Event

“Sensing and topology: some ideas by other people, and an early experiment” by Simon Dobson

Abstract
The core problem in many sensing applications is that we’re trying to
infer high-resolution information from low-resolution observations —
and keep our trust in this information as the sensors degrade. How can
we do this in a principled way? There’s an emerging body of work on
using topology to manage both sensing and analytics, and in this talk I
try to get a handle on how this might work for some of the problems
we’re interested in. I will present an experiment we did to explore
these ideas, which highlights some fascinating problems.

Event details

  • When: 30th November 2017 13:00 - 14:00
  • Where: Cole 1.33a
  • Series: Systems Seminars Series
  • Format: Seminar

Edgar Chavez (CICESE): The Metric Approach to Reverse Searching (School Seminar)

Abstract:
Searching for complex objects (e.g. images, faces, audio or video), is an everyday problem in computer science, motivated by many applications. Efficient algorithms are demanded for reverse searching, also known as query by content, in large repositories. Current industrial solutions are ad hoc, domain-dependant, hardware intensive and have limited scaling. However, those disparate domains can be modelled, for indexing and searching, as a metric space. This model has been championed to become a solution to generic proximity searching problems. In practice, however, the metric space approach has been limited by the amount of main memory available.

In this talk we will explore the main ideas behind this technology, present a successful example in audio indexing and retrieval. The application scales well for large amounts of audio because the representation is quite compact and the full audio streams are not needed for indexing and searching.

Speaker Bio:
Edgar Chavez received his Phd from the Center for Mathematical Research in Guanajuato, Mexico in 1999. He founded the information retrieval group at Universidad Michoacana where he worked until 2012. After a brief period in the Institute of Mathematics in UNAM, he joined the computer science department in CICESE in 2013, where he founded the data science group. His main research interest include access and retrieval of data and data representation, such as fingerprints and point clouds. In 2009 he obtained the Thompson-Reuters award for having the most cited paper in computer science in Mexico and Latin America. In 2008 he co-funded, with Gonzalo Navarro, the conference Similarity Search and Applications, which is an international reference in the area. He has published more than 100 scientific contributions, with about 3500 citations in google scholar.

Event details

  • When: 5th December 2017 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

Bidirectional-Curious? – Dr. Conor McBride

Type systems are often presented in a declarative style, but with an emphasis on ensuring that there is some sort of type synthesis algorithm. Since Pierce and Turner’s “Local Type Inference” system, however, there has been a small but growing alternative: bidirectional typing, where types are synthesized for variables and elimination forms, but must always be proposed in advance for introduction forms and checked. You can still get away without any type annotations, as long as you write only normal forms. But where’s the fun in that? If you want to write terms that compute, you need to write type annotations at exactly the point where an introduction form collides with its elimination form, showing exactly the type at which computation is happening.

For type systems with some sorts of value dependency, the bidirectional approach seriously cuts down on the amount of annotation required in terms, needed only to achieve type synthesis. We have a real opportunity to reduce clutter and also to give a clearer account of the connections between types and computation.

But it doesn’t stop there. A disciplined approach to the construction of bidirectional type systems makes it easier to get their metatheory right. I’ll show this by reconstructing Martin-Löf’s 1971 type theory (the inconsistent one) in a bidirectional style and show why it has type
preservation, even without normalization.

Event details

  • When: 22nd November 2017 13:00 - 14:30
  • Where: Cole 1.33b
  • Format: Talk

Computational Approaches for Accurate, Automated and Safe Cancer Care – HIG Seminar

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.

Event details

  • When: 22nd November 2017 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: HIG Seminar Series
  • Format: Seminar

SRG Seminar: “Interactional Justice vs. The Paradox of Self-Amendment and the Iron Law of Oligarchy” by Jeremy Pitt

Self-organisation and self-governance offer an effective approach to resolving collective action problems in multi-agent systems, such as fair and sustainable resource allocation. Nevertheless, self-governing systems which allow unrestricted and unsupervised self-modification expose themselves to several risks, including the Suber’s paradox of self-amendment (rules specify their own amendment) and Michel’s iron law of oligarchy (that the system will inevitably be taken over by a small clique and be run for its own benefit, rather than in the collective interest). This talk will present an algorithmic approach to resisting both the paradox and the iron law, based on the idea of interactional justice derived from sociology, and legal and organizational theory. The process of interactional justice operationalised in this talk uses opinion formation over a social network with respect to a shared set of congruent values, to transform a set of individual, subjective self-assessments into a collective, relative, aggregated assessment.

Using multi-agent simulation, we present some experimental results about detecting and resisting cliques. We conclude with a discussion of some implications concerning institutional reformation and stability, ownership of the means of coordination, and knowledge management processes in ‘democratic’ systems.

Biography
Photograph of Professor Jeremy Pitt
Jeremy Pitt is Professor of Intelligent and Self-Organising Systems in the Department of Electrical & Electronic Engineering at Imperial College London, where he is also Deputy Head of the Intelligent Systems & Networks Group. His research interests focus on developing formal models of social processes using computational logic, and their application in self-organising multi-agent systems, for example fair and sustainable common-pool resource management in ad hoc and sensor network. He also has strong interests in human-computer interaction, socio-technical systems, and the social impact of technology; with regard to the latter he has edited two books, This Pervasive Day (IC Press, 2012) and The Computer After Me (IC Press, 2014). He has been an investigator on more than 30 national and European research projects and has published more than 150 articles in journals and conferences. He is a Senior Member of the ACM, a Fellow of the BCS, and a Fellow of the IET; he is also an Associate Editor of ACM Transactions on Autonomous and Adaptive Systems and an Associate Editor of IEEE Technology and Society Magazine.

Event details

  • When: 15th November 2017 13:00 - 14:00
  • Where: Cole 1.33a
  • Series: Systems Seminars Series
  • Format: Seminar

“Ambient intelligence with sensor networks” by Lucas Amos and “Location, Location, Location: Exploring Amazon EC2 Spot Instance Pricing Across Geographical Regions” by Nnamdi Ekwe-Ekwe

Lucas’s abstract

“Indoor environment quality has a significant effect on worker productivity through a complex interplay of factors such as temperature, humidity and levels of Volatile Organic Compounds (VOCs).

In this talk I will discuss my Masters project which used off the shelf sensors and Raspberry Pis to collect environmental readings at one minute intervals throughout the Computer Science buildings. The prevalence of erroneous readings due to sensor failure and the strategy used for the identification and correction of such faults will be presented. Identifiable correlations between environmental variables and attempts to model these relationships will be discussed

Past studies identifying the ideal environmental conditions for human comfort and productivity allow for the objective assessment of indoor environmental conditions. An adaptation of Frešer’s environment rating system will be presented, showing how VOC levels can be incorporated into assessments of environment quality and how this can be communicated to building users.”

Nnamdi’s abstract

“Cloud computing is becoming an almost ubiquitous part of the computing landscape. For many companies today, moving their entire infrastructure and workloads to the cloud reduces complexity, time to deployment, and saves money. Spot Instances, a subset of Amazon’s cloud computing infrastructure (EC2), expands on this. They allow a user to bid on spare compute capacity in Amazon’s data centres at heavily discounted prices. If demand was ever to increase such that the user’s maximum bid is exceeded, their compute instance is terminated.

In this work, we conduct one of the first detailed analyses of how location affects the overall cost of deployment of a spot instance. We simultaneously examine the reliability of pricing data of a spot instance, and whether a user can be confident that their instance has a low risk of termination.

We analyse spot pricing data across all available Amazon Web Services regions for 60 days on a variety of instance types. We find that location does play a critical role in spot instance pricing and also that pricing differs depending on the granularity of the location – from a more coarse-grained AWS region to a more fine-grained Availability Zone within a region. We relate the pricing differences we find to the price’s stability, confirming whether we can be confident in the bid prices we make.

We conclude by showing that it is very possible to run workloads on Spot Instances achieving
both a very low risk of termination as well as paying very low amounts per hour.”

Event details

  • When: 9th November 2017 13:00 - 14:00
  • Where: Cole 1.33a
  • Series: Systems Seminars Series
  • Format: Seminar

Towards Refinement by Resolution in Dependent Type Theory – František Farka

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.

Event details

  • When: 9th November 2017 12:00 - 13:00
  • Where: Cole 1.33b
  • Format: Talk

SACHI Seminar: Alix Goguey (University of Saskatchewan) – Augmenting touch expressivity to improve the touch modality

 

Title

Augmenting touch expressivity to improve the touch modality

Abstract

During the last decades, touch surfaces have become more and more ubiquitous. Whether on tablets, on smartphones or on laptops, touch surfaces are used by a majority of us on a daily basis. However, the limited expressivity – the different channels used to convey information to the system – of the touch modality restricts drastically the amount of features that can be controlled via touch only. For instance, a typical smartphone touchscreen only provides the absolute position of a contact on the screen, thus applications usually offer only one way to carry out tasks (which can augment user frustration or cap performances) or restrict possibilities (e.g. Photoshop on desktop offers more than 600 commands but only about 40 on smartphones and tablets). In this talk, I will present an overview of my on-going research and discuss different ways to tackle this problem, augment touch expressivity and user efficiency: from tools that helps better designing touch interfaces to the use of new input dimensions in original interaction techniques.

Speaker biography

Alix Goguey is a post postdoctoral fellow working with Carl Gutwin in the Interaction Lab at the University of Saskatchewan, Canada. He received his Ph.D. in Computer Science in October 2016 in the Mjolnir research group at Inria Lille – Nord Europe, France, under the supervision of Géry Casiez. His work focuses on understanding and designing interaction techniques on touch input devices and particularly through the use of new information such as finger identification. To learn more about Alix’s work: www.alixgoguey.fr

Event details

  • When: 1st November 2017 13:15 - 14:15
  • Where: Honey 103 - GFB
  • Format: Seminar