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

Distinguished Lecture Series, Semester 1, 2017-18


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 Marti

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.


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.

SRG Seminar: “Simulating a pulmonary tuberculosis infection using a network-based metapopulation model” by Michael Pitcher and “A Fake City of People: Modeling the Co-evolution of City and Citizens” by Xue Guo

Event details
When: 28th September 2017 13:00 – 14:00
Where: Cole 1.33b
Series: Systems Seminars Series
Format: Seminar

Michael Pitcher’s abstract

Tuberculosis (TB) is one of the world’s most deadly infectious diseases, claiming over 1.4 million lives every year. TB infections typically affect the lungs and treatment regimens are long and arduous, requiring at least 6 months of daily chemotherapy. Previous investigations have shown TB to have unique localisations within the lung at varying stages of infection. The initial implant and the primary lesion which arises from it can occur anywhere in the lungs, with a greater probability of occurrence in the lower to middle regions of the lung. However, reactivation of a previously latent form of disease always involves cavitation of the tissue at the apical regions. This difference in spatial location of TB infections suggests two important factors: i) bacteria are able to disseminate across the lung in some manner, and ii) the environment at the top of the lung has some properties that make it preferential for TB replication.

In this project, we aim to build a whole-organ model of the lung and surrounding lymphatics which incorporates both bacterial dissemination possibilities and lung tissue spatial heterogeneity in order to understand their impact on TB. We develop ComMeN (Compartmentalised Metapopulation Network), a Python framework designed to allow the easy creation of complex network-based metapopulations with spatial heterogeneity upon which interaction dynamics can be applied, with discrete event modelling using the Gillespie Algorithm. We then extend this framework to create a TB-specific model, PTBComMeN, which models a TB infection occurring over lung tissue which is divided into patches, each of which contains spatial attributes appropriate to its position in the lung, such as ventilation, perfusion and oxygen tension. Events dictate the interactions between cells and bacteria and their interaction with the environment, with dissemination occurring between edges joining patches on the lung network. This model allows experimentation into studying the effects spatial heterogeneities and bacterial dissemination may have on the progression of disease and the model is designed to provide insight into the factors that result in long treatment times for TB.

Xue Guo’s abstract

By the year 2050, the global urban population will reach 2.5 billion. While the fast pace of urbanisation brings improved quality of life initially, the surging population will inevitably lead to unique urban issues. Emerging research fields, with the aim of creating smarter cities, plan to counteract these problems. To facilitate this research, we need solid models to generate ’fake cities’, which cannot be easily produced by existing random graph algorithms due to spatial constraints. Therefore, we propose a new model for the co-evolution of city and population, which can show how street network forms, how population spreads and how settlements emerge and diminish. The new model will be a random city generator, which could be used to backtrack the history and predict the future of a city, or act as test cases for the validation and evaluation of urban optimisation algorithms.

Daniel Sorin (Duke University): Designing Formally Verifiable Cache Coherence Protocol (School Seminar)

Event details

  • When: 26th September 2017 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

The cache coherence protocol is an important but notoriously complicated part of a multicore processor. Typical protocols are far too complicated to verify completely and thus industry relies on extensive testing in hopes of uncovering bugs. In this work, we propose a verification-aware approach to protocol design, in which we design scalable protocols such that they can be completely formally verified. Rather than innovate in verification techniques, we use existing verification techniques and innovate in the design of the protocols. We present two design methodologies that, if followed, facilitate verification of arbitrarily scaled protocols. We discuss the impact of the constraints that must be followed, and we highlight possible future directions in verification-aware microarchitecture.

Speaker Bio:
Daniel J. Sorin is the Addy Professor of Electrical and Computer Engineering at Duke University. His research interests are in computer architecture, with a focus on fault tolerance, verification, and memory system design. He is the author of “Fault Tolerant Computer Architecture” and a co-author of “A Primer on Memory Consistency and Cache Coherence.” He is the recipient of a SICSA Distinguished Visiting Fellowship, a National Science Foundation Career Award, and Duke’s Imhoff Distinguished Teaching Award. He received a PhD and MS in electrical and computer engineering from the University of Wisconsin, and he received a BSE in electrical engineering from Duke University.

Felipe Meneguzzi (PUCRS): Plan Recognition in the Real World (School Seminar)

Event details

  • When: 19th September 2017 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

Plan and goal recognition is the task of inferring the plan and goal of an agent through the observation of its actions and its environment and has a number of applications on computer-human interaction, assistive technologies and surveillance.
Although such techniques using planning domain theories have developed a number of very accurate and effective techniques, they often rely on assumptions of full observability and noise-free observations.
These assumptions are not necessarily true in the real world, regardless of the technique used to translate sensor data into symbolic logic-based observations.
In this work, we develop plan recognition techniques, based on classical planning domain theories, that can cope with observations that are both incomplete and noisy and show how they can be applied to sensor data processed through deep learning techniques.
We evaluate such techniques on a kitchen video dataset, bridging the gap between symbolic goal recognition and real-world data.

Speaker Bio:
Dr. Felipe Meneguzzi is a researcher on multiagent systems, normative reasoning and automated planning. He is currently an associate professor at Pontifícia Universidade Católica do Rio Grande do Sul (PUCRS). Prior to that appointment he was a Project Scientist at the Robotics Institute at Carnegie Mellon University in the US. Felipe got his PhD at King’s College London in the UK and an undergraduate and masters degree at PUCRS in Brazil. He received the 2016 Google Research Awards for Latin America, and was one of four runners up to 2013 Microsoft Research Awards. His current research interests include plan recognition, hybrid planning and norm reasoning.

Mark Olleson (Bloomberg): Super-sized mobile apps: getting the foundations right (School Seminar)

Event details

  • When: 17th October 2017 14:00 - 15:00
  • Where: Cole 1.33a
  • Series: School Seminar Series
  • Format: Seminar

An email client. An instant messenger. A real-time financial market data viewer and news reader. A portfolio viewer. A note taker, file manager, media viewer, flight planner, restaurant finder… All built into one secure mobile application. On 4 different mobile operating systems. Does this sound challenging?
Mark from Bloomberg’s Mobile team will discuss how conventional development tools and techniques scale poorly when faced with this challenge, and how Bloomberg tackles the problem.

Speaker Bio:
Mark Olleson is a software engineer working in Bloomberg’s Mobile Professional team. Mark start developing iOS apps around the time the original iPad launched, and since has worked on projects which share common characteristics: scale and complexity. Today he specialises in large-scale and cross-platform mobile-app technology.