Crowd Estimation: Approximating Crowd Sizes with Multi-modal Data

Date and Time:  Wed, 6 March 2019, 11:00 a.m. Venue: Lawrence Stenhouse Building Room 01.19 (LSB 01.19) Speaker: Dr. Fang-Jing Wu, TU Dortmund Speaker's biography and contact details: Dr. Fang-Jing Wu is a junior professor at TU Dortmund. Prior to TU Dortmund, she was a Research Scientist at Cloud Service and Smart Things Group, NEC Laboratories Europe from 2015 to 2017. Prior to NEC Labs, she was a Scientist at the Institute of Infocomm Research (I2R), Agency for...

Infectious disease informatics

Date: 6 Feb 2019 Time: 13:00 Venue: SCI 0.31 Speaker: Dr. Andrew Page, Quandram Institute, (formerly IFR)   Abstract: Bacteria are everywhere, some help us, and some make us very sick. A better understanding of the bacteria in our lives can help prevent infectious diseases, keep our food safe and our bodies healthy. Genome sequencing has allowed us to gain an understanding of some bacteria, however as sequencing technologies have massively advanced, producing...

Dependence Modelling Using Multivariate Copulas with Applications

Dependence Modelling Using Multivariate Copulas with Applications (3 day short course) Dates:  25th-27th March 2019 Course Leader :  Dr. Aristidis K. Nikoloulopoulos   For more information visit: https://www.uea.ac.uk/computing/copula-course        

Postgraduate Open Event - 30 Jan

Postgraduate Open Event – 30 Jan Are you thinking about studying for your Master’s or Research degree? Register today to find out more at UEA’s Postgraduate Open Event on Wednesday 30 January . At the event you’ll be able to meet and talk with current students and academics, and gain expert advice on the application process and funding opportunities for your subject area of interest. A Master’s or Research degree can provide you with an enhanced professional skillset and...

Novel Machine Learning Methods for Cancer Research 

Date and Time: Wed 23 Jan 2019 at 13:00 Venue: SCI 3.05 Speaker: Dr. Colin Campbell,  University of Bristol   Title: Novel Machine Learning Methods for Cancer Research  Abstract The talk will have two parts, both illustrating the potential promise of using innovative machine learning methods in application to the large and diverse omics datasets now being derived within cancer research. In the first part we consider novel methods, based on machine...