For the Public
Outreach
The HiPEDS Centre is committed to providing outreach and public engagement activities. These activities often include partnerships with schools and relationships with industrial partners. The outreach component of the doctoral training programme allowed our students to develop skills to communicate their subject area more widely, as well as engaging the public with their science.
Our past students have created seven videos with Amyric Films that show some of the exciting areas of their research. We hope you’ll find them interesting!
How Robots See
Charlie Houseago teaches us about one of the most powerful tools available for computer vision: the convolutional filter.
Trouble with Big Data
Ali Hadian describes the challenges around how to work with big data so that it can be searched quickly.
Can we Guarantee AI is Safe?
Michael Akintunde describes the importance of verification in automated systems and how researchers are attempting to achieve this verification.
Security in Cyber Physical Systems
Luca Castiglione discusses attacks on cyber physical systems, such as systems that interact with their surrounding environment (e.g., a train network). How can we detect and defend against these attacks?
Understanding the Spoken World
Aiden Hogg explains that, whilst most people find it quite easy to figure out who is talking, and when through hearing, computers find this very difficult. He takes us through how computers do this now, and how his research allows computers to do this more easily.
Deep Learning with Custom Devices
Ruizhe Zhao takes us through his research on how computers can use "Convolutional Neural Networks" to perform visual tasks, like detecting objects in videos. However, these can require lots of memory and be slow to execute. His research aims to effectively reduce the size of these networks to improve their performance.
Metaprogrammes for Heterogenous Systems
Jessica Vandebon walks us through her research on enabling fast and energy efficient computing, where modern large-scale computer systems contain specialist hardware that can accelerate parts of an application. However, programming these devices currently requires specialist skills that few programmers do have. Her research aims to automatically apply optimisations for these heterogeneous systems to help programmers use these effectively.
Molecular-based point-of-care diagnostics
Kenny Malpartida Cárdenas talks about her research to develop tests for the detection antimicrobial resistance and infections diseases (including malaria and covid) that can be used without needing lab equipment.
Superpositition for Quantum Machine Learning
Viet Pham Ngoc discusses his research of the use of Quantum Computers for machine learning.
Training of Machine Learning on Custom Hardware
Convolutional Neural Networks (CNNs) are used in a wide variety of Machine Learning applications, but modern CNNs are limited by the time and energy that is needed to train them. Diederik Vink takes us through his research which aims to use custom solutions on reconfigurable hardware to train CNNs. By calculating with less precise numbers where less accuracy is needed, CNNs can be trained fast and efficiently while maintaining accuracy!
Videos for the Public
A selection of HiPEDS student presentations and discussions of their research.
Films for the Public
Graphcore
Professor Andrew Davison and PhD researcher Joseph Ortiz discuss their use of Graphcore's IPU graph processor to more efficiently compute bundle adjustment in robot vision, using Gaussian Belief Propagation.
Graphcore
Joseph Ortiz discusses use of Graphcore's IPU graph processor
Professor Andrew Davison and PhD researcher Joseph Ortiz discuss their use of Graphcore's IPU graph processor to more efficiently compute bundle adjustment in robot vision, using Gaussian Belief Propagation.
Understanding the role of neural heterogeneity in learning
Nicolas Perez Nieves presents his research at the online workshop SNUFA'21.
Nicolas Perez Nieves presents his research at the online workshop: Spiking Neural Networks as Universal Function Approximators (SNUFA'21).
Lab on Chip to Detect Malaria
Kenny Malpartida describes digital diagnostic approaches
FPL2020: (3-min) An Adaptable High-Throughput FPGA
Philippos Papaphilippo's live pitch for the full paper at FPL 2020
FPL2020 live pitch for the full paper: Philippos Papaphilippou, Chris Brooks and Wayne Luk "An Adaptable High-Throughput FPGA Merge Sorter for Accelerating Database Analytics", The International Conference on Field-Programmable Logic and Applications (FPL) 2020.
FPL2020: (25-min) An Adaptable High-Throughput FPGA
Philippos Papaphilippou's presentation for the full paper at FPL 2020
FPL2020 video presentation for the full paper: Philippos Papaphilippou, Chris Brooks and Wayne Luk "An Adaptable High-Throughput FPGA Merge Sorter for Accelerating Database Analytics", The International Conference on Field-Programmable Logic and Applications (FPL) 2020
ROmodel: Modeling robust optimization problems in Pyomo
Johannes Weiber explains how ROmodel extends the capabilities of the modeling language Pyomo
Johannes Weiber explains how ROmodel extends the capabilities of the modeling language Pyomo to robust optimization problems.
A robust approach to warped Gaussian process [...]
Johannes Weiber explains warped gaussian processes with robust optimization
Temporal blocking for wave propagation [...]
George Bisbas presents his research at the High Performance Computing Conference 2021, Rice Universi
George Bisbas presents his research at the High Performance Computing Conference 2021, Rice University, Ken Kennedy Institute, Houston.
Optimizing FPGA-Based CNN Accelerator [...]
Hongxiang Fan presents his research at ICCD'20.
Hongxiang Fan presents his research at ICCD'20.
CompilerInvocation to -cc1 command line
Daniel Grumberg presents his research to the 2020 LLVM Developers' meeting.
Daniel Grumberg presents his research to the 2020 LLVM Developers' meeting.