Distinguished Lecture Series: Formal Approaches to Quantitative Evaluation

Event details

  • When: 8th April 2019 09:30 - 15:30
  • Where: Lower College Hall
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

Biography:
Jane Hillston was appointed Professor of Quantitative Modelling in the School of Informatics at the University of Edinburgh in 2006, having joined the University as a Lecturer in Computer Science in 1995. She is currently Head of the School of Informatics. She is a Fellow of the Royal Society of Edinburgh and Member of Academia Europaea. She currently chairs the Executive Committee of the UK Computing Research Committee.
Jane Hillston’s research is concerned with formal approaches to modelling dynamic behaviour, particularly the use of stochastic process algebras for performance modelling and stochastic verification. The application of her modelling techniques have ranged from computer systems, to biological processes and transport systems. Her PhD dissertation was awarded the BCS/CPHC Distinguished Dissertation award in 1995 and she was the first recipient of the Roger Needham Award in 2005. She has published over 100 journal and conference papers and held several Research Council and European Commission grants.
She has a strong interest in promoting equality and diversity within Computer Science; she is a member of the Women’s Committee of the BCS Computing Academy and chaired the Women in Informatics Research and Education working group of Informatics Europe 2016—2018, and during that time instigated the Minerva Informatics Equality Award.

Formal Approaches to Quantitative Evaluation
Qualitative evaluation of computer systems seeks to ensure that the system does not exhibit bad behaviour and is in some sense “correct”. Whilst this is important it is also often useful to be able to reason not just about what will happen in the system, but also the dynamics of that behaviour: how long it will take, what are the probabilities of alternative outcomes, how much resource is used….? Such questions can be answered by quantitative analysis when information about timing and probability are incorporated into models of system behaviour.

In this short series of lectures I will talk about how we can extend formal methods to support quantitative evaluation as well as qualitative evaluation of systems. The first lecture will focus on computer systems and a basic approach based on the stochastic process algebra PEPA. In the second lecture I will introduce the language CARMA which is designed to support the analysis of collective adaptive systems, in which the structure of the system may change over time. In the third lecture I will consider systems where the exact details of behaviour may not be known and present the process algebra ProPPA which combines aspect of machine learning and inference with formal quantitative models.

Timetable:
Lecture 1: 9:30 – 10:30 – Performance Evaluation Process Algebra (PEPA)
Coffee break at 10:30 – 11:15
Lecture 2: 11:15 – 12:15 – Collective Adaptive Resource-sharing Markovian Agents (CARMA)
Lecture 3: 14:15 – 15:15 – Probabilistic Programming for Stochastic Dynamical Systems (ProPPA)
Venue: Upper and Lower College Halls

DLS: Scalable Intelligent Systems by 2025 (Carl Hewitt)

Event details

  • When: 13th November 2018 09:30 - 15:30
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

Venue: The Old Course Hotel (Hall of Champions)

Timetable:

9:30 Lecture 1
10:30 Break with Coffee
11:15 Lecture 2
12:15 Break for Lunch (not provided)
14:15 Lecture 3
15:15 Discussion

Lecture 1: Introduction to Scalable Intelligent Systems

Lecture 2: Foundations for Scalable Intelligent Systems

Lecture 3: Implications of Scalable Intelligent Systems

Speaker Bio:

Professor Carl Hewitt is the creator (together with his students and other colleagues) of the Actor Model of computation, which influenced the development of the Scheme programming language and the π calculus, and inspired several other systems and programming languages. The Actor Model is in widespread industrial use including eBay, Microsoft, and Twitter. For his doctoral thesis, he designed Planner, the first programming language based on pattern-invoked procedural plans.

Professor Hewitt’s recent research centers on the area of Inconsistency Robustness, i.e., system performance in the face of continual, pervasive inconsistencies (a shift from the previously dominant paradigms of inconsistency denial and inconsistency elimination, i.e., to sweep inconsistencies under the rug). ActorScript and the Actor Model on which it is based can play an important role in the implementation of more inconsistency-robust information systems. Hewitt is an advocate in the emerging campaign against mandatory installation of backdoors in the Internet of Things.

Hewitt is Board Chair of iRobust™, an international scientific society for the promotion of the field of Inconsistency Robustness. He is also Board Chair of Standard IoT™, an international standards organization for the Internet of Things, which is using the Actor Model to unify and generalize emerging standards for IoT. He has been a Visiting Professor at Stanford University and Keio University and is Emeritus in the EECS department at MIT.

Abstract:

A project to build the technology stack outlined in these lectures can bring Scalable Intelligent Systems to fruition by 2025. Scalable Intelligent Systems have the following characteristics:

  • Interactively acquire information from video, Web pages, hologlasses, online data bases, sensors, articles, human speech and gestures, etc.
  • Real-time integration of massive pervasively inconsistent information
  • Scalability in all important dimensions meaning that there are no hard barriers to continual improvement in the above areas
  • Close human collaboration with hologlasses for secure mobile interaction. Computers alone cannot implement the above capabilities
  • No closed-form algorithmic solution is possible to implement the above capabilities

Technology stack for Scalable Intelligent Systems is outlined below:

  • Experiences Hologlasses: Collaboration, Gestures, Animations, Video
  • Matrix Discourse, Rhetoric, and Narration
  • Citadels No single point of failure
  • Massive Inconsistency Robust Ontology Propositions, Goals, Plans, Descriptions, Statistics, Narratives
  • Actor Services Hardware and Software
  • Actor Many Cores Non-sequential, Every-word-tagged, Faraday cage Crypto, Stacked Carbon Nanotube

For example, pain management could greatly benefit from Scalable Intelligent Systems. Complexities of dealing with pain have led to the current opioid crisis. According to Eric Rodgers, PhD., director of the VA’s Office of Evidence Based Practice:

“The use of opioids has changed tremendously since the 1990s, when we first started formulating a plan for guidelines. The concept then was that opioid therapy was an underused strategy for helping our patients and we were trying to get our providers to use this type of therapy more. But as time went on, we became more aware of the harms of opioid therapy and the development of pill mills. The problems got worse.

It’s now become routine for providers to check the state databases to see if there’s multi-sourcing — getting prescriptions from other providers. Providers are also now supposed to use urine drug screenings and, if there are unusual results, to do a confirmation. [For every death from an opioid overdose] there are 10 people who have a problem with opioid use disorder or addiction. And for every addicted person, we have another 10 who are misusing their medication.”

Pain management requires much more than just prescribing opioids, which are often critical for short-term and less often longer-term use. [Coker 2015; Friedberg 2012; Holt 2017; Marchant 2017; McKinney 2015; Spiegel 2018; Tedesco, et. al. 2017; White 2017] Organizational aspects play an important role in pain management. [Fagerhaugh and Strauss 1977]

DLS: Functional Foundations for Operating Systems

Event details

  • When: 13th February 2018 09:30 - 15:15
  • Where: Byre Theatre
  • Series: Distinguished Lectures Series, Systems Seminars Series
  • Format: Distinguished lecture

Biography: Dr. Anil Madhavapeddy is a University Lecturer at the Cambridge Computer Laboratory, and a Fellow of Pembroke College where he is Director of Studies for Computer Science. He has worked in industry (NetApp, Citrix, Intel), academia (Cambridge, Imperial, UCLA) and startups (XenSource, Unikernel Systems, Docker) over the past two decades. At Cambridge, he directs the OCaml Labs research group which delves into the intersection of functional programming and systems, and is a maintainer on many open source projects such as OpenBSD, OCaml, Xen and Docker.

Timetable
9:30: Introduction by Professor Saleem Bhatti
9:35: Lecture 1
10:35: Break with tea and coffee
11:15: Lecture 2
12:15: Lunch (not provided)
14:00: Lecture 3
15:00: Close by Professor Simon Dobson

Lecture 1: Rebuilding Operating Systems with Functional Principles
The software stacks that we deploy across computing devices in the world are based on shaky foundations. Millions of lines of C code crammed into monolithic operating system kernels, mixed with layers of scheduling logic, wrapped in a hypervisor, and served with a dose of nominal security checking on the side. In this talk, I will describe an alternative approach to constructing reliable, specialised systems with a familiar developer experience. We will use modular functional programming to build several services such as a secure web server that have no reliance on conventional operating systems, and explain how to express their logic in a high level, functional fashion. By the end of it, everyone in the audience should be able to build their own so-called unikernels!

Lecture 2: The First Billion Real Deployments of Unikernels
Unikernels offer a path to a more sane basis for driving applications on hardware, but will they ever be adopted for real? For the past fifteen years, an intrepid group of adventurers have been developing the MirageOS application stack in the OCaml programming language. Along the way, it has been deployed in many unusual industrial situations that I will describe in this talk, starting with the Docker container stack, then moving onto the Xen hypervisor that drives billions of servers worldwide. I will explain the challenges of using functional programming in industry, but also the rewards of seeing successful deployments quietly working in mission-critical areas of systems software.

Lecture 3: Programming the Next Trillion Embedded Devices
The unikernel approach of compiling highly specialised applications from high-level source code is perfectly suited to programming the trillions of embedded devices that are making their way around the world. However, this raises new challenges from a programming language perspective: how can we run on a spectrum of devices from the very tiny (with just kilobytes of RAM) to specialised hardware? I will describe the new frontier of functional metaprogramming (programs which generate more programs) that we are using to compile a single application to many heterogenous devices, and a Git-like model to coordinate across thousands of nodes. I will conclude with by motivating the need for a next-generation operating system to power new exciting applications such as augmented and virtual reality in our situated environments, and remove the need for constant centralised coordination via the Internet.

DLS: What Every Computer Scientist Should Know About Computer History

Event details

  • When: 10th October 2017 09:30 - 16:00
  • Where: Byre Theatre
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

What Every Computer Scientist Should Know About Computer History

Prof Ursula Martin

Update: Lectures will be live streamed at this link.

Distinguished Lecture Series, Semester 1, 2017-18

Biography:

Professor Ursula Martin CBE FREng FRSE joined the University of Oxford as Professor of Computer Science in 2014, and is a member of the Mathematical Institute.  She holds an EPSRC Established Career Fellowship, and a Senior Research Fellowship at Wadham College. Her research, initially in algebra, logic and the use of computers to create mathematical proofs, now focuses on wider social and cultural approaches to understanding the success and impact of current and historical computer science research.

Prof Ursula Martin

Prof Ursula Martin

Before joining Oxford she worked at  Queen Mary University of London, where she was Vice-Principal for Science and Engineering (2005-2009), and Director of the impactQM project (2009-2012), an innovative knowledge transfer initiative. She serves on numerous international committees, including the Royal Society’s Diversity Committee and the UK Defence Science Advisory Council.  She worked  at the University of St Andrews from 1992 – 2002, as only its second female professor, and its first in over 50 years. She holds an MA in Mathematics from Cambridge, and a PhD in Mathematics from Warwick.

Timetable:

9.30 Introduction

9.35 Lecture 1:  The early history of computing: Ada Lovelace, Charles Babbage, and the history of programming

10.35 Break with Refreshments Provided

11.15 Lecture 2: Case study, Alan Turing,  Grace Hopper, and the history of getting things right

12.15 Lunch (not provided)

2.30 Welcome by the Principal, Prof Sally Mapstone

2.35 Lecture 3: What do historians of computing do, and why is it  important for computer scientists today

3.30 Close

Lecture 1. The early history of computing: Ada Lovelace, Charles Babbage, and the history of programming

IN 1843 Ada Lovelace published a remarkable paper in which she explained  Charles Babbage’s designs for his Analytical Engine. Had it been built, it would have had in principle the same capabilities  as a modern general purpose computer. Lovelace’s paper is famous for its insights into more general questions, as well as for its detailed account of how the machine performed its calculations – illustrated with a large table which is often called, incorrectly, the “first programme”.   I’ll talk about the wider context; why people were interested in computing engines; and some of the other work that was going on at the time, for example Babbage’s remarkable hardware description language. I’ll  look at different explanations for why Babbage’s ideas did not take off, and give a quick overview of what did happen over the next 100 years, before  the invention of the first digital computers.

Lecture 2. Case study, Alan Turing,  Grace Hopper, and the history of getting things right

Getting software right was a theme of programming for the days of Babbage onwards. I’ll look at the work of pioneers Alan Turing and Grace Hopper, and talk about the long interaction of computer science with logic, which has led to better programming languages, new ways to prove programmes correct, and sophisticated mathematical theories of importance in their own right.  I’ll look at the history of the age-old debate about whether computer science needs mathematics to explain its main ideas, or whether practical skills, building things and making things simple for the user are more important.

Lecture 3: What do historians of computing do, and why is it  important for computer scientists today

When people think about computer science, they think about ideas and technologies that are transforming the future – smaller faster smarter connected devices, powered by, AI, and big data – and looking at the past can be seen as a bit of a waste of time. In this lecture I’ll look at what historians do and why it is important; how we get history wrong; and in particular often miss the contribution of of women.  I’ll illustrate my talk with  my own work on Ada Lovelace’s papers, to show how  detailed historical work is needed to debunk popular myths – it is often claimed that Lovelace’s talent was  “poetical science” rather than maths, but I’ve shown that she was a gifted perceptive and knowledgeable mathematician. I’ll explain how the historian’s techniques of getting it right can help us get to grip with  topical problems like “Fake news”, and give us new ways of thinking about the future.

DLS: Algorithms for healthcare-related matching problems

Event details

  • When: 31st March 2017 09:15 - 15:30
  • Where: Lower College Hall
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

Algorithms for healthcare-related matching problems

Distinguished Lecture Series, Semester 2, 2016-7

David Manlove

School of Computing Science, University of Glasgow

Lower College Hall (with overflow simulcast in Upper College Hall)

Abstract:

Algorithms arise in numerous everyday appPicture of David Manlovelications – in this series of lectures I will describe how algorithms can be used to solve matching problems having applications in healthcare settings.  I will begin by outlining how algorithms can be designed to cope with computationally hard problems.  I will then describe algorithms developed at the University of Glasgow that have been used by the NHS to solve two particular matching problems.  These problems correspond to the annual assignment of junior doctors to Scottish hospitals, and finding “kidney exchanges” between kidney patients and their incompatible donors in the UK.
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DLS: Distributed Systems and Sensing by Prof. Julie McCann

Event details

  • When: 7th November 2016 09:15 - 16:00
  • Where: Lower College Hall
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

DISTINGUISHED LECTURE SERIES

Semester 1

TITLE:

Distributed Systems and Sensing

by

Julie McCann

jm

7th November 2016

Lower and Upper College Halls

 

Introduction

By Professor Simon Dobson

School of Computer Science

University of St Andrews

The first of this academic year’s distinguished lectures will be given by Professor Julie McCann, Imperial College, London on Monday 7th November 2016 at Lower and Upper College Halls.

 

Overview

Chirping, self-organising, adaptive and intelligent tiny computers are beginning to enter both the market and people’s homes, performing various monitoring and control duties. From Google’s self-drive cars to the walls of modern office blocks, these simple devices are talking to each other in highly intelligent ways, mimicking the collective behaviour of insect colonies, for example, to overcome individual failures or changes in the local environment.

 

 

 Biography

Prof Julie A. McCann is a Professor of Computer Systems in Imperial College London (IC), where she leads the Adaptive Embedded Systems Engineering Research Group, she is Director for the Imperial wide Centre for Smart Connected Futures, Co-Director of the Intel Collaborative Research Institute for Sustainable Cities and she is CI for the NEC Smart Water Systems Lab and many other substantive projects with industry and academia with a focus on networking and sensing infrastructures to support environments such as smart cities, water and gas networks etc. She is CI on the EPSRC energy/water/food nexus WefWebs project where her focus is on precision farming and wine making.

Likewise, her NERC FUSE project designed and deployed a now patented sensing infrastructure for floodplain monitoring in Oxfordshire. Her research centres on highly decentralized and self-organizing scalable embedded frugal computing systems where one avoids a single point of failure to produce truly scalable solutions. She is a Fellow of the British Computer Society and is the Associate Editor for ACM Transactions on Adaptive Autonomic Systems (TAAS), has been General and Technical chair for the IEEE International Conference on Self-Adaptive and Self-Organising systems (SASO) and IEEE SECON 2016, SMARTCOMP 2017 and has been on the programme committee for IEEE INFOCOM, ACM UBICOMP and many more. Julie has presented her work in A* conferences and keynoted at the Indian Science Conclave Congregation of Nobel Prize Winners, for the encouragement of disadvantaged kids into science and computing in 2008.

 

 

 

Programme:   Monday 7th November 2016

 
     
 

09:15 – 09:30

 

Introduction:

 
  By Professor Simon Dobson  
 

09:30 – 10:30

 

Lecture 1:

 
  Professor Julie McCann will initially talk through how Wireless Sensor Networks are being used today and what other sciences will impact this subject leading to the ability to have Programmable Matter.  
 

10:30 – 11:00

 

Coffee Break

 
    Refreshments served
 

11:00 – 12:00

 

Lecture 2:

 
  In her second talk she will come very much down to earth and discuss how such systems are programmed today in terms of the hardware stack that composes them and the protocols that allow them to collaborate.  
 

12:00 – 14:00

 

Lunch Break

 
  Free time  
 

14:00 – 15:00

 

Lecture 3:

 
  Prof McCann will introduce some of the challenges that still remain, such as scaling this technology to larger dimensions but to also make them more resilient as well as secure etc. and the challenges that control adds to the system.  
 

15:00 – 15:30

 

 

Q & A Session:

 

 
  Open forum

 

 
   

 

 

Distinguished Lecture Series: Reminder of next event – ‘CS for All’ by President Maria Klawe

Event details

  • When: 31st March 2016 09:00 - 16:00
  • Where: Byre Theatre
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

Reminder that President Maria Klawe will be speaking at our Distinguished Lecture Series on March 31st 2016 in St Andrews.KlaweMaria

During this event Maria  will discuss the challenges in CS for all, including CS education in K-12, computing for all in undergraduate education, and CS research aimed at people with accessibility challenges and creating educational and research opportunities around the applications of computational technologies in almost every discipline and economic sector.

Programme of events:

  • 09:00 – 09:30
    • Introduction: By Professor Aaron Quigley
  • 09:30 – 10:30
    • Lecture 1: Computing for all in K-12 education
  • 10:30 – 11:00
    • Coffee Break: Refreshments served in foyer
  • 11:00 – 12:00
    • Lecture 2: Computing for all in undergraduate education
  • 12:00 – 14:00
    • Lunch Break: Free time
  • 14:00 – 15:00
    • Lecture 3: Computing for all in research
  • 15:00 – 15:30
    • Q & A: Open forum in the auditorium
  • 15:30 – 16:00
    • Informal time with Speaker: In the foyer

Distinguished Lecture Series: ‘CS for All’ by President Maria Klawe

Event details

  • When: 31st March 2016 09:00 - 16:00
  • Where: Byre Theatre
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

The School of Computer Science is delighted to announce that President Maria Klawe will be speaking at our Distinguished Lecture Series on March 31st 2016 in St Andrews. This event will consist of a series of talks from 9am with a tea/coffee break, a lunch break, afternoon talk and Q&A session. Maria Klawe2

Biography

Maria Klawe became Harvey Mudd College’s fifth president in 2006. She joined Harvey Mudd from Princeton University after serving 14 years at the University of British Columbia. Prior to UBC, Klawe spent eight years with IBM Research in California and two years at the University of Toronto. She received her PhD (1977) and BSc (1973) in mathematics from the University of Alberta. In addition to numerous other commitments, Klawe is a member of the boards of Microsoft Corporation, Broadcom Corporation and the nonprofit Math for America and is a fellow of the American Academy of Arts & Sciences.

Distinguished Lecture Series

Lecture 1 starting at 09:00hrs: Computing for all in K-12 education

Lecture 2 starting at 11:00hrs:  Computing for all in undergraduate education

Lecture 3 starting at 14:00hrs: Computing for all in research

There will be a Q & A session between 15:00hrs and 15:30hrs, followed by the opportunity to meet President Klawe informally in the foyer.

Distinguished Lecture: ‘Scalability and Fault-tolerance, are they the same?’ by Joe Armstrong

Event details

  • When: 16th November 2015 09:15 - 15:30
  • Where: Byre Theatre
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

The first of this academic year’s distinguished lectures will be given by Professor Joe Armstrong, co-inventor of Erlang, on Monday 16th November 2015 at The Byre Theatre.Joe Armstrong

Abstract:

To build a scalable system the important thing is to make small isolated independent units. To scale up we just add more units. To build a fault-tolerant system the important thing to do is make small isolated independent units…. Does that sound familiar? Haven’t I seen that somewhere before? Oh yes, in the first paragraph! So maybe scalability and fault tolerance are really different names for the same thing.

This property of systems, namely that fault-tolerant systems were also scalable, was noticed years ago, notably in the design of the Tandem computer system. The Tandem was design for fault tolerance but rapidly became a leading supplier of scalable computer platforms. Thus it was with Erlang.

Erlang followed  a lot of the Tandem design, it was built for fault-tolerance but some of the most successful applications  (such as WhatsApp) use it for its scalability.

In this lecture I’ll talk about the intimate relationship between scalability and fault-tolerance and why they are architecturally the same thing.

I’ll talk about the design of Erlang and why scalable systems have to be built on non-shared memory abstractions.

Bio:

Joe Armstrong has been programming since 1967. He invented the programming language Erlang. He has worked as a programmer, founded a few successful companies and written a few books. He has a PHD in Computer Science from KTH. He is currently Adjunct Professor of Computer Science at the KTH Royal Institute of Technology in Stockholm.

What’s happening to computer hardware, and what does it mean for systems software?

Event details

  • When: 2nd April 2015 09:15 - 15:30
  • Where: St Andrews
  • Series: Distinguished Lectures Series
  • Format: Distinguished lecture

Mothy RoscoeThe first set of Computer Science Distinguished Lectures in 2015 will
be given by Prof Mothy Roscoe of ETH Zurich, 09:15–15:30 on Thursday 2nd April
in the Byre Theatre.

Computer systems are not what they used to be, and the days when a
machine could be described as a processor, some memory, and some I/O
devices are long gone. Modern machines, from Systems-on-a-Chip in
phones to rack-scale data appliances, are themselves complex networks
of heterogeneous processing elements, different kinds of memory, and
diverse communication links.
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