People

Dr Russo’s research focuses on the  development of formal frameworks, algorithms and tools for distributed inference, inductive learning, abductive reasoning and their probabilistic extensions, with emphasis on their scalability and portability to small devices.  Her work has been applied to pervasive computing, policy-based network and systems management, security, declarative networking, software engineering and bioinformatics, with the emphasis to provide intelligent solutions for analysis, elaboration and adaptation software systems behaviours and their specifications.

Dr Naranker Dulay is a Reader in Computing Science at the Department of Computing at Imperial College and member of the Distributed Software Engineering  section. His research interests span security, pervasive-mobile-distributed systems, networking, software engineering, systems and network management, and applied machine learning.

Dr Krysia Broda is a Senior Lecturer and member of the Logic and Artificial Intelligence research section. Her research interests are in the area of Automate Reasoning, Inductive Logic Programming, Teleo-Reactive agents and Neural-symbolic Integration. She has supervised numerous PhD students and she is currently responsible for the MRes course offered in the Department of Computing.

Dr Dalal Alrajeh is currently a Junior Research Fellow at Imperial College London, where she was awarded her PhD in 2011 in the area of Requirements Elaboration using Machine Learning and Inductive Learning.  Her main research is on formal reasoning techniques for diagnosing and repairing faults in partial declarative specifications, and more recently on  computational methods for supporting serious crime investigations (e.g. AI-based techniques for behavioural analysis and crime linkage in serial crimes). Methods that are central to her work are model checking, inductive logic programming, abductive reasoning and answer set programming.

Dr Jiefei Ma is a research associate at Imperial College London, currently in his third year of post-doctoral research. He was awarded his PhD at Imperial College London in 2011 in the area of distributed abductive reasoning. His research interests are in the areas of Artificial Intelligence, including knowledge representation, data mining, machine learning, abductive, inductive and speculative reasoning, and applications of Artificial Intelligence, including evolvable adaptive systems, policy-based autonomous systems, multi-agent systems,  declarative distributed computing and robotics.

Dr Luke Dickens is a research associate at Imperial College London, currently in his third year of post-doctoral research. He was awarded his PhD at Imperial College London in 2010 in the area of multi-agent reinforcement learning. His research interests are in Machine Learning. including reinforcement learning, and its applications in the areas of crowd sourcing, adaptable systems, privacy and social networks.

Dr. Anna Lavygina is a research associate at the Department of Computing, Imperial College London. Her research interests include artificial intelligence, machine learning, evolutionary computation, biologically-inspired algorithms, fuzzy systems identification, optimization of multi-objective, combinatorial, dynamic constrained problems.

Nataly Maimari is a PhD student at the Department of Bioengineering under the direct joint supervision of Professor Rob Krams and Dr Alessandra Russo, and therefore an active research member of the Spike group. She is currently in her 3rd year of PhD, supported by the British Heart Foundation studentship. Her research is focus on the development of a computational framework for automatic extraction of logic-based models of gene regulatory networks from microarray data using probabilistic abductive inference and related systems, also developed within the SPIKE group. Her research activity is also in collaboration with Professor Tony Kakas at the University of Cyprus, one of the key research collaborators of the SPIKE group.

Duangtida is a PhD student, currently in her 3rd year, at the SPIKE group, Imperial College London. Her research is  focus on novel algorithms for efficient non-monotonic inductive logic programming  that can scale up to large noisy data set in real domain applications. Such algorithms should  be flexible enough to support also predicate invention, a crucial feature of any learning system in domains where the learning bias is not  fully definable a priori. Her application domains include learning user-behaviours from data collected through mobile devices in order to support automated adaptation of the devices to better meet the needs of the user.

Calin-Rares a PhD student, currently in his 2nd year, at the SPIKE group, Imperial College London. His research is currently focus on novel methods for probabilistic logical learning, exploring probabilistic extensions of established inductive logic programming (ILP) paradigms, abductive frameworks and answer-set programming (ASP) systems. His broader research interests include also applications of machine learning in bioinformatics, natural language processing and software engineering.