We host a number of events in the Department of Computer Science.


Women+@DCS seminar series

women+@DCS is a group that supports activities for promoting greater inclusion and visibility in computer science teaching, research and academic leadership. Please join us for this upcoming series of seminars. Details will be posted here.

A list of past Women+@DCS seminars can be found on the Women+@DCS website

LunchBytes Panel: Teaching Code

BCSWomen Lovelace Colloquium 

Departmental seminar series 

Details to be announced.

Inaugural Lectures

All new professors, whether they have been internally promoted or appointed externally, are given the opportunity to give an inaugural lecture. The Department's Inaugural Lecture series provides an opportunity to celebrate these achievements with each lecture representing a significant milestone in an academic's career.

The normal format is for a lecture of approximately an hour, followed by a celebratory wine reception.

Lectures are open to all University staff and students as well as to members of the public. 

Past Inaugural Lectures

From Science Fiction to Data Science: the evolution of consumer predictive analytics

Visiting Professor of Computer and Information Science, Clive Humby OBE

Thursday 25 November 2022

Abstract: This talk will compare sociology "Mass Action" (e.g. Isaac Asimov Foundation Trilogy) to what we see today in Consumer Data Science and how small actions can influence large numbers of consumers and the methods we developed.

The making of ourselves: from psychology to robotics

Professor Tony J. Prescott

Wed 28 November 2018

Abstract: This talk will explore how the approach of brain-based robotics is illuminating our understanding of animal and human brains, minds and behavior, from the fossil trails left by precambrain animals, through the brain loops underlying decision-making and exploration in whiskered mammals, to our human capacity for mental time travel. Linking research in neuroscience, psychology and robotics, I will argue that this synthetic (or “understanding through building”) approach can help answer fundamental questions about the human condition including the mystery of the human “sense of self”.

Go to the bee and be wise: algorithms from nature

Professor James Marshall

Wednesday 28 February 2018

Professor James Marshall is the head of the Complex Systems Modelling research group within the Department of Computer Science. His research interests cover modelling of collective behaviour, particularly in social insects, evolutionary theory, decision theory, robotics, and theoretical neuroscience.

Abstract: Honey bees have fascinated humanity for thousands of years, from their ‘political' and ‘economic’ life, to their abilities to solve problems in groups and individually. In this lecture I will talk about my work in understanding how bees work, from collectively choosing the best place to live, to navigating through the world. I will talk about bees’ individual brains, but also about how they might collectively function like a brain. I will discuss what engineering may learn from the bee. There will be bee-inspired robots, and probably some honey.

The beat goes on... How computer models help us understand how our hearts beat.

Professor Richard Clayton

Wednesday 24 January 2018

Professor Richard Clayton is part of the Complex Systems Modelling research group within the Department of Computer Science.  His research interests are focussed on developing physics-based and mechanistic computational models and simulations as tools to examine the structure and function of human tissues and organs. This theme aligns with the INSIGNEO institute for in-silico medicine in Sheffield.

Abstract: Each time our heart beats, an extraordinary sequence of events takes place at spatial scales ranging from single molecules right up to the whole organ. These intricate mechanisms continue to work reliably throughout our lifetimes. So what are they? What can go wrong? And what have computers got to do with it all? In this lecture I will address these questions, and show how an engineering mindset can not only shed light on the way that biological systems behave, but also pose some important scientific questions about the nature of living things.


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