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Virtual seminar series

The seminars in this series cover R&D outside of the LIV.INNO centre’s core research areas and give an insight into cutting edge research data intensive science.

Recent years have witnessed a dramatic increase of data in many fields of science and engineering, due to the advancement of sensors, mobile devices, biotechnology, digital communication, and internet applications.

Targeted training in managing, analysing, and interpreting large, complex datasets and high rates of dataflow in areas such as Astrophysics and nuclear and particle physics is provided by this CDT on data intensive science.

To offer the students (and its staff) an opportunity to broaden their horizons in data science, LIV.INNO invites researchers from various other organisations to speak at our virtual seminar series. Here the students learn about Big Data challenges and applications outside their own focus area, as part of their continued development.

These virtual seminars are held using conferencing tool Zoom and are open to students, staff and anyone else who is interested. Recent seminars covered areas such as “cardiovascular risk prediction using big data” and “artificial intelligence in nuclear power generation applications”.

The details of scheduled and a number of past seminars are listed below. 

Registration for the Liverpool Virtual Seminar Series on Data Intensive Science - Autumn/Winter 2023/24 is now open!

Please register via the events webpage: https://indico.ph.liv.ac.uk/e/data_science_seminars


Upcoming Seminars

7th May 2024 | 3.00pm (GMT) - Fabian Ruehle 

Assistant Professor at the Physics and Mathematics Department of Northeastern University College of Science 

"Rigorous results from machine learning"


9th April 2024 | 3.30pm (GMT) - Katy Clough 

STFC Ernest Rutherford Research Fellow at Queen Mary University of London

"Numerical simulations of spacetime and the role of HPC" 


Previous Seminars

March 2024 - Shannon Vallor 

Baillie Gifford Chair in the Ethics of Data and Artificial Intelligence at the Edinburgh Futures Institute (EFI) at the University of Edinburgh

"Building a Responsible AI Ecosystem: Lessons from the Past and Future of Responsible Research and Innovation"


February 2024 - Parisa Rashidi 

Associate Professor at the J. Crayton Pruitt Family Department of Biomedical Engineering (BME) at University of Florida

"AI and Pervasive Sensing: The New Frontier in Acute Care"

(link to seminar on YouTube)


January 2024 - Yuan-Sen Ting   

Associate Professor at the Australian National University

"Can Artificial Intelligence Generate Meaningful Scientific Hypotheses?"

(link to seminar on YouTube)


December 2023 - Hsiang-Chih Hwang   

Postdoctoral Fellow at the Institute for Advanced Study (USA)

"How does neural network help reveal the mass of (nearly) all the stars"

(link to seminar on YouTube)


November 2023 - Ilya Kuprov   

Professor of physics at the University of Southampton

"Reverse-engineering deep neural networks"

(link to seminar on YouTube)


October 2023 - Saskia Charity   

Senior Research Associate in the particle physics cluster at the University of Liverpool

"High performance computing in the muon g-2 experiment at Fermilab"

(link to seminar on YouTube)


May 2023 - Leigh Whitehead  

Senior Research Associate in the high energy physics group of the University of Cambridge

"Neutrino Interaction Classification: DUNE, CNNs and transfer learning"

(link to seminar on YouTube)


April 2023Jesse Granney and Charles Gretton

Jesse Granney - Postdoctoral Fellow at Australian National University College of Science
Charles Gretton - TechLauncher Program Convener, at Australian National University College of Engineering, Computing and Cybernetics

"Machine Learning and Adaptive Optics"

(link to seminar on YouTube)


March 2023 - Zach Ross

William H. Hurt Scholar and Assistant Professor of Geophysics at the Seismological Laboratory of the California Institute of Technology

"Seismic wave propagation and inversion with Neural Operators"

(link to seminar on YouTube)


January 2023 - Kelly Moran 

Research staff member in the statistical sciences group at Los Alamos National Laboratory

"How to train your Emu"

 (link to seminar on YouTube)


December 2022  - Aviad Levis 

Postdoctoral Researcher at the Computing and Mathematical Sciences Department, Caltech

"Computational Imaging for Scientific Discovery: From Cloud Physics to Black Hole Dynamics"

 (link to seminar on YouTube)


November 2022  - Małgorzata J. Zimoń

Research Staff Member at IBM Research UK

"Enabling digital twinning with surrogate models"

(link to seminar on YouTube)


October 2022 - Francois Lanusse

CNRS researcher in observational cosmology and machine learning at the Astrophysics Department of CEA Paris-Saclay (France)

"Merging deep learning with physical models for the analysis of cosmological surveys"

(link to seminar on YouTube)


August 2022 - Adi Hanuka

Senior Software Engineer, Machine Learning, Eikon Therapeutics, CA, US

"Robust Virtual Diagnostics for Accurate and Confident Beam Properties Prediction"

(link to seminar on YouTube)


June 2022  - Salvatore Cuomo

Associate Professor of Numerical Analysis, University of Naples Federico II

"Physics-informed neural networks for solving Gray-Scott systems"

 (link to seminar on YouTube)


May 2022 - Joanna Leng 

Senior Research Software Engineer, University of Leeds

"How computers have changed science and predictions on how that will continue"

(link to seminar on YouTube)


April 2022 - Vitaliy Kurlin 

Reader in the Computer Science Department and Materials Innovation Factory, University of Liverpool

"The Crystal Isometry Principle"

(link to seminar on YouTube)


December 2021 - Wesley Tansey

Computational Oncology, Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center (USA)

"Modeling, testing, and adaptive experimental design in high-throughput cancer drug screens"


The full list of previous seminars can be found on the LIV.DAT webpage.


Back to: Centre for Doctoral Training for Innovation in Data Intensive Science