Join us at the University's Data Science and Big Data Showcase for businesses
This event aims to grow and strengthen our links with businesses, in the broad area of Data Science and Big Data.
All businesses are welcome to come and meet University researchers from across the organisation who are exhibiting their expertise and cutting-edge knowledge. Businesses can view the wide range of practical applications of our research which derives from our community of over 100 data-savvy computer scientists, engineers, physicists, CGI experts, statisticians, business analysts, life scientists and many more.
The event will offer the opportunity to view case studies and demonstrations, as well as chat to experts and network over refreshments.
More information and booking
Please contact the Business Development Team email@example.com to register your interest in attending this event.
Book your place
Big Data research
We are open for R&D collaboration, knowledge transfer and commercial activities. Contact Philip Lucas and Farshid Amirabdollahian for more information.
Examples of our expertise, including past and current projects:
- Voice biometrics: novel methodologies with application to e-banking and airport security.
- Algorithms for neuromorphic hardware, enabling accelerated machine learning in power-restricted applications. This new type of hardware rivals GPUs for performance with only a fraction of the power supply, opening up applications on mobile devices or for robotic sensing.
- Face recognition and face-deidentification via machine learning (deep learning). Privacy can be protected whilst retaining the desired biometric data.
- Cyber security. Our specialist cyber security research team assists local and national bodies with digital security issues for PC networks, wearable devices, industrial control systems and the ever-growing Internet of Things.
- Games and Visual Effects Research Lab. In computer games, virtual reality and CGI for the film industry, the G-VERL team has 20 years of experience.
- Monitoring Biodiversity: multi-modal stations sensing sound, ultrasound, illumination, temperature and weather. Wireless communication with the base station.
- Immersive Visual Data Mining.
- Gaussian processes to study absorption by human skin of drugs and other chemicals.
- Machine learning to study the contribution of cerebellar nucleus neurons to epileptic absence seizures. This contributed to a closed loop system that detects and terminates these seizures in mice.
- Determining the size and orientation of tiny ice crystals in cirrus clouds by machine learning classification of scattered light images.
- Improved clustering algorithms in data mining and machine learning. We are researching feature weighting in density-based clustering algorithms to optimize the contribution of useful features over irrelevant or redundant features.
- Object classification in multi-wavelength image data by machine learning. From an initial application to study of distant galaxies, this algorithm is now being applied to analyse medical images of the heart.
- Energy consumption analysis through data mining. Demand prediction, discovery of use patterns. Disaggregation to identify appliances.
The Sawhney Suite, via main reception, College Lane Campus, University of Hertfordshire, Hatfield, Hertfordshire AL10 9AB