Liviu Badea

Position

Address

Degrees

• Doctorate in Computer Science from the Bucharest "Polytechnica" University 1995 (with a thesis on knowledge representation in Artificial Intelligence)
• MSc in Computer Science (with a Diploma of Merit) from the Bucharest "Polytechnica" University 1990 (with a thesis on nonlinear planning in Artificial Intelligence)

Areas of Research

• Bioinformatics (gene expression analysis, especially for various types of cancer, gene network inference, integrating bioinformatics data sources and ontologies)
• Semantic Web
• Knowledge Representation and Reasoning, Description Logics, Modal, Temporal and Dynamic Logics
• Machine Learning (Inductive Logic Programming)
• Constraint Logic Programming, Constraint Handling Rules
• Reasoning about Action and Planning
• Intelligent Information Integration
• Probabilistic network inference
• Expert Systems, Knowledge Based Systems (KBS)
• Genetic Algorithms

Description of the Research Activities

I also work on combining various molecular biology and genetics resources, such as microarray data, location analysis (regulator binding) data, gene ontologies and literature abstracts for elucidating the structure of gene networks. In this context, I have devised an improvement of constraint-based probabilistic network structure inference algorithms regarding the determination of the direction of causal influences [26,27,28].

I also studied sparse factorizations such as Nonnegative Matrix Factorization (NMF) and Positive Tensor Factorization (PTF) as clustering methods for gene expression data allowing for overlapping clusters [31,32,33]. The stability of clustering with nonnegative factorizations was addressed using an original meta-clustering approach also based on nonnegative factorizations [32].

A combined use of microarray gene expression data, functional annotations in terms of the Gene Ontology as well as an inductive learner (based on Inductive Logic Programming) have allowed us to automatically obtain functional descriptions discriminating genes differentially expressed in two recently discovered types of adenocarcinoma of the lung [Garber et al. 2001]. This work can help in automating the higher level functional analysis of gene expression data [24].

I am also involved in the European Framework Programme 6 Network of Excellence REWERSE (Reasoning on the Web with Rules and Semantics), where we develop a Semantic Web architecture for querying multiple information sources using domain-specific ontologies [30], as well as bioinformatics applications using Semantic Web technology [34].

In the past, I have been involved in several Artificial Intelligence projects in the fields of knowledge representation, computational logic, constraint logic programming, machine learning (especially inductive logic programming), genetic algorithms, AI planning, intelligent information integration and bioinformatics.

I have done extensive research in the field of description logics, especially in designing and implementing efficient inference algorithms for very expressive description logics (such as those with the transitive closure of relations). Taking into account the correspondence with various extensions of the propositional dynamic logic (PDL), the obtained results are applicable to modal, temporal and dynamic logics too. I have also been considering modal, temporal and higher order extensions of these knowledge representation languages and have investigated the associated inference problems. All these results have been validated by implementations (the RegAL and ExClaim systems).

The longer term goal of these researches is the implementation of a unified architecture for knowledge representation and reasoning, that would be used for modeling intelligent agent environments (see [8,7,14]).

In the area of machine learning, more precisely Inductive Logic Programming, I have developed a (so-called) perfect refinement operator that eliminates annoying problems occurring in all theories and implemented ILP systems [13].
In [15], I have shown that the advantages of completeness, non-redundancy and flexibility can be combined by constructing a perfect refinement operator that is "flexible". This should enable a more flexible traversal of the hypotheses space of an ILP system. Refining complete clausal theories has been investigated in [21].

In a different line of work I have constructed refinement operators for description logics (DLs) which are useful for developing learning systems in DL languages. [16] presents the first refinement operator for a DL and discusses the DL specific problems, such as example coverage, which are more complicated for DLs due to the Open World Assumption.

Additionally, I have considered the application of ILP in the domain of learning trading rules [17]. This application is interesting since it involves learning strategies in a domain in which there are no (or - in any case - very few) regularities in the historical data. It also leads in a natural way to dealing with the problem of learning from disjunctive examples (similar to multiple-instance learning).

I have also been involved in the European Project SILK (System Integration via Logic and Knowledge) dealing with intelligent integration of legacy components. The SILK architecture contains a meta-model of the components to be integrated which is used by a specilized mediator for planning and splitting user queries into queries that can be dealt with by the components [20].

We are planning to deal with integrating information sources (such as data- and knowledge bases) as well as complex applications with side-effects. To achieve this, we have developed an original partial order planning algorithm dealing with dependent fluents [22].

I have also worked in the European joint project PEKADS, which has been focused on operationalizing the KADS knowledge based systems development methodology using description logics. In this framework, I have developed and implemented a logic-based language called ExClaim (having a meta-level architecture and supporting non-determinism) for describing and executing KADS models [14].

In the European project RENEGADE, I have worked on genetic algorithms based tools for tour planning and multiple vehicle routing.
 

Interdisciplinary research interests

Publications

[40] Liviu Badea. Generalized Clustergrams for Overlapping Biclusters. Proceedings of the International Joint Conference on Artificial Intelligence IJCAI-09, Pasadena, pp 1383-1388, 2009.

[39] Liviu Badea, Vlad Herlea, Simona Dima, Traian Dumitrascu, Irinel Popescu. Combined gene expression analysis of whole-tissue and microdissected pancreatic ductal adenocarcinoma identifies genes specifically overexpressed in tumor epithelia. Hepatogastroenterology. 2008 Nov-Dec;55(88):2016-27. PMID:19260470 Supplementary information

[38] Liviu Badea. Tracking the Dimensional Evolution of Gene Expression Biclusters”. Proceedings of the 2008 International Conference on Bioinformatics & Computational Biology BIOCOMP-2008, pp.116-121.

PSB-08

[37] Liviu Badea. Extracting Gene Expression Profiles Common to Colon and Pancreatic Adenocarcinoma Using Simultaneous Nonnegative Matrix Factorization. Proc. Pacific Symposium on Biocomputing PSB-2008, pp. 267-278, World Scientific 2008.

[36] Liviu Badea. Combining Gene Expression and Transcription Factor Regulation Data using Simultaneous Nonnegative Matrix Factorization. Proc. BIOCOMP-2007, CSREA Press, pp. 127-131.

[35] Liviu Badea, Doina Tilivea. Stable Biclustering of Gene Expression Data with Nonnegative Matrix Factorizations. Proceedings of the International Joint Conference on Artificial Intelligence IJCAI-07, Hyderabad, India, pp. 2651-2656.

[34] Liviu Badea. Semantic Web Reasoning for Analyzing Gene Expression Profiles. Proceedings Principles and Practice of Semantic Web Reasoning, PPSWR 2006, LNCS 4187, pp. 78-89, Springer Verlag.

[33] Liviu Badea, Doina Tilivea. Meta-clustering Gene Expression Data with Positive Tensor Factorizations. Proceedings European Conference on Artificial Intelligence ECAI-06, p. 787, IOS Press 2006.

[32] Liviu Badea. Clustering and Metaclustering with Nonnegative Matrix Decompositions. Proc. of the European Conference on Machine Learning ECML-05. Lecture Notes in Artificial Intelligence, Vol. 3720, pp. 10-20, Springer Verlag, 2005. (C) Springer Verlag.

[29] Rolf Backofen, Mike Badea, Pedro Barahona, Liviu Badea, François Bry, Gihan Dawelbait, Andreas Doms, François Fages, Carole Goble, Andreas Henschel, Anca Hotaran, Bingding Huang, Ludwig Krippahl, Patrick Lambrix, Werner Nutt, Michael Schroeder, Sylvain Soliman, Sebastian Will. Towards a semantic web for bioinformatics. (Poster) In: Proceedings of "Bioinformatics 2004", Linköping, Sweden (3rd - 6th June 2004), SocBIN - Society for Bioinformatics in the Nordic countries.
 
 

[28] Liviu Badea - Determining the Direction of Causal Influence in Large Probabilistic Networks: A Constraint-Based Approach. Proceedings of the European Conference on Artificial Intelligence ECAI 2004, IOS Press, pp. 263-267.

 

ISMB-2004

[27] Liviu Badea - Extracting networks of influences from microarray data. ISMB-2004 poster.

 

[26] Liviu Badea - Inferring large gene networks from microarray data: a constraint-based approach. International Joint Conference on Artificial Intelligence IJCAI-03, Proceedings of the Workshop on Learning Graphical Models for Computational Genomics, 2003.

 

CMSB-2003

[25] Liviu Badea, Doina Tilivea - Integrating biological process modelling with gene expression data and ontologies for functional genomics (position paper). Computational Methods in Systems Biology, Proceedings. LNCS 2602, pp.187-193. (C) Springer Verlag.

 

PSB-2003

[24] Liviu Badea - Functional discrimination of gene expression patterns in terms of the Gene Ontology, Proc. of the Pacific Symposium on Biocomputing PSB-2003, World Scientific 2003, pp.565-576.

 

FQAS-2002

[23] Liviu Badea, Doina Tilivea - Intelligent Information Integration as a Constraint Handling Problem, Proc. of the Fifth International Conference on Flexible Query Answering Systems (FQAS-2002), October 27 - 29, 2002, Copenhagen, Lecture Notes In Computer Science, Vol. 2522, pp. 12-27, Springer Verlag, 2002.

 

[22] Liviu Badea, Doina Tilivea - Abductive Partial Order Planning with Dependent Fluents. In Franz Baader, Gerhard Brewka, Thomas Eiter (Eds.): KI-2001: Advances in Artificial Intelligence, Joint German/Austrian Conference on AI, Vienna, September 19-21, 2001. Lecture Notes in Computer Science 2174 Springer 2001, pp. 63-77.

[21] Liviu Badea - A Refinement Operator for Theories. Inductive Logic Programming : 11th International Conference, ILP-2001, Strasbourg, France, September 9-11, 2001, Lecture Notes in Computer Science, Volume 2157, pp.1-14, Springer Verlag, 2001.
 

[20] Liviu Badea - Query Planning for Intelligent Information Integration using Constraint Handling Rules.  IJCAI-2001 Workshop on Modeling and Solving Problems with Constraints (Seattle, August 2001).

[19] Badea Liviu - Learning Trading Rules with Inductive Logic Programming.  In Ramon López de Mántaras, Enric Plaza (Eds.): ECML-2000 (11th European Conference on Machine Learning, Barcelona), Lecture Notes in Computer Science, Vol. 1810, Springer, 2000, pp. 39-46.

[18] Liviu Badea, Shan Hwei Nienhuys-Cheng - A Refinement Operator for Description Logics.
In James Cussens, Alan M. Frisch (Eds.): 10th International Conference on Inductive Logic Programming ILP-2000, London, Lecture Notes in Computer Science, Vol. 1866, Springer, 2000, pp. 40-59.

[17] Liviu Badea, Shan-Hwei Nienhuys-Cheng - Refining Concepts in Description Logics.
In Franz Baader, Ulrike Sattler (Eds.): Proceedings of the 2000 International Workshop on Description Logics (DL2000), RWTH Aachen, 2000, pp. 31-44.

[16] Liviu Badea, Shan-Hwei Nienhuys-Cheng – Learning in Description Logics by Refining Concepts, Proceedings of the 12th Belgium-Netherlands Artificial Intelligence Conference BNAIC'2000.
 

[15] Liviu Badea - Perfect Refinement Operators can be Flexible. European Conference on Artificial Intelligence ECAI-2000, Berlin, pp.266-270.

 

[14] Liviu Badea - Knowledge Modelling and Reusability in ExClaim. Proceedings of the International Joint Conference on Artificial Intelligence IJCAI-99, Stockholm, 1999, pp. 606-613.

 

[13] Liviu Badea, Monica Stanciu - Refinement Operators can be (Weakly) Perfect. in Saso Dzeroski and Peter Flach (eds) - Proceedings of the 9th International Conference on Inductive Logic Programming (ILP-99), Bled, 1999, pp.21-32, (C) Springer Verlag.

 

[12] Liviu Badea - Planning in Description Logics: Deduction versus Satisfiability Testing. in Henri Prade (ed) - Proceedings of the European Conference on Artificial Intelligence, Brighton 1998, pp. 479-483, Wiley and Sons, 1998.

[11] Liviu Badea - Encoding Planning in Description Logics: Deduction versus Satisfiability Testing, Proceedings of the ESSLLI-98 Workshop on Reasoning about Actions: Foundations and Applications, Saarbruecken, August 17 - 21, 1998.

[10] Liviu Badea - Planning in Description Logics: Deduction versus Satisfiability Testing, in Henri Prade (ed) - Proceedings of the 1998 International Workshop on Description Logics (DL'98), IRST, Povo-Trento, June 6-8, 1998.
 

[9] Liviu Badea - Reifying Concepts in Description Logics - Proceedings of the International Conference on Artificial Intelligence IJCAI'97, Morgan Kaufmann 1997, pp.142-149.

 

	[8] Liviu Badea - A unified architecture for knowledge representation based on description logics, in Wolfgang Wahlster (ed) - Proceedings of the European Conference on Artificial Intelligence, Budapest 1996, pp. 282-286, Wiley and Sons, 1996.
	[7] Liviu Badea - ExClaim: a hybrid language for knowledge representation and reasoning using description logics - Proceedings of the ECAI'96 Workshop on "Validation, Verification and Refinement of Knowledge-Based Systems", Budapest 1996.

[6] Liviu Badea - A practical decision method for logics of action and time, submitted.

[5] Liviu Badea - Towards a unified architecture for knowledge representation and reasoning based on description logics, Proc. Int. Workshop on Description Logics DL'95, Universita La Sapienza, Rome, June 1995, pp. 32-37.

[4] Liviu Badea - A unified architecture for knowledge representation based on terminological logics, Studies in Informatics and Control, Vol. 4, No. 2, June 1995.

[3] Liviu Badea, Stefan Trausan-Matu - Specification of Term Subsumption Languages for KADS Operationalization, PEKADS Technical Report WP4/TR/4.2.1/1.0.

[2] Liviu Badea, Doina Tilivea - ExClaim: a language for operationalizing CommonKADS expertise models using description logics, PEKADS Technical Report PEKADS/WP4/TR/4.5.1

[1] Liviu Badea - Analiza si evaluarea principalelor shell-uri si medii de programare existente pentru elaborarea de sisteme experte, Revista Romana de Informatica si Automatica, Vol. 1, nr. 3-4, 1991, pp. 29-44.
 

Systems developed

ExClaim (Executable CommonKADS Language for Integrated Modeling) - a knowledge based systems development language with knowledge modeling, execution and simulation facilities (based on description logics)

ReGAL - a DL-based knowledge representation language GENITOUR - a genetic algorithms based environment for tour planning (for multiple vehicle routing)

Participation in International Projects

Programming languages

Foreign languages