Data-Centric Engineering

Data-Centric Engineering

Data-Centric Engineering Journal, Cambridge University Press

The DCE Webinar series is a programme of monthly virtual events about data-centric engineering: the use of data science methods and models for improving the reliability, resilience, safety, efficiency and usability of engineered systems. It is hosted by the Data-Centric Engineering journal at Cambridge University Press – a peer-reviewed open access journal dedicated to the interface of data science and all engineering disciplines – with the support of The Alan Turing Institute and the Lloyd's Register Foundation .

For more information and updates follow the DCE Blog on Medium

Speakers
Community

Upcoming live seminars

April 2026

SuMoTuWeThFrSa
1234
567891011
12131415161718
19202122232425
2627282930
University of Cambridge
University of Birmingham
1

Digital Twins for Underground Infrastructure

BS
Brian Sheil
BN
Brian Sheil & Jelena Ninic
University of Cambridge and University of Birmingham
Chaired by Marcus Haywood-Alexander
Friday, April 10, 2026 2:00 PM (UTC)
RSVP to seminar

Published seminars

University of Cambridge

Optimal experiment design with adjoint-accelerated Bayesian inference

Matthew Yoko, University of Cambridge
The University of Texas at Austin

Reinforcement Learning in Building Energy Management: Challenges and Future Directions

Zoltan Nagy, The University of Texas at Austin
Swansea University
ETH Zurich

Securing Cyber-Physical Systems: Economic Adoption and Risk Perception of Cybersecurity

Siraj Shaikh, Swansea University
Marcus Haywood-Alexander, ETH Zurich
University of Southern California

The Air-Conditioning Paradox: Protecting Vulnerable Populations from Extreme Heat

Kelly Twomey Sanders, University of Southern California
University of Cambridge

Augmenting reality with The World Avatar - automating data centric engineering

Markus Kraft, University of Cambridge
KTH Royal Institute of Technology

Modelling and Controlling Turbulent Flows through Deep Learning

Ricardo Vinuesa, KTH Royal Institute of Technology
University of Luxembourg

Digital twins in mechanics and medicine

Stéphane Bordas, University of Luxembourg
University of Western Australia

Building a Data Fit Organisation

Melinda Hodkiewicz, University of Western Australia
Zane Prickett, Unearthed
Technical University of Munich

Differentiable Physics Simulations for Deep Learning

Nils Thürey, Technical University of Munich