Kevin is the founder and CEO of RunRev, overseeing a global team and development of the Rev programming language.
This seminar has been postponed due to Kevin’s work commitments. A new date will be announced in due course.
Monty Widenius delivered the Semester 1 Distinguished Lecture Series on Monday 15th October 2012, from 10am to 3.30pm, in Upper College Hall.
Monty is CEO & CTO at Monty Program Ab, and is perhaps best known as founder of MySQL, the world’s most used open source.
Monty delivered three lectures on MySQL and Open Source Business. He has kindly made the slides available – linked to from the titles.
The lectures were introduced by the Dean of Science, Prof Al Dearle, and refreshments were provided at 11am.
These lectures were open to all.
The detailed programme is available as a pdf: Monty Widenius DLS Programme
Reverend Bayes, meet Countess Lovelace: Probabilistic Programming for Machine Learning
Andrew D. Gordon, Microsoft Research and University of Edinburgh
Abstract: We propose a marriage of probabilistic functional programming with Bayesian reasoning. Infer.NET Fun turns the simple succinct syntax of F# into an executable modeling language – you can code up the conditional probability distributions of Bayes’ rule using F# array comprehensions with constraints. Write your model in F#. Run it directly to synthesize test datasets and to debug models. Or compile it with Infer.NET for efficient statistical inference. Hence, efficient algorithms for a range of regression, classification, and specialist learning tasks derive by probabilistic functional programming.
Bio: Andy Gordon is a Principal Researcher at Microsoft Research Cambridge, and is a Professor at the University of Edinburgh. Andy wrote his PhD on input/output in lazy functional programming, and is the proud inventor of Haskell’s “>>=” notation for monads. He’s worked on a range of topics in concurrency, verification, and security, never straying too far from his roots in functional programming. His current passion is deriving machine learning algorithms from F# programs.
Mobility in vivo
Barry Brown, Co-director Mobile Life, University of Stockholm
barbro.tumblr.com
The Mobile VINN Excellence Centre
Abstract
Despite the widespread use of mobile devices, details of mobile technology use ‘in the wild’ have proven difficult to collect. For this study we uses video data to gain new insight into the use of mobile computing devices. Screen-captures of smartphone use, combined with video recordings from wearable cameras, allow for the analysis of the detail of device use in a variety of activity and settings. We use this data to describe how mobile device use is threaded into other co-present activities, focusing on the use of maps and internet searches to support users on a day-trip. Close analysis of the video data reveals novel aspects of how gestures are used on touch screens, in that they form a resource for the ongoing coordination of joint action. We go on to describe how the local environment and information in the environment are combined to guide and support action. In conclusion, we argue for the mobility of mobile devices being as much about this interweaving of activity and device use, as it is about physical portability.
Speaker: Laurel Riek, University of Notre Dame
Title: Facing Healthcare’s Future: Designing Facial Expressivity for Robotic Patient Mannequins
Abstract:
In the United States, there are an estimated 98,000 people per year killed and $17.1 billion dollars lost due to medical errors. One way to prevent these errors is to have clinical students engage in simulation-based medical education, to help move the learning curve away from the patient. This training often takes place on human-sized android robots, called high-fidelity patient simulators (HFPS), which are capable of conveying human-like physiological cues (e.g., respiration, heart rate). Training with them can include anything from diagnostic skills (e.g., recognizing sepsis, a failure that recently killed 12-year-old Rory Staunton) to procedural skills (e.g., IV insertion) to communication skills (e.g., breaking bad news). HFPS systems allow students a chance to safely make mistakes within a simulation context without harming real patients, with the goal that these skills will ultimately be transferable to real patients.
While simulator use is a step in the right direction toward safer healthcare, one major challenge and critical technology gap is that none of the commercially available HFPS systems exhibit facial expressions, gaze, or realistic mouth movements, despite the vital importance of these cues in helping providers assess and treat patients. This is a critical omission, because almost all areas of health care involve face-to-face interaction, and there is overwhelming evidence that providers who are skilled at decoding communication cues are better healthcare providers – they have improved outcomes, higher compliance, greater safety, higher satisfaction, and they experience fewer malpractice lawsuits. In fact, communication errors are the leading cause of avoidable patient harm in the US: they are the root cause of 70% of sentinel events, 75% of which lead to a patient dying.
In the Robotics, Health, and Communication (RHC) Lab at the University of Notre Dame, we are addressing this problem by leveraging our expertise in android robotics and social signal processing to design and build a new, facially expressive, interactive HFPS system. In this talk, I will discuss our efforts to date, including: in situ observational studies exploring how individuals, teams, and operators interact with existing HFPS technology; design-focused interviews with simulation center directors and educators which future HFPS systems are envisioned; and initial software prototyping efforts incorporating novel facial expression synthesis techniques.
Biography:
Dr. Laurel Riek is the Clare Boothe Luce Assistant Professor of Computer Science and Engineering at the University of Notre Dame. She directs the RHC Lab, and leads research on human-robot interaction, social signal processing, facial expression synthesis, and clinical communication. She received her PhD at the University of Cambridge Computer Laboratory, and prior to that worked for eight years as a Senior Artificial Intelligence Engineer and Roboticist at MITRE.
Room 1.33a at 2:00 pm on Friday 7th September 2012
Abstract:
In the field of natural language parsing, the syntax of natural languages is
modeled by means of formal grammars and automata. Sometimes these formalisms
are borrowed from the field of formal language theory and are adapted to the
task at hand, as in the case of context-free grammars and their lexicalized
versions, where each individual rule is specialized for one or more lexical
items. Sometimes these formalisms are newly developed, as in the case of
dependency grammars and tree adjoining grammars. In this talk, I will
briefly overview several of these models, discussing their mathematical
properties and their use in parsing of natural language.
Seminar by Dr Apu Kapadia, Indiana University
We introduce Soundcomber, a “sensory malware” for smartphones that
uses the microphone to steal private information from phone
conversations. Soundcomber is lightweight and stealthy. It uses
targeted profiles to locally analyze portions of speech likely to
contain information such as credit card numbers. It evades known
defenses by transferring small amounts of private data to the malware
server utilizing smartphone-specific covert channels. Additionally, we
present a general defensive architecture that prevents such sensory
malware attacks.
Speaker: Helen Purchase, University of Glasgow
Title: An Exploration of Interface Visual Aesthetics
Abstract:
The visual design of an interface is not merely an ‘add-on’ to the functionality provided by a system: it is well-known that it can affect user preference, engagement and motivation, but does it have any effect on user performance? Can the efficiency or effectiveness of a system be improved by its visual design? This seminar will report on experiments that investigate whether any such effect can be quantified and tested. Key to this question is the definition of an unambiguous, quantifiable characterisation of an interface’s ‘visual aesthetic’: ways in which this could be determined will be discussed.
About Helen:
Dr Helen Purchase is Senior Lecturer in the School of Computing Science at the University of Glasgow. She has worked in the area of empirical studies of graph layout for several years, and also has research interests in visual aesthetics, task-based empirical design, collaborative learning in higher education, and sketch tools for design. She is currently writing a book on empirical methods for HCI research.
Systems Seminar – by John Thomson
All wecome.
The Results Delusion
Abstract:
It is often said that any subject which requires the word ‘science’ to be placed somewhere in its name, is unlikely to be very scientific. This is unfortunately far too true for systems research in general. Every systems conference, papers are presented which show significant speedups over previous approaches to problem X, but these improvements are rarely replicated in output from industry. Why? The unpalatable answer is that a significant amount of systems research is the result of self-delusion, bad science and, I suspect occasionally, fraud.
Standards of scientific rigour in CS often fall well below what would be taken for granted in other sciences – particularly with regard to measurement of results, statistical analysis and replicability of results. I would like to do something about this, and will be presenting the idea for a new CS journal, which focuses on this exact problem. Oh, and peer review is gone too! Pitfalls abound. Would love to hear your comments, objections and advice.
Abstract: In this talk I will present some of the work being done in the new Inference, Dynamics, and Interaction group, at the University of Glasgow. In particular, we are interested in using probabilistic inference to improve interaction technology on handheld devices (particularly with touch screens).
I will show how we are using sequential Monte-Carlo techniques to infer distributions over user inputs which can be (1) augmented with applications to provide a smooth handover of control between the human and device and (2) used to extract additional information regarding touch interactions and subsequently improve touch accuracy.
There is a short bio on my webpage:
http://www.dcs.gla.ac.uk/~srogers
