Virtual Seminar Series
To offer the students (and its staff) an opportunity to broaden their horizons in big data science, LIV.DAT invited researchers from various other organisations to speak at our virtual seminar series. Here the students learned about Big Data challenges and applications outside their own focus area, as part of their continued development.
The details of past seminars can be found below.
The data science seminars have now been moved to our new doctoral training centre for innovation in data intensive science LIV.INNO.
To register for upcoming seminars, please go to the event webpage:
https://indico.ph.liv.ac.uk/e/data_science_seminars
Previous Seminars
August 2022 | 17:15 (Europe/London) - Dr 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 - Prof 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 - Dr 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 - Dr 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 - Dr 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"
October 2021 - Dr Stefano Albrecht
Head of the Autonomous Agents Research Group, University of Edinburgh
“Deep Reinforcement Learning for Multi-Agent Interaction”
June 2021 - Dr Myriam Neaimeh
School of Engineering, Newcastle University & Data-Centric Engineering Group, Turing Institute
"Applying data science methods to modernise transport and electricity infrastructures"
May 2021 - Professor Shirley Ho
Cosmology X Data Science Group, Flatiron Institute, New York (USA) &
Department of Astrophysical Sciences, Princeton University (USA)
“Machine learning the Universe: Opening the Pandora Box”
April 2021 - Dr Anne O’Carroll
Remote Sensing Scientist, EUMETSAT, Darmstadt (DE)
“Combining satellite data with ocean surface measurements: Sea Surface Temperature (SST) observations”
March 2021 - Professor Stephen Fairhurst
School of Physics and Astronomy, Cardiff University & Data Intensive CDT (Cardiff, Bristol, Swansea)
“Analysis of gravitational waveforms to better understand black holes”
February 2021 - Professor Simon Maskell
Dept. of Electrical Engineering and Electronics, University of Liverpool
“SMC-Stan: A Scalable and Flexible Software tool for Better Bayesian Inference”
December 2020 - Dr Jana Kemnitz
Senior Data Scientist, Distributed-AI-Systems Research Group Siemens
“Industrial Data Science, Machine-, Transfer- and Federated Learning”
November 2020 - Professor Paul Watson
Computer Science and Director of the Digital Institute, Newcastle University
“A Declarative Approach to Distributed Stream Processing”
October 2020 - Professor Brant Robertson
Dept. of Astronomy and Astrophysics, University of California (UCSC)
“Morpheus: A Deep Learning Framework for the Pixel-level Analysis of Astronomical Image Data”
July 2020 - Dr Graeme West
Department of Electronic and Electrical Engineering, University of Strathclyde
“Artificial Intelligence in nuclear power generation applications”
June 2020 - Dr Jessica Barret
MRC Biostatistics Unit, University of Cambridge
“Cardiovascular risk prediction using big data: A statistician’s perspective”
May 2020 – Dr Patrick Parkinson
Department of Physics and the Photon Science Institute, University of Manchester
“Big-data for nano-electronics”