Venue Date
4th Annual Alumni Dinner Steve Marchant Department of Computer Science, Malet Place Engineering Buil 23 Apr 15, 18:00 - 22:00
5th International Conference on Digital Health Steve Marchant Florence, Italy 18 May 15 (start 09:00) - 20 May 15
London Hopper 2015 Steve Marchant BCS, 1st Floor, Davidson Building, 5 Southampton Row, London 20 May 15, 10:00 - 16:00

Recordings and Slides from previous Distinguished Lectures

Experiments with Non-parametric Topic Models by Prof Wray Buntine

Thursday 22 January 2015

View the recording on Lecturecast (UCL login required) here

This talk will cover some of our recent work in extended topic models to serve as tools in text mining and NLP (and hopefully, later, in IR) when some semantic analysis is required.  In some sense our goals are akin to the use of Latent Semantic Analysis.  The basic theoretical/algorithmic tool we have for this is non-parametric Bayesian methods for reasoning on hierarchies of probability vectors. The concepts will be introduced but not the statistical detail. Then I'll present some of our KDD 2014 paper (Experiments with Non-parametric Topic Models), and some extended work such as "Bibliographic Analysis with the Citation Network Topic Model" (ACML 2014) and "Topic Segmentation with a Structured Topic Model" (NAACL 2013).  Various evaluations and comparisons will be made.

Prof. Wray Buntine joined Monash University in February 2014 after 7 years at NICTA in Canberra Australia.  He was previously of Helsinki Institute for Information Technology from 2002, and at NASA Ames Research Center, University of California, Berkeley, and Google. He is known for his theoretical and applied work in document and text analysis, data mining and machine learning, and probabilistic methods. He applies probabilistic and non-parametric methods to tasks such as text analysis.  In 2009 he was programme co-chair of ECML-PKDD in Bled, Slovenia, and was programme co-chair of ACML in Singapore in 2012.  He reviews for conferences such as ACML, ECIR, SIGIR, ECML-PKDD, ICML, NIPS, UAI, and KDD, and is on the editorial board of Data Mining and Knowledge Discovery.

Understanding user behaviour at three scales by Daniel Russell

Tuesday 8 July 2014

View the recording on Lecturecast (UCL login required) here

How people behave is really the central question for data analytics.  The way people play, the ways they interact, the kinds of behaviors they bring to the game ultimately drive how our systems perform, and what we can understand about why they do what they do.  In this talk I’ll describe three different scales of collecting data about user behavior, showing how looking at behavior data at the micro-, meso-, and macro-levels is a superb way to understand what people are doing in our systems, and why.  Knowing this lets you not just understand what’s going on, but also how to improve the user experience for the next design cycle. 

Daniel Russell is the Uber Tech Lead for Search Quality and User Happiness in Mountain View. He earned his PhD in computer science, specializing in artificial intelligence until he realized that magnifying and understanding human intelligence was his real passion. Twenty years ago he foreswore AI in favor of HI, and enjoys teaching, learning, running and music, preferably all in one day. He worked at Xerox PARC before it was PARC.com, and was in the Advanced Technology Group at Apple, where he wrote the first 100 web pages for www.Apple.com using SimpleText and a stone knife. He also worked at IBM and briefly at a startup that developed tablet computers before the iPad.

Computational Differential Geometry & Fabrication-Aware Design by Dr Helmut Pottmann

Wednesday 26 February 2014

View the recording on Lecturecast (UCL login required) here

This talk will present an overview of my recent research which evolves around discrete and computational differential geometry with applications in architecture, computational design and manufacturing. From the mathematical perspective, we are working on extensions of classical differential geometry to data and objects which frequently arise in applications, but do not satisfy the classical differentiability assumptions. On the practical side, our work aims at geometric modeling tools which include important aspects of function and fabrication already in the design phase. This interplay of theory and applications will be illustrated at hand of selected recent projects on the computational design of architectural freeform structures under manufacturing and structural constraints. In particular, we will address smooth skins from simple and repetitive elements, self-supporting structures, form-finding with polyhedral meshes, optimized support structures, shading systems and the exploration of the available design space.

Helmut Pottmann earned a Ph.D. in Mathematics from Vienna University of Technology in 1983. He has held faculty positions in Germany (Kaiserslautern, Hamburg) and the US (UC Davis, Purdue) and has been Professor of Applied Geometry at Vienna University of Technology since 1992. In 2009 he became Professor at King Abdullah University of Science and Technology, where he served as Director of the Geometric Modeling and Scientific Visualization Center until 2013. Pottmann has co-authored two books and more than 200 articles in scientific journals. He is also co-founder and scientific director of Evolute GmbH, a company which offers services and software to industries facing challenges related to complex geometry.

The Functoriality of Data: Understanding Geometric Data Sets Jointly by Prof Leonidas J. Guibas

Wednesday 4 September 2013

View the recording on Lecturecast (UCL login required) here

The information contained across many data sets is often highly correlated. Such connections and correlations can arise because the data captured comes from the same or similar objects, or because of particular repetitions, symmetries or other relations and self-relations that the data sources satisfy. This is particularly true for data sets of a geometric character, such as GPS traces, images, videos, 3D scans, 3D models, etc. We argue that when extracting knowledge from the data in a given data set, we can do significantly better if we exploit the wider context provided by all the relationships between this data set and a "society" or "social network" of other related data sets. We discuss mathematical and algorithmic issues on how to represent and compute relationships or mappings between data sets at multiple levels of detail. We also show how to analyze and leverage networks of maps, small and large, between inter-related data. The network can act as a regularizer, allowing us to benefit from the "wisdom of the collection" in performing operations on individual data sets or in map inference between them.

This "functorial" view of data puts the spotlight on consistent, shared relations and maps as the key to understanding structure in data. It is a little different from the current dominant paradigm of extracting supervised or unsupervised feature sets, defining distance or similarity metrics, and doing regression or classification – though sparsity still plays an important role. The inspiration is more from ideas in homological algebra or algebraic topology,  exploiting the algebraic structure of data relationships or maps in an effort to disentangle dependencies and assign importance to the vast web of all possible relationships among multiple data sets. We illustrate these ideas largely using examples from the realm of 3D shapes and images -- but the notions are more generally to the analysis of graphs and other networks, acoustic data, biological data such as microarrays, homeworks in MOOCs, etc. This is an overview of joint work with multiple collaborators, as discussed in the talk.

Leonidas Guibas obtained his Ph.D. from Stanford under the supervision of Donald Knuth. His main subsequent employers were Xerox PARC, DEC/SRC, MIT, and Stanford. He is currently the Paul Pigott Professor of Computer Science (and by courtesy, Electrical Engineering) at Stanford University. He heads the Geometric Computation group and is part of the Graphics Laboratory, the AI Laboratory, the Bio-X Program, and the Institute for Computational and Mathematical Engineering. Professor Guibas' interests span geometric data analysis, computational geometry, geometric modeling, computer graphics, computer vision, robotics, ad hoc communication and sensor networks, and discrete algorithms. Some well-known past accomplishments include the analysis of double hashing, red-black trees, the quad-edge data structure, Voronoi-Delaunay algorithms, the Earth Mover's distance, Kinetic Data Structures (KDS),  Metropolis light transport, and the Heat-Kernel Signature. Professor Guibas is an ACM Fellow, an IEEE Fellow and winner of the ACM Allen Newell award.

Evolution of Computing by Rick Rashid

Friday 18 January 2013

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Limits in computing power and our ability to interact with computers have also imposed limits on our understanding of the world around us.  Increasingly, those limits are being removed, clearing the way for new advances in almost every kind of human endeavor.

Rick Rashid, Microsoft chief research officer and head of Microsoft Research, will present his vision of the future of computing research in light of these breakthroughs and the opportunities that lie ahead.

Folkflore of Network Protocols by Radia Perlman

Tuesday 15 January 2013

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It's very hard to understand the field of network protocols by focusing on the details of one particular protocol. Issues are clouded by marketing hype and protocol group rivalry. What is really intrinsic to the differences between one protocol and another? This talk covers some of the ways in which solutions can differ, as well as demystifying some especially confusing pieces of this field, such as what is really the difference between "layer 2 solutions" and "layer 3 solutions", why we need both Ethernet and IP, the evolution of Ethernet from its original invention (CSMA/CD) through spanning tree and now TRILL, and some things that people assume to be true that may not be. The talk includes some possible research areas.

Radia Perlman is a Fellow at Intel Labs, specializing in network protocols and security protocols.  Many of the technologies she designed have been deployed in the Internet for decades, including link state routing, the spanning tree algorithm, and TRILL, which improves upon spanning tree while still "being Ethernet".  She has also made contributions to network security, including assured delete of data, design of the authentication handshake of IPSec, trust models for PKI, and network infrastructure robust against malicious trusted components. She is the author of the textbook "Interconnections: Bridges, Routers, Switches, and Internetworking Protocols", and co-author of "Network Security". She has a PhD from MIT in computer science, holds over 100 issued patents, and has received various industry awards including lifetime achievement awards from ACM's SIGCOMM and Usenix, and an honorary doctorate from KTH.

Behavioural Nudge or Technological Fudge? by Prof Yvonne Rogers

Wednesday 3 October 2013

View the recording on Lecturecast (UCL login required) here 

We all have a pet behaviour we would like to change, such as eating better, exercising more, or reducing our energy consumption. Many of us would also like to manage our time more effectively, by spending less time randomly Googling, sofa slouching or looking out the window. How can we design new technologies to help people change their behaviour? Nudging methods, derived from behavioural economics and social psychology, have become increasingly popular. But how effective are they and can technology be designed to exploit them? In this talk, Yvonne will describe our investigations into how decision environments can be restructured in innovative ways, using pervasive, ambient and wearable technologies to nudge behaviour in ways that are desirable to the individual. Our goal is to help people make better-informed decisions in situ. Underlying all of this, however, is the nagging question of whether it is ethical, desirable or sustainable to be nudging people in a desired direction. Or, is it a case of technological fudging, where we may be covering over deeper problems?

Yvonne's research interests are in the areas of ubiquitous computing, interaction design and human-computer interaction. A central theme is how to design interactive technologies that can enhance life by augmenting and extending everyday, learning and work activities. This involves informing, building and evaluating novel user experiences through creating and assembling a diversity of pervasive technologies. Yvonne has been awarded a prestigious EPSRC dream fellowship and is currently (until June 2012) rethinking the relationship between ageing, computing and creativity. Yvonne is also visiting Professor at the Open University, Indiana University, and Sussex University, and has spent sabbaticals at Stanford, Apple, Queensland University, and UCSD. Central to her work is a critical stance towards how visions, theories and frameworks shape the fields of HCI, cognitive science and Ubicomp. She has been instrumental in promulgating new theories (e.g. external cognition), alternative methodologies (e.g. in the wild studies) and far-reaching research agendas (e.g. "Being Human: HCI in 2020 manifesto).

Computers & Brains by Prof Steve Furber

Wednesday 14 September 2012

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The principles of information processing in the brain are still far from understood. But progress in computer technology means that we can now realistically contemplate building computer models of the brain that can be used to probe these principles much more readily than is feasible, or ethical, with a living biological brain. What might these models tell us about brain function, and what might we learn that can then be applied to building more efficient, fault-tolerant, parallel computers?

Steve Furber CBE, FRS, FREng is the ICL Professor of Computer Engineering at the School of Computer Science at the University of Manchester and is probably best known for his work at Acorn Computers, where he was one of the designers of the BBC Micro and the ARM 32-bit RISC microprocessor.

Cyber Security From 30,000 Feet: The Benefits of Multidisciplinary Research by Dr Shari Lawrence Pfleeger

Cyber Security From 30,000 Feet: The Benefits of Multidisciplinary Research by Dr Shari Lawrence Pfleeger

Wednesday 21 March 2012

Download the slides here

Shari Lawrence Pfleeger is Director of Research for the Institute for Information Infrastructure Protection at Dartmouth College. She joined the I3P after serving for almost nine years as a senior researcher at the RAND Corporation. Previously, she headed Systems/Software, Inc., a consultancy specializing in software engineering and technology.  She has been a developer and maintainer for real-time, business-critical software systems, a principal scientist at MITRE Corporation's Software Engineering Center, and manager of the measurement program at the Contel Technology Center. She has also held several research and teaching positions at universities world-wide.

Shari is well-known for her work in empirical studies of software engineering and is the author of many books and articles, including Analyzing Computer Security (with Charles P. Pfleeger), Security in Computing (4e, with Charles P. Pfleeger), and Software Engineering: Theory and Practice (4e, with Joanne Atlee). She has been associate editor of IEEE Transactions on Software Engineering, associate editor-in-chief of IEEE Software, and she is currently associate editor-in-chief of IEEE Security & Privacy. Shari has been named repeatedly by the Journal of Systems and Software as one of the world's top software engineering researchers..  Shari earned a BA in mathematics from Harpur College, an MA in mathematics from Penn State, an MS in planning from Penn State, a PhD in information technology and engineering from George Mason University, and was awarded a Doctor of Humane Letters by Binghamton University.

Visitors from Outside UCL

Visitors are welcome to many of the events listed. However, could visitors from outside UCL please email the UCL contact (in the Speaker/Organiser column) to ensure that attendance is possible.


Where a simple room number is given the event takes place in the new Computer Science building on Malet Place. Please see the Getting Here pages.

Other Events

Regular workshops and seminars are run by:

London Hopper & Karen Spärck Jones Lecture 2015

*Registration now open!*

UCL Computer Science and the BCS Academy will be presenting the 11th. London Hopper Colloquium on Wednesday, 20 May 2015 at the BCS headquarters in London. This 1-day event is free and will feature women speakers talking about their research, a spotlight competition open to postgraduate students and postdoctoral researchers, and lots of opportunities to network with other new researchers in computing.

Click here for the programme and registration.

We are also pleased to announce that Dr. Cordelia Schmid from INRIA, France, will be presenting the 5th Karen Spärck Jones Lecture, an evening event honouring women in computing research, that will follow the London Hopper at the BCS Headquarters. Dr. Schmid is the Research Director and Head of the LEAR (LEArning and Recognition in Vision) Project Team.

The London Hopper and Karen Spärck Jones Lecture take place at the BCS headquarters in Central London, with support from UCL Computer Science, the BCS Academy and IBM.

CS Unveiled

See here for more details about CS Unveiled - we will be launching new department initiatives and revealing our latest research impact stories.

Posting New Events

We are keen to ensure that Departmental events and news items are publicised through the CS Web site. CS staff who are organising an event or know some news that would be of general interest can help us by sending details to announce@cs.ucl.ac.uk.