People

Jonathan Lawry

Research interests

• Social learning
• Collective decision making
• Approximate reasoning

Hub role

Work package: Cooperation in Heterogeneous Teams

Jianhong Wang

Research interests

• Multi-Agent Reinforcement Learning
• Cooperative Game Theory (coalition formation and credit assignment)
• Multi-Agent System modelling for real-world problems (e.g., smart grids, robotics, etc.)

Hub role

Work package: Cooperation in Heterogeneous Teams, working with Jonathan Lawry

Yiannis Demiris

Research interests

• Assistive Robotics and Human–Robot Interaction
• Human action understanding and human-centred robot behaviour adaptation
• Multimodal learning and fusion
• Distributed learning and in particular human-in-the-loop learning with privacy

Hub role

Work package: Cooperation in Heterogeneous Teams

Fernando Estévez Casado

Research interests

• Distributed/federated learning and privacy in robotics
• Assistive robots and trustworthy HRI (focus on mobility aids)
• User-centred robot learning, personalisation, and adaptation over time
• Deployment on real-world applications, platforms, and human participants

Hub role

Work package: Cooperation in Heterogeneous Teams, working with Yiannis Demiris and Deniz Gündüz

Amanda Prorok

Research interests

• Collective intelligence
• Robotics
• Multi-agent and muti-robot systems
• Applications such as:
  • Automated transport and logistics
  • Environmental monitoring
  • Surveillance
  • Search

Hub role

Work package: Cooperation in Heterogeneous Teams

Ioannis Kontoyiannis

Research interests

Information theory

• Communication and compression at pragmatic rates
• Truly high-SNR channel capacity
• Compression of truly sparse data

Statistics

• Bayesian causal discovery
• Regression and estimation for the Levy state space model

Machine learning and AI

• Bayesian/MDL neural network inference
• Sparse Gaussian processes
• Design and analysis of efficient Reinforcement Learning
• Stochastic Approximation algorithms

Hub role

Work package: Learning to Compress and Communicate

Lampros Gavalakis

Research interests

• Information theory
• Fundamental limits
• Entropy
• Inequalities
• De Finetti’s theorem
• Sampling bounds
• Entropic CLT and applications
• Entropy of Gaussian mixtures and applications

Hub role

Work package: Learning to Compress and Communicate, working with Ioannis Kontoyiannis

Deniz Gündüz

Research interests: Information Processing and Communications Laboratory (IPC-Lab)

Machine learning (ML) for data compression and communication

• ML-based channel code design
• ML-based image/video compression
• ML-based channel estimation and channel state compression

Distributed/ federated learning (FL)

• Communication-efficient FL
• Over-the-air computation for FL

Semantic communications

• Deep–learning aided wireless video transmission and intelligence

Privacy and security in learning

• Byzantine attacks in federated learning
• Private data sharing

Hub role

Work package: Learning to Compress and Communicate

Arpan Mukherjee

Research interests: 

• problems at the intersection of signal processing, statistics, and machine learning.
• sequential decision-making paradigms such as bandits and reinforcement learning
• theoretical underpinnings of foundation models

Hub role

Work package: Learning to Compress and Communicate

Haotian Wu

Research interests:

• Deep learning for source transmission and edge intelligence

• Efficient communication and compression

• Implicit representation and communication”

Hub role

Work package: Learning to Compress and Communicate

Ioannis Papageorgiou

Research interests:

• interface between Bayesian Statistics, Machine Learning and Information Theory
• combining modern machine learning techniques with ideas from information theory
• modelling and inference of time series (both discrete-valued and real-valued)
• developing tree-based methods that are inspired by information-theoretic ideas and algorithms

Hub role

Work package: Learning to Compress and Communicate

Nilanjana Datta

Research interests

• Quantum entropies and divergences
• Quantum hypothesis testing
• Entanglement theory
• Quantum communication

Hub role

Work package: Quantum Information and Computing

Bjarne Bergh

Research interests

• Quantum hypothesis testing
• Quantum machine learning
• Distributed quantum algorithms

Hub role

Work package: Quantum Information and Computing, working with Nilanjana Datta

Neil Walton

Research interests

• Queueing
• Congestion
• Networks
• Probability
• Optimization

Hub role

Work package: Quantum Information and Computing

Thiru Vasantam

Research interests

• Applied probability and queueing theory
• Internet of Things
• Performance modeling and analysis of communication networks
• Quantum networking
• Sequential analysis and changepoint detection

Hub role

Work package: Quantum Information and Computing

Sanidhay Bhambay

Research interests

• Performance analysis of complex networks
• Stochastic modelling
• Quantum networks
• Optimal schemes for entanglement distribution in Quantum Switches
• Fusion based quantum computing using graph states

Hub role

Work package: Quantum Information and Computing, working with Neil Walton and Thirupathaiah Vasantam

Ayalvadi Ganesh

Research interests

Random graphs and processes

• Connectivity
• Epidemics
• Opinion dynamics

Decentralised algorithms

• Information dissemination
• Collective decision-making and coordination

Stochastic optimisation

• Resource allocation
• Load balancing
• Multi-armed bandits

Hub roles

• Deputy Director
• Work package: Trustworthy Decentralised Learning

Guru Ganeshan

Research interests

• Using probabilistic and algebraic techniques to design and analyze codes/methodologies for smart data storage/retrieval with feature selection
• Analysis of classification and dynamic evolution; for example: random forest classifier,  under independent and identically distributed (i.i.d.) conditions

Hub role

• Work package: Trustworthy Decentralised Learning, working with Ayalvadi Ganesh

Po-Ling Loh

Research interests

• Theoretical statistics
• Random graphs and networks
• Robustness
• Differential privacy

Hub role

• Management committee and EDI lead
• Work package: Trustworthy Decentralised Learning

Sidharth Jaggi

Research interests

• Adversarial information-processing
• Stealthy/covert communication
• Group testing
• Network Coding

Hub roles

• Hub Director
• Work package: Trustworthy Decentralised Learning