Registration is open for the next Software Carpentry workshop in St Andrews on September 23-24 in the Parliament Hall. We will teach UNIX shell, version control with Git and programming with Python. Please see the workshop page for further details and the link to registration via PDMS.
A SICSA Education workshop on Learning Analytics for Improving Evidence-based Teaching will be organised in St Andrews during summer 2018 by Dr Kasim Terzic.
Modern external beam radiation therapy techniques allow the design of highly conformal radiation treatment plans that permit high doses of ionsing radition to be delivered to the tumour in order to eradicate cancer cells while sparing surrounding normal tissue. However, since it is difficult to avoid irradiation of normal tissue altogether and ionising radiation also damages normal cells, patients may develop radiation-induced toxicity following treatment. Furthermore, the highly conformal nature of the radiation treatment plans makes them particularly susceptible to geometric or targeting uncertainties in treatment delivery. Geometric uncertainties may result in under-dosage of the tumour leading to local tumour recurrence or unacceptable morbidity from over-dosage of neighbouring healthy tissue.
I will present work in three areas that bear directly on treatment accuracy and safety in radiation oncology. The first area addresses the development of automated image registration algorithms for image-guided radiation therapy with the aim of improving the accuracy and precision of treatment delivery. The registration methods I will present are based on statistical and spectral models of signal and noise in CT and x-ray images. The second part of my talk addresses the identification of predictors of normal tissue toxicity after radiation therapy and the study of the spatial sensitivity of normal tissue to dose. I will address the development of innovative methods to accurately model the spatial characteristics of radiation dose distributions in 3D and results of the analysis of this important, but heretofore lacking, information as a contributing factor in the development of radiation-induced toxicity. Finally, given the increasing complexity of modern radiation treatment plans and a trend towards an escalation in prescribed doses, it is important to implement a safety system to reduce the risk of adverse events arising during treatment and improve clinical efficiency. I will describe ongoing efforts to formalise and automate quality assurance processes in radiation oncology.
Biography
Reshma Munbodh is currently an Assistant Professor in the Department of Diagnostic Imaging and Therapeutics at UConn Health. She received her undergraduate degree in Computer Science and Electronics from the University of Edinburgh and her PhD in medical image processing and analysis applied to cancer from Yale University. Following her PhD, she performed research and underwent clinical training in Therapeutic Medical Physics at the Memorial Sloan-Kettering Cancer Center. She is interested in the development and application of powerful analytical and computational approaches towards improving the diagnosis, understanding and treatment of cancer. Her current projects include the development of image registration algorithms for image-guided radiation therapy, the study of normal tissue toxicity following radiation therapy, longitudinal studies of brain gliomas to monitor tumour progression and treatment response using quantitative MRI analysis and the formalisation and automation of quality assurance processes in radiation oncology.
Abstract
Dependent types are increasingly used in functional programming languages. The surface syntax of dependent types, as seen by a programmer, is elaborated by a compiler into an internal, type-theoretic representation. In order to perform this step, the compiler needs to infer a nontrivial amount of information to successfully type-check the internal representation. This process—type refinement—is complex, implementation dependent, and very few formal developments currently exist. We discuss a novel and simpler formalisation of type refinement in first order type theory with dependent types. We propose a translation of type-refinement problems to Horn-Clause logic with explicit proof-terms, using proof-relevant resolution as the type inference mechanism.
Adam Barwell (adb23) will be presenting a summary of his recently submitted thesis.
Problem structure, or linkage, refers to the interaction between variables in a black-box fitness function. Discovering structure is a feature of a range of search algorithms that use structural models at each iteration to determine the trajectory of the search. Examples include Information Geometry Optimisation (IGO), Covariance Matrix Adaptation Evolution Strategy (CMA-ES), Bayesian Evolutionary Learning (BEL) and Estimation of Distribution Algorithms (EDA).
In particular, EDAs use probabilistic graphical models to represent structure learned from evaluated solutions. Various EDA approaches using trees, directed acyclic graphs and undirected graphs have been developed and evaluated on a range of benchmarks with a variety of representations.
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The school’s Athen SWAN charter is now on our main website.
Ian Sommerville has been appointed Emeritus Professor in the School of Computer Science. Ian retired earlier this year following an illustrious career. From the Emeritus Tribute presented to Academic Council,
Ian Sommerville is one of the leading academic Software Engineers in the world, and very possibly the leading educator in the field. In his own words, “Software engineering is an engineering discipline that is concerned with all aspects of software production.” His career has been dedicated to solving problems within Software Engineering, and teaching others this exciting modern discipline. While being a Professor of Computer Science, Ian always describes himself proudly as an engineer rather than a computer scientist.
The timetables for Semester 1 2014-2015 are available here:
Dr. Roy Dyckhoff will give a talk titled, “Geometrisation of first-order logic”.
Abstract:
We show that every first-order theory T has a conservative extension G_T that is a geometric theory. Reasoning problems in T can therefore be replaced by problems in G_T, where the methods of geometric (aka ‘coherent’) logic are applicable. We discuss related work by Skolem (1920), Antonius (1975), Bezem and Coquand (2005), Fisher (2007–..), Polonsky (2011) and Mints (2012).
(A formula is **positive** iff built from atoms using \exists, \land and \lor. A **geometric implication** is the universal quantification of a formula C -> D where C and D are positive. A theory is **geometric** iff axiomatised by geometric implications. Lots of mathematical theories are geometric. Reasoning in a geometric theory usually avoids the unnatural conversions of resolution-based theorem proving, and produces intuitionistically sound proofs)
Joint work with Sara Negri (Helsinki).
