Research staff

A list of AIAI research staff

Member Interests
lchen
Longfei Chen Human behaviour analysis; Temporal modeling; Explainability; Visual sensing.
Xiao Chen
Xiao Chen Fault-tolerance and consistency algorithm design with reinforcement learning, consensus and trust management for blockchain and fintech systems, stochastic modelling and optimization theory.
  Mark Chevallier  
rcontreras
Ricardo Contreras Monitoring of dynamic process compositions and data processing with focus on older adults.Monitoring of dynamic process compositions and data processing with focus on older adults.
luna
Luna De Ferrari

Current role: AI coordinator for the AIM-CISC Artificial Intelligence and Multimorbidity project.

Past roles: data scientist at the Edinburgh Parallel Computing Centre and teaching coordinator for statistics and R programming, University of Edinburgh.

Research experience: Applied machine learning (deep and classic) and statistics, medical data management for AI and ML, DevOps and database administration.

pgaldi
Paola Galdi Machine learning and statistical modelling for biomedical data, multimodal data integration, network-based modelling.
  Viveka Goswami  
Dilara Kekulluoglu
Dilara Kekulluoglu  Dilara's research areas are privacy, responsible AI, human computer interaction, and computational social science. 
xli
Xue Li Knowledge representation, theory repairing by combining abduction, belief revision and conceptual change via reformation based on automated reasoning, and the applications of theory repairing.
d liu
Daxin Liu

Artificial Intelligence, Knowledge Representation and Reasoning, Modal Logic of Probabilistic Belief and Actions, Verification of Epistemic Robot Program.

knuamah
Kobby Nuamah

Hybrid and modular AI architectures using a combination of symbolic and machine learning methods towards explainability; question answering using inference over knowledge graphs; software engineering.

  Opeyemi Osakuade  
  Victor Prokhorov  
grmoreno
Guillermo Romero Moreno  Interdisciplinary research with statistical models, AI, ML, and network science applied to complex systems in various areas, such as politics, health, biology, robotics, etc.
  Richard Schmoetten