Summer-internships
Past Internship Projects

Past Internship Projects

Communication Systems

Our goal is to make digital infrastructures more robust, resilient, and secure, and to develop advanced applications for now and the future. We also study interactions between these systems and society to help inform government policy.

Examples of previous projects:

  • 5G Measurements and Experimentations
  • Assessing traffic scheduling mechanisms in the Linux Kernel for Fronthaul access of virtual base stations in the Cloud-RAN

Cryptography

Modern cryptography enables applications like e-voting, machine learning on cloud-stored data without loss of privacy, and allows secure login without revealing passwords. We seek ways to represent information securely, protecting its confidentiality and guaranteeing its authenticity using methods from informatics, mathematics and engineering.

Examples of previous projects:

  • Constructing Equation Systems Representing Block Ciphers
  • Developing and documenting software for using Software Defined Radio connection
  • Edge Computing
  • Reevaluating Cluster Attacks against AES
  • Success-rate estimation in Side-Channel attacks with simulated leakage
  • Weakly-Private Information Retrieval for Coded Databases
  • Weakly-Private Information Retrieval for Coded Databases

Machine Learning

We focus on the mathematical foundations of machine learning, the experimental study of machine learning algorithms, and the application of machine learning in real-life applications including sports, human health and software engineering. We also develop machine learning methods that can be used in practical applications to process large amounts of data derived from multiple sources.

Examples of previous projects:

  • A Realistic Child Avatar based on Deepfake
  • Artificial intelligence based child avatar for police interview training
  • Time-Aware Constrained Multimodal Data Fusion
  • User Quality of Experience in Virtual Reality Interaction with a AI powered Child Avatar

Scientific computing

We work on advanced computational methods – from their mathematical foundations through to their application – to investigate complex physiological phenomena and medical conditions. Our key interest is modeling processes and conditions of the heart and brain, including heart failure, stroke, and dementia.

Examples of previous projects:

  • Automated finite element simulations on AMD GPUs 
  • Data analysis and numerical simulation of neuron potentials
  • DD-MAC
  • Enabling Graph Neural Networks at Exascale Project
  • Explore small conductance calcium activated (SK) channel pharmacology in cardiomyocytes and cardiac tissue
  • Exploring the AMD Instinct MI100 GPU
  • Granger causality assessment in clinical time series image registration 
  • Investigating the effects of stimulus current assignment in a neuronal cell model
  • MicroNN - Predicting tissue- microcirculation interaction by neural networks 
  • Optimisation strategies for ensemble simulations of ODE systems arising from models in cardiac electrophysiology
  • Ordinary differential equation-based modeling of cells in human cartilage
  • Porting finite element simulations to heterogeneous architectures
  • ReducedStokes (reduced order modelling of interaction between free flow and porous medium)

Software Engineering

We use software engineering methods and tools to design, develop, maintain, test and validate complex software systems. Our goal is to ensure that the software we rely on is robust, reliable, safe and secure, both for today’s systems and for quantum systems of the future.

Examples of previous projects:

  • AI-based testing techniques for generating synthetic healthcare data 
  • Application of Metamorphic Testing and Mutation Testing to AI automated planning systems
  • Automated fixing of one-line Java bugs using CodeBERT model 
  • Benefit Points in Jira 
  • Benefits Management Plugin for Jira
  • Developing a chaos-engineering environment for the evaluation of autonomously self-healing software systems
  • Developing a chaos-engineering environment for the evaluation of autonomously self-healing software systems
  • Digital Twins for Self-Driving Cars
  • Log parsing and analysis of Chaos Toolkit logs 
  • Primary and secondary effects of digital investments (PSEDI)