The impact of explainability, governance and bias when your models really matter.
With Prof. Mark Girolami, Turing Institute and Prof. Derek McAuley, Nottingham University.
14 June 2022, livestreamed from Cambridge
Register below
Cambridge Session 2 will focus on Mission Critical Machine Learning – explainability, governance and bias when your models really matter.
We will hear from Prof. Mark Girolami, Chief Scientist at The Alan Turing Institute and Prof. Derek McAuley, Professor of Digital Economy at Nottingham University alongside Iker Perez and David Sutton two leading data scientists at Featurespace, in a short series of Keynotes and Panel Discussion.
Date: Tuesday 14th June 2022
Livestream via Zoom
Join from: 4:55pm BST/5:55pm CEST/ 11:55am EST
Want to know what to expect? You can watch last year’s virtual session on Deep Learning, with Prof. Frank Kelly, here.
Professor Mark Girolami is the Chief Scientist of The Alan Turing Institute and took up this role from October 2021. Previous to his role as Chief Scientist, he led the Institute’s Data-Centric E...
Derek's research expertise is in ubiquitous computing, computer architecture, networking, distributed systems and operating systems, while his interdisciplinary interests include issues of ethics, ...
Iker is a Principal Research Scientist at Featurespace, where he specialises in uncertainty quantification and probabilistic reasoning, as well as interpretability and algorithmic fairness in autom...
David is responsible for Featurespace's research and innovation program. Prior to joining the company in 2015, David was a Research Associate in observational cosmology at the Kavli Institute for C...
Professor Mark Girolami is the Chief Scientist of The Alan Turing Institute and took up this role from October 2021. Previous to his role as Chief Scientist, he led the Institute’s Data-Centric Engineering (DCE) Programme, launched with the Lloyd’s Register Foundation as a strategic partner. The partnership has driven forward the creation of data-centric engineering as a discipline that now has global reach and influence.
Under his leadership, the DCE programme has grown into a multi-million pound global research and innovation endeavour that saw the delivery of a number of ‘world-firsts’ including the world’s first self-sensing 3D printed stainless steel pedestrian bridge in Amsterdam; sustainable and more efficient underground agriculture; advanced AI enabled city scale air quality monitoring systems; the city level monitoring of social distancing and activity assessment in guiding London through the COVID-19 pandemic; the development of an AI enabled UK Air Traffic Control Service, and digital twin technologies in rail transportation and aerospace design, amongst many others.
The launch of the international Data-Centric Engineering journal by Cambridge University Press firmly established DCE as an emerging discipline of global importance. Mark was also the driving force behind the first-ever DCEng Summit in September 2021. The event attracted international expert speakers from countries around the globe and represented another important moment in the growth of the discipline.
In 2019, Mark was elected to the Sir Kirby Laing Professorship of Civil Engineering, following the retirement of Professor Lord Robert Mair, within the Department of Engineering at the University of Cambridge, where he also holds the Royal Academy of Engineering Research Chair in Data Centric Engineering. Prior to joining the University of Cambridge, Mark held the Chair of Statistics in the Department of Mathematics at Imperial College London.
He was an EPSRC Established Career Research Fellow (2012-2018), an EPSRC Advanced Research Fellow (2007-2012), was a recipient of a Royal Society Wolfson Research Merit Award, and in 2011 was elected to the Fellowship of the Royal Society of Edinburgh.
After a PhD and lectureship in the Computer Laboratory at the University of Cambridge Derek moved to a chair in the Department of Computer Science at the University of Glasgow. He returned to Cambridge in July 1997, to help found the Cambridge Microsoft Research facility, moving on to found the Intel lablet in Cambridge in July 2002.
Before joining Nottingham in 2009, Derek spent a year working in Oregon for Intel and enjoyed the cut and thrust of two startups, XenSource (now Citrix) and Netronome.
During his time at Nottingham, Derek has also spent a year as Chief Innovation Officer (in residence) at the Digital Catapult during its startup phase in 2013/2014 and more recently spent a short sabbatical helping colleagues in the Computer Lab set up Unikernel Systems (acquired by Docker). His technology work has led him into policy matters and he served on the Furman panel looking at digital competition that resulted in the UK HM Treasury report Unlocking Digital Competition.
Iker is a Principal Research Scientist at Featurespace, where he specialises in uncertainty quantification and probabilistic reasoning, as well as interpretability and algorithmic fairness in automated fraud prevention.
He joined Featurespace in 2020, following a lectureship in the School of Mathematical Sciences at the University of Nottingham. Iker holds a PhD in probability theory, and he is an accredited graduate statistician by the Royal Statistical Society. Loves dogs.
David is responsible for Featurespace’s research and innovation program. Prior to joining the company in 2015, David was a Research Associate in observational cosmology at the Kavli Institute for Cosmology in the University of Cambridge, where he developed algorithms to study the Cosmic Microwave Background.
At Featurespace, David developed the company’s approach to card fraud prevention, built out the company’s expertise in deep learning, and led the team that won the 2022 UK-US PETs Prize Challenge. His models have been deployed to more than 30 banks worldwide. David holds a DPhil (PhD) in Astrophysics from the University of Oxford and a Masters from University College London. In 2018, he was a recipient of the Gruber Prize for Cosmology as a member of the Planck team and has an academic publishing h-index of 70.
