floods is formulated as a mixed-integer linear programming model and solved using a Greedy Randomised Adaptive Search Procedure (GRASP). Preliminary results on some randomly generated instances are presented. The proposed approach is then used empirically for investigating cost effective ways in which flood damage to road infrastructure can be mitigated in the City of Hanoi. the case study uses real data, flood scenarios and mitigation impact measures produced by the GCRF-OSIRIS inter-disciplinary research team which includes social scientists, climatologists, hydrologists, and transport economists. The talk concludes with a discussion of the challenges of working on GCRF projects and the numerous opportunities for OR researchers to contribute to the United Nation Sustainable Development Goals.

Some Advice on Scientific Publishing
Professor Gilbert Laporte

Professor Gilbert Laporte (Canada Research Chair in Distribution Management, HEC Montreal) will offer some advice on scientific publishing, with a strong emphasis on operational research papers. Examining the several components of a standard OR paper: title page, abstract, introduction, literature review, mathematical model, algorithm, computational results, conclusion acknowledgements and references. The talk will also touch on some aspects related to the submission and the revision processes.

How academic publishing works and how to raise your research profile
Sarah Roughley

This session will be split into two halves – the first section will provide an overview of the different publishing models that exist in scholarly publishing, specifically journal publishing, and the second section will look at the tools that are available to help you improve the visibility of your research including ORCID, Altmetric and social media.

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Simulating real-world uncertainty in the classroom-an entrepreneurial perspective

Contrary to popular belief, entrepreneurship is a process that can be learned, not only to create companies but to solve problems and to adopt an entrepreneurial mindset that views the world around us from a different perspective, where "We" (the entrepreneurs) realize and respond to a certain call-for-action. To do so, entrepreneurs need to be experts at navigating uncertainty and attempt to convert it to a strategic advantage. The board game “ESHIP - Navigating Uncertainty” was created to aid an entrepreneurial learning process where one could absorb the principles of navigating uncertainty in an implicit and thus an intuitive manner. The players can test their team-based decision-making abilities within the safe and risk-free environment of a game.

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Train (re)scheduling and speed profile design in rail management and operation
Dr. Hongbo Ye

An efficient rail system requires the trains to adhere to the timetables and the rail system itself to be able to mitigate the propagation of delay and recover from disruptions quickly. On the other hand, the energy efficiency is also a big concern for the railway managers and operators. In the day-to-day operation of the rail system, the punctuality and energy efficiency can be achieved by providing train drivers with sophisticatedly designed speed profiles to follow, while the delay and disruption can be managed via real-time rescheduling. This talk will provide a brief introduction on the planning, management, operation and control of the rail system, with a particular focus on rescheduling and speed profile design. In detail, it will introduce (i) the procedure of railway planning, (ii) the concept and modelling of train scheduling and rescheduling problems, (iii) a particular kind of rescheduling which deals with predictable disturbances such as adverse weather, (iv) the concept and modelling of train speed profile design problems, and (v) potential research directions related to uncertainties.

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Google Hashcode Hackathon

The Risk Institute will be hosting a hub for the Google Hashcode Hackathon in the Risk Institute Seminar Room. Everyone is welcome. The hackathon will take place on the 28th Feb starting at 17:30.

The Hashcode Hackathon is a competitive programming competition. You have 4 hours to write a program to process some data from Google, and produce a solution which will be scored by their system.

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Applications of Gaussian Process Regression in Uncertainty Quantification
Jinglai Li

Many complex engineering systems are often described by large-scale computer models. Quantifying uncertainty in such systems often requires a large number of simulations of such intensive computer models, which renders the total computational cost prohibitive. To this end, one possible solution is to construct some computationally efficient surrogate models of the systems and use them in the simulations. In this talk, we will discuss a popular surrogate model - the Gaussian Process regression, and the application of it in bot forward and inverse Uncertainty Quantification problems.

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Open Lecture Series: Jim Hall

As part of the Open Lecture Series, Professor Jim Hall FREng (Professor of Climate and Environmental Risks in the School of Geography and the Environment and a Senior Research Fellow in the Department of Engineering Science) will give a talk explaining the ITRC’s methodology for national infrastructure assessment and will explain how NISMOD is being used to assess options for infrastructure provision in Britain. His research focuses upon management of climate-related risks in infrastructure systems, in particular relating to various dimensions of water security, including flooding and water scarcity.

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Expert Elicitation Symposium

The Institute for Risk and Uncertainty of the University of Liverpool will host a two-day symposium on expert elicitation over 13-14 February 2019. We are hoping to develop some synoptic guidance for people who must address expert opinions in their quantitative risk assessments. There have recently been several prominent books on this topic from various quarters in the social, biological, and physical sciences, with rather divergent stories about best practices.

The event will consist of a number of proffered talks from distinguished meta-experts on the topic, and extensive expert panel discussions including the perspective from industrial and academic practitioners.

View the schedule here
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Should we use probability or imprecise probability for epistemic uncertainty?

In this workshop, we will discuss the benefits and disadvantages of two alternative expressions for epistemic uncertainty: precise probability and bounds on probability, including verbal encapsulations that encode uncertainty. The quantification will be demonstrated using open-source code for the R programming environment. We will then compare expressions from these two approaches and discuss them in light of research and principles of risk analysis. The workshop will also present research from risk communication literature and an overview of experiments comparing the success in communicating epistemic uncertainty by bounds or precise probability. The question we would like to answer is, when and why to use bounds or not? The workshop will explain and focus on the difference between aleatory and epistemic uncertainty. It will address two problems drawn from existing opinions, one with medium and one with weak background knowledge.

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Research Collaboration Meeting

This one day meeting will provide an opportunity for research active staff to meet potential collaborators from other departments. There will be presentations by group representatives from the School of Engineering and the Department of Mathematical Sciences, followed by structured discussion, and the chance to win funding to support a student summer internship to kick-start a collaborative research project.

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Dr Qian Fu

Understanding and predicting weather-related incidents on the rail network: case studies of wind- and heat-related incidents in GB context

The impacts of extreme weather events on railway operations are complex and in the most severe cases can cause significant disruption to the rail services, leading to delays for passengers and financial penalties to the industry.
This talk by Dr Quian Fu (Research Fellow, Birmingham Centre for Railway Research and Education, University of Birmingham) will focus on a prototype data model, which enables exploration of the underlying causal factors impacting on weather-related incidents on the rail network in GB context.

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Dr Michael Crichton

Wearable, Non-invasive or Continuous medical technologies: the other half of the puzzle

Currently we’re seeing an explosion in the popularity of wearable consumer electronics, which are leading many to question: Why is medical technology not making more use of these? One reason is that whilst our capacity in electronics is improving, our understanding of our body’s interface is still limited. In this presentation I will discuss the complexity of soft tissues and how their composite structure leads to many challenges but also opportunities for new medical technologies. In particular, I will look at how the material behaviour of skin and mucosal tissue provides a great location for sensor development. I will also discuss the development of a novel vaccination technology and how an understanding of skin’s mechanics positioned this technology for translation from basic research to clinical prototypes.

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Raw Milk Series

Risk Tradeoffs: Crying over Raw Milk

Humans depend on a diverse, protective microflora of bacteria. Some argue that pasteurisation of milk robs consumers of essential heath benefits. Others worry that raw milk can carry disease bacteria leading to illness or even death. Scientific evidence documents both benefits and risks associated with drinking raw milk, but public health authorities often emphasise on risks. Is this smart?

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An Overview of Smart Meter Load Forecasting Techniques
Hesham Al-Ammal

Hesham Al-Ammal teaches Computer Science at the University of Bahrain. He graduated with a BSc from KFUPM, Saudi Arabia; an MSc in Computer Science from Louisiana State University, USA; and a PhD in Computer Science from the University of Warwick, UK. He held several administrative positions at the University of Bahrain, including Director of the Quality Assurance Center (2008-2011), and Dean of the College of Information Technology (2011-2017). His research interests include: algorithms, cyber security, and data analytics.

The presentation will review the latest load forecasting techniques, in the context of different scale and horizons. Today, the competitive energy market demands more accurate forecasting at different scales, ranging from a single smart-meter (end-user) up to a whole power grid system. As a result of this market need, load forecasting is considered today as an essential part of the electricity industry’s planning process.
Load forecasting is not only important for the management of electricity’s generation, transmission, and distribution; but also, is crucial for consumers in order to optimize the use of their home electricity management systems. Although some past reviews investigate load forecasting, but a very few consider all possible scales and horizons. An up to date survey of load forecasting techniques will also will be presented by considering new trends such as distributed load forecasting, cloud computing techniques, real-time, and stream processing algorithms.
The is joint work with Sameem Abdul Kareem and Elham M. Eskandarnia, University of Malaya, Malaysia.

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Open Lecture Series: Gerd Gigerenzer

Gerd Gigerenzer is Director of the Harding Center for Risk Literacy at the Max Planck Institute for Human Development in Berlin. He is former Professor of Psychology at the University of Chicago and John M. Olin Distinguished Visiting Professor, School of Law at the University of Virginia. He is also Batten Fellow at the Darden Business School, University of Virginia, and Fellow of the Berlin-Brandenburg Academy of Sciences and the German Academy of Sciences. Awards for his work include the AAAS Prize for the best article in the behavioral sciences and the Association of American Publishers Prize for the best book in the social and behavioral sciences.

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EPSRC & ESRC Centre for Doctoral Training (CDT) - Annual Showcase Conference 2018

The Liverpool Institute for Risk and Uncertainty will host on campus the Annual Showcase Conference on Wednesday September 26th. This is supported by EPSRC & ESRC Centre for Doctoral Training (CDT). In this conference our Students will present their research progress to step up onto their PhD status. Further, there will be a poster competition open to all PhD students of the Risk Institute. This is an opportunity to see the current research pursued at the CDT and Institute for Risk and Uncertainty.

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Patrick Schwaferts

Imprecise Tuesdays: Robust Bayes Factor.

The Bayes Factor is a Bayesian tool for comparing two hypotheses, which is gaining popularity in psychological research and being suggested to replace classical t-tests. However, the Bayes Factor requires the specification of a prior distribution for the parameter of interest, which cannot be done unambiguously. In many situations, when further research is needed, information is not complete. This problem can be solved in the context of imprecise probabilities by using only the available (incomplete) knowledge. In this approach, a set of prior distributions is used instead of a single prior, yielding a set of Bayes Factor results, which is called the Robust Bayes Factor. In my talk, I will present the result of a project, in which the Bayes Factor was generalized to imprecise probabilities in a two-sample context with normally distributed data. The effect size between the two groups serves as parameter of interest and its prior was modeled as a set of normal distributions.

Liam Adamson

Imprecise Tuesdays: Minimisation of the effect of aleatory uncertainties on dynamic systems by active control using the method of receptances.

This paper presents a method to reduce the effect of uncertainties on dynamic systems by means of active control. In the proposed approach, pole placement is performed iteratively using an optimisation algorithm with an objective function that includes the variance of the real and imaginary part of each of the system’s pole. The method is advantageous in that control gains are calculated using the method of receptances, which eliminates model form uncertainty since only measured receptance data is used. Moreover, variances are extracted through a polynomial chaos expansion, which requires fewer samples as opposed to other techniques. The method is demonstrated numerically on a simple multi-degree-of-freedom system. It is shown that active control can be used in a way that not only places the poles of the system but also reduces their spread. Furthermore, it is shown that it is possible to directly relate uncertainty in the poles to meaningful physical based uncertainty in the structural parameters.

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The XXII IMEKO World Congress 2018 in Belfast

Risk related conferences: The XXII World Congress of the International Measurement Confederation (IMEKO)

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SIPTA Summer School

The 8th SIPTA Summer School took place in Oviedo (Spain) from 24 to 28 of July, 2018. It introduced both the main theoretical aspects of imprecise probability models and in particular belief functions, as well as their applications on machine learning, decision making and engineering. Leading specialists in these different aspects of imprecise probabilities gave lectures on the main concepts and techniques associated to their area of expertise, in a friendly environment favouring interaction between participants.

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REC2018

REC2018 was the eighth biennial meeting in the Reliable Engineering Computing series. Hosted by the Liverpool Institute for Risk and Uncertainty, the theme was "Computing with Confidence", bringing together engineers and scientists of all kinds from across industrial, academic and governmental institutions.

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Liverpool Pint of Science

Pint of Science returned to Liverpool for a second year, as part of an international, three-day festival that will see thousands of scientists simultaneously standing up and telling the public about their research in over 100 cities across 12 countries.

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Open Lecture Series: Risk - Perceptions Versus the Data

As part of the Open Lecture Series, Professor Richard Clegg (Foundation Chief Executive, Lloyd's Register) gives a talk which takes a sideways look at risk from the angle of public perceptions versus reality. It looks at the data behind the hazards and dangers we experience in everyday life, and the psychology of why we seem to accept and tolerate some risks but not others. The talk also compares risks by drawing analogies – for example how many bananas do you need to eat to get the same radiation dose from natural potassium-40 as you do from a dental X-ray?

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Open Lecture Series: "Debt strikes back" or the "Return of the Regulator"

As part of the Open Lecture Series, Alex Brazier (Director, Financial Stability Strategy and Risk (FSSR), Bank of England) gives a talk regarding economic risk.

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Open Lecture Series: The value of uncertainty in decision making: challenges and lessons learnt from addressing climate change

As part of the Open Lecture Series, Dr Veronica Bowman (Defence Science and Technology Laboratory) gives a talk providing an illustrative scenario examining the theoretical release and spread of a disease within a city, demonstrating both the challenges faced in such a complex scenario and sharing current best practice when communicating with decision makers.

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Open Lecture Series: Calculating and Communicating Uncertainty and Risk to Allow Informed Decision Making

As part of the Open Lecture Series, Professor Roger Street (University of Oxford) gives a talk on 'The value of uncertainty in decision making: challenges and lessons learnt from addressing climate change'.

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Uncertainty Quantification and Management Special Interest Group: High Value Manufacturing

The Study Group is an opportunity for industry to gain access to UK excellence in the fields of mathematics, statistics, engineering, and computer science. The structure of the Group allows for this to be done in a structured, intense session over three days.