ioannis tsamardinos curriculum v · ph.d. – 2015 georgia orphanoudaki biology dept. un. of crete...
TRANSCRIPT
IOANNIS TSAMARDINOS CURRICULUM VITAE
Current Affiliations: Contact Information:
Associate Professor, Un. Crete: +30 (2810) 393 575
Department of Computer Science (CSD), Cellular: +30 (6978) 145 614
University of Crete (UOC)
Co-Founder, Email Addresses:
Visiting Professor
School of Computing and Engineering Web sites:
University of Huddersfield www.mensxmachina.org
www.gnosisda.gr
Contents General Information .................................................................................................................................................. 2
Summary Statistics of Research Recognition ............................................................................................................ 4
Academic Information ............................................................................................................................................... 5
Community Service ................................................................................................................................................... 8
Research .................................................................................................................................................................. 13
Recognition ............................................................................................................................................................. 27
Research Funding .................................................................................................................................................... 32
Innovation and Commercialization.......................................................................................................................... 36
General Information
Personal
Born in Thessaloniki, Greece in 1973. Greek citizenship. Military obligations fulfilled Feb.
2006 – Aug. 2006. Fluent in Greek and English.
Research Interests
Machine Learning, Data Science, Bioinformatics, Artificial Intelligence, Causal Inference
and Induction, Learning from Biomedical Data, Feature and Variable Selection, Applica-
tions of Machine Learning in Biomedical Informatics, Integrative Causal Analysis
Positions
Dates Title Institution
Jul 2017 – Present Vising Professor University of Huddersfield
Oct. 2013 – Present Founder and CEO Gnosis Data Analysis PC
July 2013 – Present Associate Professor CSD-UOC
Jan. 2011 –Dec. 2013 Head of Bioinformatics Lab. ICS-FORTH1
Sep. 2006 –Jun 2013 Assistant Professor CSD-UOC
Sep. 2006– Oct. 2015 Affiliated Research Scientist ICS-FORTH
Feb. 2006–2013 Adjunct Assistant Professor DBMI, Vanderbilt University
Nov. 2001 – Feb. 2006 Assistant Professor DBMI, Vanderbilt University
Jun. 1997 – Aug. 1997 Intern Caelum Research
NASA Ames Research Cen-
ter, Moffett Field, CA
Education
Dates-Degree Institution Dissertation Title
Aug. 2001,
Ph.D.
Intelligent Systems Pro-
gram, University of Pitts-
burgh
Constraint-based Temporal Reasoning
Algorithms and Applications to Planning
Jul. 1998, M.Sc. Intelligent Systems Pro- Reformulating Temporal Plans for Effi-
1 Institute of Computer Science, Foundation for Research and Technology
gram, University of Pitts-
burgh
cient Execution
Jul. 1995, B.Sc. Department of Computer
Science, University of
Crete
SM (Storage Manager): A Distributed Sys-
tem of Hierarchical Management of Rela-
tional Multimedia Databases, GPA
8.71/10.0, Graduated second in class
Summary Statistics of Research Activity and Recognition (last update 10 September 2017)
Peered-reviewed publica-tions
98
Journal papers 40
Conference papers 54
Book chapters 4
Google scholar
Citations 5658
h-index 29
I10-index 58
Publish or Perish (query: “tsamardinos”)
Citations 5837
h-index 30
hI,norm 20
Google Scholar profile https://scholar.google.gr/citations?user=7fendUwAAAAJ&hl=en
LinkedIn https://www.linkedin.com/in/ioannis-tsamardinos-8831077
ResearchGate https://www.researchgate.net/profile/Ioannis_Tsamardinos/
Academia.edu https://crete.academia.edu/IoannisTsamardinos
Group’s page www.mensxmachina.org
Public Videos For a full list please check http://mensxmachina.org/en/presentations/
Google Scholar citation profile (citations for 2017 not fully indexed yet)
Academic Information
Graduate Programs Participation
Dates Title
2007 – present Member of the Graduate Program of the Computer Science De-
partment, University of Crete
2011 – present Member of the Brain and Mind Graduate Program, inter-
departmental, University of Crete
2016 – present Member of the Bioinformatics Graduate Program, School of
Medicine, University of Crete
Course Teaching
Dates Title Institution
2016 – present Biostatistics Medical School, University
of Crete (supervisor)
2016 – present Data Analysis Methods in Bioinformat-
ics
Medical School, University
of Crete (co-instructor)
2011- present HY119, Linear Algebra CSD, University of Crete
2006 - present HY577, Machine Learning CSD, University of Crete
2008 - present HY482, Algorithms in Bioinformatics CSD, University of Crete &
Medical School, UoC (co-
instructor)
2008 - present HY387, Intr. to Artificial Intelligence CSD, University of Crete
2006, 2007 HY150, Programming CSD, University of Crete
2003, 2004 DBMI 330, 330a, Biomedical Artificial
Intelligence (and lab)
DBMI, Vanderbilt Universi-
ty
Student Supervision
Degree Name Institution
Ph.D. ongoing Giorgos Borboudakis CSD, University of Crete
Ph.D. – 2015 Sofia Triantafillou CSD, University of Crete
Ph.D. – 2010 Laura E. Brown DBMI, Vanderbilt University
Masters – ongoing Klio Verrou Bioinformatics, Medical School,
UOC
Masters – ongoing Zacharias Papadovasilakis Bioinformatics, Medical School,
UOC
Masters – ongoing Christos Tselas CSD, University of Crete
Masters – 2017 Roubini Xenou CSD, University of Crete
Masters – 2017 Elissavet Greasidou CSD, University of Crete
Masters – 2016 Georgios Athinaiou CSD, University of Crete
Masters – 2016 Anna Roubelaki CSD, University of Crete
Masters – 2015 Panayiotis Tzirakis CSD, University of Crete
Masters – 2015 Konstantinos Kerkentzes CSD, University of Crete
Masters – 2013 Giorgos Borboudakis CSD, University of Crete
Masters – 2011 Angelos Armen CSD, University of Crete
Masters - 2006 Laura E. Brown DBMI, Vanderbilt University
Masters - 2006 Lawrence Fu DBMI, Vanderbilt University
Committee Member
Degree Name Institution
Ph.D. – ongoing Achilleas Nikolaos Doygalis CSD, University of Crete
Ph.D. – ongoing Kostas Varsos CSD, University of Crete
Ph.D. – ongoing Giorgos Simantiris CSD, University of Crete
Ph.D. – 2016 Sofia Kleisarchaki University Grenoble Alps
Ph.D. – 2016 Maria Paraskeyopoyloy Dept. of Mechanical Engineering,
University of Thessaly
Ph.D. – 2015 Giorgio Lucio Papadopoulos Biology Dept. Un. of Crete
Ph.D. – 2015 Georgia Orphanoudaki Biology Dept. Un. of Crete
PhD. – 2014 Nikos Kyriazis CSD, University of Crete
Ph.D. – 2013 Ghada Trabelsi Ecole Polytechnique de l'université
de Nantes
Ph.D. – 2013 Nestoras Karathanasis Biology Dept. Un. of Crete
Ph.D. – 2013 Amanullah Yasin Universite de Nantes
Ph.D. – 2013 Grace Huang University of Pittsburgh
Ph.D. – 2013 Antti Hyttinen Comp. Sci. Dept, Un. Helsinki
Ph.D. – 2011 Maria Markaki CSD, University of Crete
Ph.D. – 2011 Giorgos Tzanis Dept. of Informatics, AUTH
Ph.D. – 2011 Paktos Theodoros CSD, University of Crete
Ph.D. – 2009 Vassilis Tsiaras CSD, University of Crete
Ph.D. – 2008 Alexander Statnikov DBMI, Vanderbilt University
Ph.D. – 2008 Yindalon Aphinyanaphongs DBMI, Vanderbilt University
Masters – 2017 Dimitris Degiannis CSD, University of Crete
Masters – 2016 Maria Plakia CSD, University of Crete
Masters – 2016 Gouidis Filippos CSD, University of Crete
Masters – 2015 Charonyktakis Pavlos CSD, University of Crete
Masters – 2013 Douvatzis Petros CSD, University of Crete
Masters – 2012 Sofia Kleisarhaki CSD, University of Crete
Masters – 2012 Vasilis Efthymiou CSD, University of Crete
Masters – 2011 Chrysi Filipaki CSD, University of Crete
Masters – 2011 Giorgos Hatzivasilis CSD, University of Crete
Masters – 2009 Dimitrios Velegrakis CSD, University of Crete
Masters – 2009 Aikaterini Ghirzou CSD, University of Crete
Masters – 2009 Maria Kalaitzaki CSD, University of Crete
Masters – 2009 Michalis Moudatsos CSD, University of Crete
Masters – 2008 Evaggelia Kassapaki CSD, University of Crete
Masters – 2008 Yiannis Lilis CSD, University of Crete
Masters – 2005 Yindalon Aphinyanaphongs DBMI, Vanderbilt University
Masters – 2005 Nafeh Fananapazir DBMI, Vanderbilt University
Masters – 2005 Alexander Statnikov DBMI, Vanderbilt University
Prof. Tsamardinos has supervised the following number of Undergraduate Dissertations between the years 2010-
2016 respectively 3, 3, 6, 4, 2, 2, 1.
Community and Administrative Service
Conference Organization
Dates Role Title
2017 Founder, organiz-
ing committee
MASSCAUSAL 2, Second International Workshop on
Computational Methods for Single-Cell Data
http://mensxmachina.org/en/causalpath-masscausal-
workshop-2017/
2017 Organizing Com-
mittee
Hellenic Bioinformatics (HBIO 2017) conference: Bioin-
formatics and its applications in Health, Biodiversity and
the Environment
2015 Founder, organiz-
ing committee
MASSCAUSAL, Causal Discovery and Modelling of Sig-
nal Pathways with Mass Cytometry Data,
http://www.mensxmachina.org/causalpath/workshop.html
2012 Local Organizing
Committee
7th Conference of the Hellenic Society for Computational
Biology & Bioinformatics - HSCBB12
2011 Area Chair European Conference in Machine Learning (ECML –
2011)
2011 Senior PC member 22nd International Joint Conference in Artificial Intelli-
gence (IJCAI 2011)
2007 Co-organizer Hellenic Bioinformatics & Medical Informatics Meeting
Reviewer for Scientific Journals
Dates Field Title
2017 Artificial Intelligence Transactions on Knowledge and Data Engineering
2016 Statistics Behaviormetrics
Bioinformatics Bioinformatics Journal
Artificial Intelligence Artificial Intelligence Journal
Artificial Intelligence International Journal on Artificial Intelligence Tools
2015 Machine Learning Journal of Machine Learning Research
Computer Science Information Sciences
Artificial Intelligence Knowledge and Information Systems
Machine Learning IEEE Transactions on Neural Networks and Learning
Systems
2014 Files lost
2013 Files lost
2012 Statistics Annals of Statistics
Pattern Recognition Transactions on Pattern Analysis and Machine Intelli-
gence
Computer Science International Journal of Approximate Reasoning
Machine Learning Journal of Machine Learning Research
2011 Artificial Intelligence Applied Artificial Intelligence, Special Issue on Event
Recognition
Artificial Intelligence Transactions on Knowledge and Data Engineering
Machine Learning Journal of Machine Learning Research
Bioinformatics BMC Bioinformatics
2010 Artificial Intelligence Knowledge and Information Systems
Machine Learning Journal of Machine Learning Research
Bioinformatics Bioinformatics
2009 Bioinformatics BMC Bioinformatics
Computer Science International Journal of Approximate Reasoning
Machine Learning Journal of Machine Learning Research
Pattern Recognition IEEE Trans. on Pattern Analysis and Machine Intelli-
gence
Artificial Intelligence Transactions on Knowledge and Data Engineering
2008 Machine Learning Journal of Machine Learning Research
2007 Machine Learning Machine Learning Journal
Bioinformatics Bioinformatics
Bioinformatics BMC Bioinformatics
Machine Learning Journal of Machine Learning Research
2006 Machine Learning Journal of Machine Learning Research
Artificial Intelligence Journal of Artificial Intelligence Research
2005 Artificial Intelligence Decision Support Systems Journal
Artificial Intelligence Artificial Intelligence Journal
2004 Artificial Intelligence International Journal of Pattern Recognition and A.I
Artificial Intelligence AI Communications Journal
2003 Artificial Intelligence Journal of Artificial Intelligence Research
2002 Artificial Intelligence Journal of Artificial Intelligence Research
Reviewer for Conferences
2010 Medical Informatics Virtual Physiological Human Conference
2009 Artificial Intelligence International Conference on Intelligent Systems Design
and Applications
2005 Bioinformatics Pacific Symposium in Bioinformatics (PSB)
Medical Informatics 11th World Congress on Medical Informatics, ME-
DINFO
2003 Medical Informatics American Medical Informatics Associations, AMIA
2002 Artificial Intelligence First Eur. Starting AI Researcher Symposium, STAIRS
Artificial Intelligence Second Hellenic Conference on AI, SETN
2001 Planning European Conference in Planning, ECP
Artificial Intelligence American Association for Artificial Intelligence, AAAI
Program Committee Member
2017 Artificial Intelligence American Association Artificial Intelligence (AAAI
2017)
Machine Learning International Conference on Machine Learning (ICML
2017)
Machine Learning KDD Causality Workshop (KDD CD 2017)
Machine Learning Neural Information Processing Systems (NIPS 2017)
Machine Learning Uncertainty in Artificial Intelligence (UAI 2017)
Artificial Intelligence American Association for Artificial Intelligence (AAAI
2017)
Computer Science 22nd IEEE International Symposium on Computer and
Communications (ISCC 2017)
2016 Artificial Intelligence Uncertainty in Artificial Intelligence (UAI 2016)
Artificial Intelligence International Joint Conference in Artificial Intelligence
(IJCAI 2016)
Machine Learning KDD 2016 Workshop on Causality
Artificial Intelligence Hellenic Conf. on Artificial Intelligence (SETN 2016)
2015 Bioinformatics Hellenic Society Computational Biology and Bioinfor-
matics (HSCBC 2015)
Artificial Intelligence UAI 2015, Workshop on Causality
2014 Files lost
2013 Files lost
2012 Artificial Intelligence European Conference in Artificial Intelligence (ECAI
2012)
Artificial Intelligence 7th Hellenic Conf. on Artificial Intelligence (SETN
2012)
2011 Artificial Intelligence Artificial Intelligence and Soft Computing (ASC 2011)
Artificial Intelligence Uncertainty in Artificial Intelligence (UAI 2012)
2010 Artificial Intelligence 6th Conference of the Hellenic AI Society (SETN-
2010)
Machine Learning Int. Work. on Feature Selection in Data Mining
(FSDM)
Machine Learning 20th Int. Conference on Artificial Neural Networks
Bioinformatics 10th IEEE International Conference on Information
Technology and Applications in Biomedicine (ITAB)
Machine Learning Uncertainty in Artificial Intelligence (UAI 2010)
Biomedical Inf. 12th Mediterranean Conference on Medical and
Biological Engineering and Computing – MEDICON
2009 Medical Informatics International Conference on Health Informatics
(HEALTHINF)
Planning International Conference on Automated Planning and
Scheduling (ICAPS)
2008 Bioinformatics 8th IEEE International Conference on Bioinformatics
and Bioengineering (BIBE)
2008 Machine Learning Workshop on Feature Selection in Data Mining
(FSDM)
Artificial Intelligence 20th International Conference on Tools with Artificial
Intelligence, ICTAI
Artificial Intelligence 5th Hellenic Conference on Artificial Intelligence,
SETN
2006 Artificial Intelligence FLAIRS
2004 Artificial Intelligence American Association for Artificial Intelligence (AAAI)
Artificial Intelligence Third Hellenic Conference on AI, SETN
Scientific Proposal Evaluation
2017 Swiss National Science Foundation, National Research Council
National Center of Science & Technology Evaluation, Republic of Kazakhstan
2016 Netherlands eScience Center (NLeSC), Netherlands Organisation for Scientific Re-
search Physical Sciences (NWO)
2015 Fondazione Cassa di Risparmio di Padova e Rovigo
Academic Service and Administrative Activities
Date Type Institution
2017 Faculty Tenure Committee for Chris-
toforos Nikolaou
Biology Department, University
of Crete
2017 Faculty Electoral Committee Department of Computer Sci-
ence and Engineering, Univer-
sity of Ioannina
2017 Faculty Electoral Committee Department of Molecular Biol-
ogy and Genetics, Democritus
University of Thrace
2016 Promotion Electoral Committee for
Pantelis Topalis
Institute of Molecular Biology
and Biotechnology, FORTH
2016 Promotion Committee for Ioannis
Basdekis
Institute of Computer Science,
FORTH
2016 Faculty Electoral Committee Informatics Department, Aristo-
tle University of Thessaloniki
2016-2018 Committee for Undergraduate Studies
(Επιτροπή Σπουδών Τμήματος)
CSD, University of Crete
2015-2016 Graduate Admissions Committee
Member
CSD, University of Crete
2014-2015 Graduate Admissions Committee
Member
CSD, University of Crete
2013-2014 Coordinator Graduate Admissions
Committee
CSD, University of Crete
2011-2012 Graduate Studies Committee Member CSD, University of Crete
2012 Faculty Electoral Committee CSD, University of Crete
2011-2012 Coordinator Graduate Admissions
Committee
CSD, University of Crete
2010 Faculty recommendation committee Medical School, University of Pa-
tras
2010 Faculty Electoral Committee Biology Dept., University of Crete
2009 Faculty recommendation committee Dept. of Agricultural Biotechnolo-
gy, Agricultural University of Ath-
ens
2008-09 Graduate Studies Committee Member CSD, University of Crete
2007-08 Undergraduate Studies Committee
Member
CSD, University of Crete
2006-2007 Graduate Admissions Committee
Member
CSD, University of Crete
2001-2006 Graduate Admissions Committee
Member
DBMI, Vanderbilt University
Research
All publication texts are available at the website www.mensxmachina.org . Due to
copyright restrictions some publications may not appear in their published format.
Reviewed Scientific Publications
Citation
Legend: Type : C – Conference, J – Journal, BC – Book Chapter
2017
[1] George Froudakis, George Borboudakis, Taxiarchis Stergiannakos, Maria Frysali,
Emanuel Klontzas, and Ioannis Tsamardinos, “Chemically-intuited, large-scale
screening of MOFs by machine learning techniques”, (to appear) NPJ Computation-
al Materials
J
[2] Sofia Triantafillou, Vincenzo Lagani, Christina Heinze-Deml, Angelika Schmidt,
Jesper Tegner, Ioannis Tsamardinos, "Predicting Causal Relationships from Biolog-
ical Data: Applying Automated Casual Discovery on Mass Cytometry Data of
Human Immune Cells", (to appear) Scientific Reports, (2017)
J
[3] Konstantinos Tsirlis, Vincenzo Lagani, Sofia Triantafillou, Ioannis Tsamardinos,
"On Scoring Maximal Ancestral Graphs with the Max-Min Hill Climbing Algo-
rithm", 23d ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining (KDD 2017), (2017)
C
[4] Michail Tsagris, Giorgos Borboudakis, Vincenzo Lagani, Ioannis Tsamardinos,
"Constraint-based Causal Discovery with Mixed Data", 23d ACM SIGKDD Inter-
national Conference on Knowledge Discovery and Data Mining (KDD 2017), (2017)
C
[5] Vincenzo Lagani, Giorgos Athineou, Alessio Farcomeni, Michail Tsagris, Ioannis
Tsamardinos (2016): “Feature Selection with the R Package MXM: Discovering
Multiple, Statistically-Equivalent, Predictive Feature Subsets”, Journal of Statisti-
cal Software v80(7), 2017 doi: 10.18637/jss.v080.i07
J
[6] Georgia Orfanoudaki, Maria Markaki, Katerina Chatzi, Ioannis Tsamardinos, and
Anastassios Economou, “MatureP: prediction of secreted proteins with exclusive in-
formation from their mature regions”, Scientific Reports 7, 2017, doi:10.1038/s41598-
017-03557-4
J
[7] Georgios Papoutsoglou, Giorgos Athineou, Vincenzo Lagani, Iordanis Xanthopou-
los, Angelika Schmidt, Szabolcs Éliás, Jesper Tegnér, Ioannis Tsamardinos: “SCEN-
ERY: a web application for (causal) network reconstruction from cytometry da-
ta”, Nucleic Acids Research 37, p. D412-D416, doi:10.1093/nar/gkx448
J
[8] Siomos K, Papadakis E, Tsamardinos I, Kerkentzes K, Koygioylis M, Trakatelli
CM, “Prothrombotic and Endothelial Inflammatory Markers in Greek Patients
with Type 2 Diabetes Compared to Non-Diabetics”, Endocrinology & Metabolic
Syndrome 2017, 6:1, DOI: 10.4172/2161-1017.1000259
J
2016
[9] Nestoras Karathanasis, Ioannis Tsamardinos, Vincenzo Lagani, “omicsNPC: apply-
ing the Non-Parametric Combination methodology to the integrative analysis of heter-
ogeneous omics data”, PLoS ONE 11(11): e0165545.
doi:10.1371/journal.pone.0165545
J
[10] Vincenzo Lagani, Argyro D. Karozou, David Gomez-Cabrero, Gilad Silberberg
and Ioannis Tsamardinos, “A comparative evaluation of data-merging and meta-
analysis methods for reconstructing gene-gene interactions”, BMC Bioinformatics
17(5), 287-305, 2016, doi=10.1186/s12859-016-1038-1
J
[11] Anna Roumpelaki, Giorgos Borbudakis, Sofia Triantafillou and Ioannis Tsamar-
dinos, “Marginal causal consistency in constraint-based causal learning”, UAI
2016, Workshop Causation: Foundation to Application
C
[12] Sofia Triantafillou and Ioannis Tsamardinos, “Score based vs constraint based
causal learning in the presence of confounders”, UAI 2016 workshop Causation:
Foundation to Application.
C
[13] Giorgios Borboudakis, Ioannis Tsamardinos, “Towards Robust and Versatile
Causal Discovery for Business Applications”, 22nd ACM SIGKDD Conference on
Knowledge Discovery and Data Mining (KDD 2016)
C
[14] G. Athineou, G. Papoutsoglou, S. Triantafullou, I Basdekis, V. Lagani, I. Tsamar-
dinos (2016): “SCENERY: a Web-Based Application for Network Reconstruction
and Visualization of Cytometry Data”, 10th International Conference on Practical
Applications of Computational Biology & Bioinformatics (PACBB 2016).
C
2015
[15] Christina Papagiannopoulou, Grigorios Tsoumakas, Ioannis Tsamardinos, “Dis-
covering and Exploiting Entailment Relationships in Multi-Label Learning”,
ACM SIGKDD Conference on Knowledge Discovery and Data Mining 2015 (KDD)
C
[16] Giorgos Borboudakis, Ioannis Tsamardinos, “Bayesian Network Learning with
Discrete Case-Control Data”, Uncertainty in Artificial Intelligence (UAI), 2015
C
[17] Nestoras Karathanasis, Ioannis Tsamardinos, Panayiota Poirazi, “MiRdu-
plexSVM: A High-Performing MiRNA-Duplex Prediction and Evaluation Meth-
odology”, PLoS ONE 10(5): e0126151. doi:10.1371/journal.pone.0126151
J
[18] Vincenzo Lagani, Franco Chiarugi, Dimitris Manousos, Vivek Verma, Jo Fursse,
Kostas Marias, Ioannis Tsamardinos, “Realization of a service for the long-term risk
assessment of diabetes-related complications”, Journal of Diabetes and its Complica-
J
tions 29(5), p. 691-698, 2015
[19] Vincenzo Lagani, Sofia Triantafillou, Gordon Ball, Jesper Tegner, Ioannis Tsa-
mardinos, “Probabilistic Computational Causal Discovery for Systems Biology”, in
Uncertainty in Biology, A computational Modeling Approach, Springer 2015, (Eds)
Liesbet Geris, David Gomez-Cabrero
BC
[20] Vincenzo Lagani, Franco Chiarugi, Shona Thomson, Jo Fursse, Edin Lakasing,
Russell W. Jones, Ioannis Tsamardinos, “Development and validation of risk as-
sessment models for diabetes-related complications based on the DCCT/EDIC
data”, Journal of Diabetes and Its Complications 2015 May-Jun;29(4):479-87. doi:
10.1016/j.jdiacomp.2015.03.001
J
[21] Sofia Triantafillou, Ioannis Tsamardinos, “Constraint-based Causal Discovery
from Multiple Interventions over Overlapping Variable Sets”,
16(Nov):2147−2205, 2015 Journal of Machine Learning Research
J
[22] Ioannis Tsamardinos, Amin Rakhshani, and Vincenzo Lagani, “Performance-
Estimation Properties of Cross-Validation-Based Protocols with Simultaneous
Hyper-Parameter Optimization”, Int. J. Artif. Intell. Tools 24, 1540023 (2015)
https://doi.org/10.1142/S0218213015400230
J
[23] Grace T. Huang, Ioannis Tsamardinos, Vineet Raghu, Naftali Kaminski, Panayi-
otis V. Benos, “T-Recs: Stable selection of Dynamically Formed Groups of Fea-
tures with Application to Prediction of Clinical Outcomes”, Pacific Symposium on
Biocomputing (PSB) 2015
C
2014
[24] Kerkentzes Konstantinos, Lagani Vincenzo, Tsamardinos Ioannis, Vyberg Mo-
gens, Oluf D. Røe, “Hidden treasures in “ancient” microarrays: Gene expression
portrays biology and potential resistance pathways of major lung cancer subtypes
and normal tissue”, Frontiers in Oncology 4, 2014, doi: 10.3389/fonc.2014.00251
J
[25] Sofia Triantafillou, Ioannis Tsamardinos, and Anna Roumpelaki, “Learning
Neighborhoods of High Confidence in Constraint-Based Causal Discovery”, the
Seventh European Workshop on Probabilistic Graphical Models (PGM), 2014
C
[26] Nestoras Karathanasis; Ioannis Tsamardinos; Panayiota Poirazi, “Don't use a
cannon to kill the ... miRNA mosquito”, Bioinformatics 2014; doi:
10.1093/bioinformatics/btu100
J
[27] Ioannis Tsamardinos, Amin Rakhshani, Vincenzo Lagani, “Performance-
Estimation Properties of Cross-Validation-Based Protocols with Simultaneous
Hyper-Parameter Optimization”, 8th Hellenic Conference on Artificial Intelligence
(SETN) 2014
C
2013
[28] Ismene Karakasilioti, Irene Kamileri, Georgia Chatzinikolaou, Theodoros Kos-
teas, Eleni Vergadi, Andria Rasile Robinson, Ioannis Tsamardinos, Tania A. Rozgaja,
J
Sandra Siakouli, Christos Tsatsanis, Laura J. Niedernhofer, and George A. Garinis,
“DNA Damage Triggers a Chronic Autoinflammatory Response, Leading to Fat
Depletion in NER Progeria” Cell Metabolism 18(3), Sep. 2013, 403-415
[29] Nestoras Karathanasis, Angelos Armen, Ioannis Tsamardinos and Panayiota
Poirazi, “A bioinformatics approach for investigating the determinants of Drosha
processing”, 13th IEEE International Conference on Bioinformatics and Bioengineer-
ing (IEEE BIBE 2013)
C
[30] Giorgos Borboudakis, Ioannis Tsamardinos, “Scoring and Searching over
Bayesian Networks with Informative, Causal and Associative Priors”, Uncertainty
in Artificial Intelligence (UAI) 2013
C
[31] Vincenzo Lagani, George Kortas, Ioannis Tsamardinos, “Biomarker signature
identification in “omics” data with multi-class outcome”, Computational and Struc-
tural Biotechnology Journal 6, jun. 2013
J
[32] Hunter P, Chapman T, Coveney PV, de Bono B, Diaz V, Fenner J, Frangi AF,
Harris P, Hose R, Kohl P, Lawford P, McCormack K, Mendes M, Omholt S, Quartero-
ni A, Shublaq N, Ska°r J, Stroetmann K, Tegner J, Thomas SR, Tollis I, Tsamardinos I,
van Beek JHGM, Viceconti M. 2013 “A vision and strategy for the VPH: 2012 up-
date”. Interface Focus 2013 3, 20130004. http://dx.doi.org/10.1098/rsfs.2013.0004
J
[33] Giorgio L Papadopoulos, Elena Karkoulia, Ioannis Tsamardinos, Catherine Porch-
er, Jiannis Ragoussis, Jorg Bungert and John Strouboulis, “GATA-1 genome-wide
occupancy associates with distinct epigenetic profiles in mouse fetal liver erythro-
poiesis”, Nucleic Acids Research Journal 41(9) 2013 doi: 10.1093/nar/gkt167
J
[34] Sophia Kleisarchaki, Dimitris Kotzinos, Ioannis Tsamardinos, and Vassilis Chris-
tophides, “A Methodological Framework for Statistical Analysis of Social Text
Stream”, International Workshop on Information Search, Integration and Personaliza-
tion (ISIP 2012), 2013
C
[35] Vincenzo Lagani, Lefteris Koumakis, Franco Chiarugi, Edin Lakasing, Ioannis
Tsamardinos, “A systematic review of predictive risk models for diabetes compli-
cations based on large scale clinical studies”, Journal of Diabetes and Its Complica-
tions, 2013 http://dx.doi.org/10.1016/j.jdiacomp.2012.11.003
J
2012
[36] Nestoras Karathanasis, Angelos Armen, Ioannis Tsamardinos and Panayiota
Poirazi, “SVM-Based miRNA:miRNA* Duplex Prediction”, IEEE 12th Internation-
al Conference on BioInformatics and BioEngineering (BIBE 2012)
C
[37] Giorgos Borboudakis, Sofia Triantafillou, Ioannis Tsamardinos, “Tools and Al-
gorithms for Causally Interpreting Directed Edges in Maximal Ancestral
Graphs”, The Sixth European Workshop on Probabilistic Graphical Models, (PGM)
2012
C
[38] Giorgos Borboudakis, Ioannis Tsamardinos, “Incorporating Causal Prior
Knowledge as Path-Constraints in Bayesian Networks and Maximal Ancestral
C
Graphs”, International Conference in Machine Learning (ICML), 2012
[39] Ioannis Tsamardinos, Giorgos Borboudakis, Eleni G. Christodoulou, Oluf D. Røe,
“Chemosensitivity Prediction of Tumours Based on Expression, miRNA, and Pro-
teomics Data”, International Journal of Systems Biology and Biomedical Technologies
(IJSBBT), Volume 1, Issue, 2012
J
[40] Vincenzo Lagani, Ioannis Tsamardinos, Sofia Triantafillou, “Learning from a
mixture of experimental data: a constrained–based approach”, 7th Hellenic Con-
ference on Artificial Intelligence (SETN), 2012
C
[41] Ioannis Tsamardinos, Sofia Triantafillou, Vincenzo Lagani, “Towards Integra-
tive Causal Analysis of Heterogeneous Datasets and Studies”, Journal of Machine
Learning Research 13(Apr):1097−1157, 2012
J
[42] Laura E. Brown, Ioannis Tsamardinos, Douglas P. Hardin, “To Feature Space
and Back: Identifying Top-Weighted Features in Polynomial Support Vector Ma-
chines Models”, Intelligent Data Analysis, 16(4), 2012
J
2011
[43] C. Filipaki, G. Antoniou, I. Tsamardinos, “Using Constraint Optimization for
Conflict Resolution and Detail Control in Activity Recognition”, International Joint
Conference on Ambient Intelligence (AMI 2011)
C
[44] L. Koumakis, F. Chiarugi, V. Lagani, I. Tsamardinos, "Risk assessment models
for diabetes complications: a survey of available on line tools", 2nd International
ICST Conference on Wireless Mobile Communication and Healthcare (MobiHealth
2011), Kos Island, Greece, 5-7 October 2011
C
[45] Vincenzo Lagani, Ioannis Tsamardinos, Magda Grammatikou, George Garinis, “A
Genome-Wide Study of the Effect of Aging on Level-2 Gene-Ontology Categories in
Mice Using Mixed Models”, ECML/PKDD 2011, Workshop on “Data Mining in Ge-
nomics and Proteomics”
C
[46] Eleni G. Christodoulou, Oluf Dimitri Røe, Amos Folarin, Ioannis Tsamardinos,
“Information-Preserving Techniques Improve Chemosensitivity Prediction of Tu-
mours Based on Expression Profiles”, 12th Engineering Applications of Neural Net-
works (EANN) / 7th Artificial Intelligence Applications and Innovations (AIAI) joint
conferences, Workshop on Computational Intelligence Applications in Bioinformatics
(CIAB 2011)
C
[47] Giorgos Borboudakis, Sofia Triantafillou,Vincenzo Lagani, Ioannis Tsamardinos,
“A constraint-based approach to incorporate prior knowledge in causal models”,
European Symposium on Artificial Neural Networks, Computational Intelligence and
Machine Learning (ESANN 2011)
C
[48] Angelos P. Armen and Ioannis Tsamardinos, “A Unified Framework for Estima-
tion and Control of the False Discovery Rate in Bayesian Network Skeleton Identi-
fication”, European Symposium on Artificial Neural Networks, Computational Intelli-
gence and Machine Learning (ESANN 2011)
C
2010
[49] Katerina Gkirtzou, Ioannis Tsamardinos, Panagiotis Tsakalides, Panayiota Poirazi,
“MatureBayes: A probabilistic algorithm for identifying the mature miRNA within
novel precursors”, PLoS ONE 5(8): e11843. doi:10.1371/journal.pone.0011843
J
[50] Ioannis Tsamardinos, Giorgos Borboudakis, “Permutation Testing Improves
Bayesian Network Learning”, European Conference on Machine Learning and Princi-
ples and Practice of Knowledge Discovery in Databases (ECML-PKDD 2010)
C
[51] Vincenzo Lagani, Ioannis Tsamardinos, “Structure-Based Variable Selection for
Survival Data”, Bioinformatics 2010 26(15):1887-1894;
doi:10.1093/bioinformatics/btq261
J
[52] Peter Hunter, Peter V. Coveney, Bernard de Bono, Vanessa Diaz, John Fenner,
Alejandro F. Frangi, Peter Harris, Rod Hose, Peter Kohl, Pat Lawford, Keith McCor-
mack, Miriam Mendes, Stig Omholt, Alfio Quarteroni, John Skår, Jesper Tegner, S.
Randall Thomas, Ioannis Tollis, Ioannis Tsamardinos, Johannes H. G. M. van Beek and
Marco Viceconti, “A vision and strategy for the virtual physiological human in 2010
and beyond”, Phil. Trans. R. Soc. A 2010 368, 2595-2614
J
[53] Franco Chiarugi, Dimitra Emmanouilidou, Ioannis Tsamardinos, “Morphological
classification of heartbeats to dominant and non-dominant in ECG signals”, Physio-
logical Measurement 31 (2010) 611-631
J
[54] Sofia Triantafillou, Ioannis Tsamardinos, Ioannis Tollis, “Learning Causal Struc-
ture from Overlapping Variable Sets”, in Y.W. Teh and M. Titterington (Eds.), Pro-
ceedings of The Thirteenth International Conference on Artificial Intelligence and Statis-
tics (AISTATS) 2010, JMLR: W&CP 9, pp 860-867, 2010, Chia Laguna, Sardinia, Italy,
May 13-15, 2010
C
[55] Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani,
Xenofon D. Koutsoukos, “Local Causal and Markov Blanket Induction for Causal
Discovery and Feature Selection for Classification. Part I: Algorithms and Empiri-
cal Evaluation”, Journal of Machine Learning Research, Special Topic on Causality
11:171−234, 2010
J
[56] Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, Subramani Mani,
Xenofon D. Koutsoukos, “Local Causal and Markov Blanket Induction for Causal
Discovery and Feature Selection for Classification. Part II: Analysis and Exten-
sions”, Journal of Machine Learning Research, Special Topic on Causality 11:235−284,
2010.
J
2009
[57] Ioannis Tsamardinos, Sofia Triantafillou, “The Possibility of Integrative Causal
Analysis: Learning from Different Datasets and Studies”, Journal of Engineering
Intelligent Systems 17(1), 2009
J
[58] Statnikov A, Tsamardinos I, Brown LE, Aliferis CF. “Causal Explorer: A Matlab
Library of Algorithms for Causal Discovery and Variable Selection for Classifica-
tion”. In Challenges in Causality. Volume 1: Causation and Prediction Challenge. Edited
by Guyon I, Aliferis CF, Cooper GF, Elisseeff A, Pellet JP, Spirtes P and Statnikov A.
BC
(In press) Brookline, Massachusetts: Microtome Publishing, 2009.
[59] Ioannis Tsamardinos and Asimakis P. Mariglis, “Multi-Source Causal Analysis:
Learning Bayesian Networks from Multiple Datasets”, 5th IFIP Conference on Arti-
ficial Intelligence Applications & Innovations (AIAI 2009), 2009
C
[60] Constantin Aliferis, Alexander Statnikov, Ioannis Tsamardinos., Jonathan Schild-
crout, Bryan Shepherd, Frank Harrell, “Factors Influencing the Statistical Power of
Complex Data Analysis Protocols for Molecular Signature Development from Mi-
croarray Data”, PLoS ONE, 2009; 4(3): e4922
J
[61] Chiarugi, F., Karatzanis, I., Sakkalis, V., Tsamardinos, I., Dermitzaki, T., Fou-
karakis, M., et al. (2009). “Predicting the occurrence of acute hypotensive episodes:
The PhysioNet challenge”. In Proceedings of Computers in Cardiology 2009 (CinC
2009), Park City, Utah
C
2008
[62] Laura E. Brown, Ioannis Tsamardinos, “A Strategy for Making Predictions Un-
der Manipulation”, Journal of Machine Learning Research (Workshop and Conference
Proceedings) 3:35-52, 2008
J
[63] Ioannis Tsamardinos, Laura E. Brown, “Bounding the False Discovery Rate in
Local Bayesian Network Learning”, in Twenty Third AAAI Conference on Artificial
Intelligence, 2008 (AAAI-2008)
C
[64] Chiarugi, F., Emmanouilidou, D., Tsamardinos, I., & Tollis, I. G. (2008). “Morpho-
logical classification of heartbeats using similarity features and a two-phase deci-
sion tree”. Computers in Cardiology 2008, CAR, Bologna. , 35 849-852.
C
2006
[65] Constantin F. Aliferis, Alexander Statnikov, Ioannis Tsamardinos, “Challenges in
the Analysis of Mass-Throughput Data: A Technical Commentary from the Per-
spective of Statistical Machine Learning”, Cancer Informatics. 2006; 2: 133–162
J
[66] Ioannis Tsamardinos, Alexander Statnikov, Laura E. Brown, Constantin F. Aliferis,
“Generating Realistic Large Bayesian Networks by Tiling”, the 19th International
FLAIRS conference (FLAIRS), 2006
C
[67] I. Tsamardinos, L.E. Brown, C.F. Aliferis. "The Max-Min Hill-Climbing Bayesian
Network Structure Learning Algorithm", Machine Learning Journal; 65: 31-78
J
2005
[68] Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis, “A Comparison of
Novel and State-of-the-Art Polynomial Bayesian Network Learning Algorithms”, in
the Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI),
pp. 739-745, 2005
C
[69] Alexander Statnikov, Ioannis Tsamardinos, Yerbolat Dosbayev, Constantin F. Alif-
eris, “GEMS: A System for Automated Cancer Diagnosis and Biomarker Discovery
from Microarray Gene Expression Data”, International Journal of Medical Informat-
J
ics, 74(7-8):491-503, 2005
[70] Yindalon Aphinyanaphongs, Ioannis Tsamardinos, Alexander Statnikov, Douglas
Hardin, Constantin F. Aliferis, “Text Categorization Models for High Quality Article
Retrieval in Internal Medicine”, Journal of American Medical Informatics Association
12(2):207-216, 2005
J
[71] Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, Douglas Hardin,
Shawn Levy, “A Comprehensive Evaluation of Multicategory Classification Meth-
ods for Microarray Gene Expression Cancer Diagnosis”, in Bioinformatics
21(5):631-643, 2005
C
2004
[72] Douglas Hardin, Ioannis Tsamardinos, Constantin F. Aliferis, “A Theoretical
Characterization of Linear SVM-Based Feature Selection”, in The Twenty-First In-
ternational Conference on Machine Learning (ICML 2004), 2004
C
[73] Martha E. Pollack, Ioannis Tsamardinos, “Efficiently Dispatching Plans Encoded
as Simple Temporal Problems”, in Intelligent Techniques for Planning, Idea Group
Publishing, Editors: Ioannis Vlahavas and Dimitris Vrakas, 2004
BC
[74] Laura E. Brown, Ioannis Tsamardinos, Constantin F. Aliferis, “A Novel Algorithm
for Scalable and Accurate Bayesian Network Learning”, in Proceedings of 11th
World Congress in Medical Informatics (MEDINFO ’04), 2004
C
[75] Alexander Statnikov, Constantin F. Aliferis, Ioannis Tsamardinos, “Methods for
Multi-Category Cancer Diagnosis from Gene Expression Data: A Comprehensive
Evaluation to Inform Decision Support System Development”, Proceedings of 11th
World Congress in Medical Informatics (MEDINFO ’04), 2004, Gold Medal in the Stu-
dent Paper Competition
C
2003
[76] Lewis Frey, Douglas Fisher, Ioannis Tsamardinos, Constantin F. Aliferis, Alexander
Statnikov, “Identifying Markov Blankets with Decision Tree Induction”, in The
Third IEEE International Conference on Data Mining (ICDM’03), pp. 59-66.
C
[77] C. F. Aliferis, I. Tsamardinos, A. Statnikov. “HITON, A Novel Markov Blanket
Algorithm for Optimal Variable Selection”, in the American Medical Informatics As-
sociation meeting 2003 (AMIA 2003)
C
[78] I. Tsamardinos, C.F. Aliferis, A. Statnikov. “Time and Sample Efficient Discov-
ery of Markov Blankets and Direct Causal Relations”, in The Ninth ACM SIGKDD
International Conference on Knowledge Discovery and Data Mining (KDD 2003), p.
673-678
C
[79] I. Tsamardinos, M. E. Pollack, S. Ramakrishnan, “Assessing the Probability of
Legal Execution of Plans with Temporal Uncertainty”, in ICAPS03 Workshop on
Planning under Uncertainty and Incomplete Information, 2003, p. 110-118.
C
[80] M. E. Pollack, L. Brown, D. Colbry, C. E. McCarthy, C. Orosz, B. Peintner, S. Ra-
makrishnan, and I. Tsamardinos, “Autominder: An Intelligent Cognitive Orthotic
J
System for People with Memory Impairment,” Robotics and Autonomous Systems,
44(3-4):273-282, 2003
[81] Ioannis Tsamardinos and Martha E. Pollack, “Efficient Solution Techniques for
Disjunctive Temporal Reasoning Problems,” in Artificial Intelligence, 151(1-2), pp
43-89, 2003
J
[82] Ioannis Tsamardinos, Thierry Vidal, Martha E. Pollack, “CTP: A New Constraint-
Based Formalism for Conditional, Temporal Planning”, in Special Issue on Planning
of Constraints Journal, 8:4 October 2003, p. 365-388
J
[83] Constantin F. Aliferis, Ioannis Tsamardinos, Alexander Statnikov, Laura E. Brown.
“Causal Explorer: A Causal Probabilistic Network Learning Toolkit for Biomedical
Discovery”, International Conference on Mathematics and Engineering Techniques in
Medicine and Biological Sciences (METMBS '03), p. 371-376
C
[84] C. F. Aliferis, I. Tsamardinos, P. Massion, A. Statnikov, D. Hardin. “Why Classifi-
cation Models Using Array Gene Expression Data Perform So Well: A Preliminary
Investigation Of Explanatory Factors”, International Conference on Mathematics and
Engineering Techniques in Medicine and Biological Sciences (METMBS '03), 47-53
C
[85] Ioannis Tsamardinos, Constantin F. Aliferis, Alexander Statnikov, “Algorithms for
Large Scale Markov Blanket Discovery”, The 16th International FLAIRS Conference,
St. Augustine, Florida, USA, May 2003, p. 376-381
C
[86] Constantin F. Aliferis, Ioannis Tsamardinos, Pierre Mansion, Alexander Statnikov,
Douglas Hardin, “Machine Learning Models For Classification Of Lung Cancer and
Selection of Genomic Markers Using Array Gene Expression Data”, The 16th Inter-
national FLAIRS Conference, St. Augustine, Florida, USA, May 2003, p. 67-71
C
[87] Ioannis Tsamardinos, Constantin F. Aliferis, “Towards Principled Feature Selec-
tion: Relevancy, Filters, and Wrappers”, Ninth International Workshop on Artificial
Intelligence and Statistics, Key West, Florida, USA, January, 2003 (AI&Stats 2003)
C
2002
[88] Ioannis Tsamardinos, “A Probabilistic Approach to Robust Execution of Tem-
poral Plans with Uncertainty”, Proceedings of the 2nd Greek National Conference on
Artificial Intelligence, Thessaloniki, Greece, April 2002, p. 97-108.
C
[89] Martha E. Pollack, Colleen E. McCarthy, Sailesh Ramakrishnan, Ioannis Tsamardi-
nos, “Execution Time Plan Management for a Cognitive Orthotic System”, eds. M.
Beetz and J. Hertzberg, Plan-Based Control of Robotic Agents, 2002
BC
[90] M. E. Pollack, C. E .McCarthy, S. Ramakrishnan, I. Tsamardinos, L. Brown, S. Car-
rion, D. Colbry, C. Orosz, and B. Peintner, “Autominder: A Planning, Monitoring,
and Reminding Assistive Agent,” Proceedings of the 7th International Conference on
Intelligent Autonomous Systems (IAS), March, 2002
C
[91] Alan Berfield, Panos K. Chrysanthis, Ioannis Tsamardinos, Martha E. Pollack,
Sujata Banerjee “A Scheme for Integrating e-Services in Establishing Virtual Enter-
C
prises”, 12th International Workshop on Research Issues on Data Engineering (RIDE-
02)
2001
[92] I. Tsamardinos, M. Pollack, P. Ganchev, “Flexible Dispatch of Disjunctive Tem-
poral Plans”, in Proceedings of Sixth European Conference on Planning 2001 (ECP-
01), Toledo, Spain, pp. 417—422
C
Prior to 2001
[93] I. Tsamardinos, M. E. Pollack, J. F. Horty, “Merging Plans with Quantitative
Temporal Constraints, Temporally Extended Actions, and Conditional Branches”,
Proceedings of the 5th International Conference on AI Planning and Scheduling (AIPS
2000), Breckenridge, CO, April, 2000, pp264-272. Winner of the Outstanding Student
Paper Award
C
[94] M. E. Pollack, I. Tsamardinos and J. F. Horty, "Adjustable Autonomy for a Plan
Management Agent" 1999 AAAI Spring Symposium on Adjustable Autonomy, Stanford,
CA, March, 1999
C
[95] I. Tsamardinos, N. Muscettola, and P. Morris, “Fast Transformation of Temporal
Plans for Efficient Execution”, in Proceedings of the 15th National Conference on Arti-
ficial Intelligence (AAAI’98), pp254-261
C
[96] N. Muscettola, P. Morris, and I. Tsamardinos, “Reformulation of Temporal Plans
for Efficient Execution”, in Proceedings of the 6th Conference Principles of Knowledge
Representation and Reasoning (KR) 1998, pp444-452
C
[97] C. Bicchieri, M. Pollack, C. Rovelli, and I. Tsamardinos, “The Potential for the
Evolution of Cooperation among Web Agents”, in International Journal of Computer-
Human Systems, 48(1): 9-29, 1998
J
[98] S. Orphanoudakis, M. Tsiknakis, C. Chronaki, S. Kostomanolakis, M. Zikos, and Y.
Tsamardinos. “Development of an Integrated Image Management and Communica-
tion System on Crete”, Proceedings of Computed Aided Radiology '95. Berlin, June 21-
24, pp481-487, Springer 1995
C
Other Publications
Ioannis Tsamardinos, The path to understanding causal relations, EU Research,
www.euresearcher.com, 2017
Ana I. Robles, Karina Standahl Olsen, Dana W.T. Tsui, Vassilis Georgoulias, Jenette
Creaney, Katalin Dobra, Mogens Vyberg, Nagahiro Minato, Robert A. Anders,
Anne‑Lise Børresen‑Dale, Jianwei Zhou, Pål Sætrom, Boye Schnack Nielsen, Michaela
B. Kirschner, Hans E. Krokan, Vassiliki Papadimitrakopoulou, Ioannis Tsamardinos and
Oluf D. Røe, “Excerpts from the 1st international NTNU symposium on current and
future clinical biomarkers of cancer: innovation and implementation, June 16th
and 17th 2016, Trondheim”, J Transl Med (2016) 14:295 DOI 10.1186/s12967-016-
1059-6
Angelos P. Armen and Ioannis Tsamardinos, “Estimation and Control of the False
Discovery Rate of Bayesian Network Skeleton Identication”, Technical Report
FORTH-ICS TR-441, January 2013
Peter Hunter, Tara Chapman, Peter V. Coveney, Bernard de Bono, Vanessa Diaz, John
Fenner, Alejandro F. Frangi, Peter Harris, Rod Hose, Peter Kohl, Pat Lawford, Keith
McCormack, Miriam Mendes, Stig Omholt, Alfio Quarteroni, Nour Shublaq, John Skår,
Karl Stroetmann, Jesper Tegner, S. Randall Thomas, Ioannis Tollis, Ioannis Tsamardi-
nos, Johannes HGM van Beek and Marco Viceconti, “A VISION AND STRATEGY
FOR THE VIRTUAL PHYSIOLOGICAL HUMAN”, Virtual Physiological Human
Network of Excellence NewsLetter #8, Sep. 2012
Ioannis Tsamardinos, “Βιοπληροφορική: μια νέα ώθηση στη βιολογική έρευνα”,
Economist Oct. 2010 (Greek edition)
Ioannis Tsamardinos, “Causal Data Mining in Bioinformatics”, ERCIM News 69, Spe-
cial Theme: The Digital Patient
Franco Chiarugi, Dimitra Emmanouilidou, Ioannis Tsamardinos, Ioannis G. Tollis,
“Morphological Classification of Heartbeats Using Similarity Features and a Two-
Phase Decision Tree”, Computers in Cardiology 2008
I. Tsamardinos, “Temporal Constraints and Uncertainty”, Workshop on Constraints
and Uncertainty as part of the Seventh International Conference on Principles and Prac-
tice of Constraint Programming (CP2001), Paphos, Cyprus
Tutorials
[1] Sofia Triantafillou and Ioannis Tsamardinos, “Integrative Logic-Based Causal Discov-
ery”, Uncertainty in Artificial Intelligence (UAI) 2016,
http://www.auai.org/uai2016/tutorials.php
[2] Ioannis Tsamardinos, Sofia Triantafyllou, Vincenzo Lagani, “Introduction to causal
discovery: A Bayesian Networks approach”, High-Throughput Omics & Data Integration
Workshop 2013 (COST Workshops)
[3] Ioannis Tsamardinos, Sofia Triantafyllou, “Introduction to Causal Discovery: A
Bayesian Network Approach”, European Conference on Machine Learning and Principles
and Practice of Knowledge Discovery in Databases (ECML PKDD), 2011
[4] Ioannis Tsamardinos, Sofia Triantafyllou, “Introduction to Causal Discovery: A
Bayesian Network Approach”, The Fourteenth IASTED International Conference on Arti-
ficial Intelligence and Soft Computing (ASC 2011)
[5] Ioannis Tsamardinos, Sofia Triantafyllou, “Introduction to Causal Discovery: A
Bayesian Network Approach”, 6th Hellenic Conference on Artificial Intelligence (SETN
2010) May 2010
[6] Ioannis Tsamardinos, Sofia Triantafyllou, “Introduction to Causal Discovery: A
Bayesian Network Approach”, Hellenic Artificial Intelligence Summer School 2009, Inter-
national Hellenic University
[7] Nicola Muscettola, Ioannis Tsamardinos, Luke Hunsberger, “Temporal Reasoning for
Planning, Scheduling and Execution in Autonomous Agents”, in the Fourth International
Joint Conference Autonomous Agents and Multiagent Systems (AAMAS), 2005
[8] C. F. Aliferis, I. Tsamardinos, “Machine Learning Methods for Data Modeling, Deci-
sion Support, and Discovery”, in 11th World Congress in Medical Informatics (MEDINFO
’04)
[9] C. F. Aliferis, I. Tsamardinos, “Machine Learning Methods for Data Modeling, Deci-
sion Support, and Discovery”, in American Medical Informatics Association meeting 2003
(AMIA 2003)
System Demos
[1] Statnikov A, Tsamardinos I, Aliferis CF. “Using the GEMS System for Supervised
Analysis of Cancer Microarray Gene Expression Data”. AMIA Annual Symposium,
2005
[2] Alexander Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis, “Using GEMS for
Cancer Diagnosis and Biomarker Discovery from Mircoarray Gene Expression Data”,
to the Proceedings of the Twentieth National Conference on Artificial Intelligence (AAAI),
2005
[3] Alexander Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis, “Using GEMS for
Cancer Diagnosis and Biomarker Discovery from Mircoarray Gene Expression Data”,
ISMB 2005
Posters and Abstracts
Shyam Khadka, Yannis Pantazis and Ioannis Tsamardinos, “Data Integration of Single-
Cell Mass Cytometry Measurements using Advanced Imputation Methods”, HBIO
2017
Christos Tselas, Yannis Pantazis, Kleanthi Lakiotaki and Ioannis Tsamardinos, “Large-
scale Study on Latent Feature Construction for Gene Expression with improved Pre-
dictive Power on Newly-seen Datasets”, HBIO 2017
Kleanthi Lakiotaki, Paul Charonyktakis and Ioannis Tsamardinos, “Automated machine
learning methods to predict phenotype in microarray and RNASeq gene expression
data”, HBIO 2017
Maria Markaki, Michael Tsagris, Mira Limaci, Georgios Papoutsoglou and Ioannis Tsamar-
dinos, “Clinical relevance of single-cell immune signatures in cellular subpopulations”,
HBIO 2017
Maria Nikoloudaki, Vincenzo Lagani and Ioannis Tsamardinos, “Reconstructing Ikaros
regulatory network by applying causal discovery methods on a compendium of gene
expression profiles from Acute Lymphoblastic Leukemia patients”, HBIO 2017
Giorgos Borboudakis, Ioannis Tsamardinos, “Incorporating Causal Prior Knowledge in
Causal Models”, 7th Conference of the Hellenic Society for Computational Biology & Bio-
informatics - HSCBB12
Konstantinos Kerkentzes and Ioannis Tsamardinos, “A feature selection algorithm for
identifying high-order interactions in high-dimensional biological data”, 7th Conference
of the Hellenic Society for Computational Biology & Bioinformatics - HSCBB12
Vincenzo Lagani, George Kortas, Ioannis Tsamardinos, “Biomarker signature identifica-
tion in “omics” data with multi-class outcome”, 7th Conference of the Hellenic Society for
Computational Biology & Bioinformatics - HSCBB12
Ioannis Tsamardinos, Vincenzo Lagani, Dimitris Pappas, “Discovering multiple, equiva-
lent biomarker signatures”, 7th Conference of the Hellenic Society for Computational Bi-
ology & Bioinformatics - HSCBB12
Sofia Triantafillou, Ioannis Tsamardinos, “Predicting associations from multiple “omics”
data sets using causal discovery”, 7th Conference of the Hellenic Society for Computation-
al Biology & Bioinformatics - HSCBB12 (Winner of Best Poster Award)
Sophia Kleisarchaki, Dimitris Kotzinos, Ioannis Tsamardinos, Vassilis Christophides, “To-
wards a Realistic Social Text Stream Workbench”, Intersocial Workshop on Online So-
cial Networks (IWOSN) 2012
Chatzi, K., Orfanoudaki, G., Koukaki, M., Gouridis, G, Tsamardinos I, Karamanou S. and
Economou A., “Optimal matching between signal peptides and mature domains deter-
mines protein secretion efficiency”, 1st International Proteomics Conference on Crete
(IPCC01), Heraklion 07-09 October 2010
Orfanoudaki, G., Chatzi, K., Tsamardinos, I and Economou A., “Proteome-wide search for
secretion signals in Escherichia coli”, 1st International Proteomics Conference on Crete
(IPCC01), Heraklion 07-09 October 2010
Ioannis Tsamardinos, “Integrative Causal Analysis – The Theory of Statistical Model
Integration and Data Co-Analysis”, First VPH Conference (VPH 2010)
Aliferis CF, Statnikov A, Tsamardinos I, Kokkotou E, Massion PP. “Application and
Comparative Evaluation of Causal and Non-Causal Feature Selection Algorithms for
Biomarker Discovery in High-Throughput Biomedical Datasets”, Neural Information
Processing Systems (NIPS) 2006 Workshop on Causality and Feature Selection, 2006
Alexander Statnikov, Ioannis Tsamardinos, Constantin F. Aliferis, “Using GEMS for Can-
cer Diagnosis and Biomarker Discovery from Mircoarray Gene Expression Data”,
ISMB 2005, (Winner of Best Poster Award)
Public Software and Tools
(software packages are available at http://mensxmachina.org/en/software/ )
Name Description
SCENERY SCENERY is a web-based application built on R and PHP for (caus-
al) network reconstruction, standard statistical analysis, and visualiza-
tion of flow cytometry and mass cytometry data.
MXM R Pack-
age
MXM is an R package that implements feature selection methods for
identifying minimal, statistically-equivalent and equally-predictive
feature subsets, as well as several causal discovery and network re-
construction algorithms.
GEMS GEMS stands for Gene Expression Model Selector and is a system
for automated cancer diagnosis and biomarker discovery from micro-
array gene expression data developed at Vanderbilt University by
Prof. Ioannis Tsamardinos and his colleagues.
Recognition, Awards, and Distinctions
Honors, Awards, and Distinctions
Dates Award Details
Jun.
2017
2006 paper receives
Google Scholar Arti-
ficial Intelligence
“classic” status
The paper “The max-min hill-climbing Bayesian network
structure learning algorithm”, 2006 receives the status of
“classic paper of 2006” by Google Scholar, for the catego-
ry of Artificial Intelligence.
https://scholar.google.com/ citations?
view_op=list_classic_articles&hl=en&by=2006&vq=
eng_artificialintelligence
Nov.
2014
Boeringer Ingelheim
Cancer Research
Award (Best Ab-
stract / Poster of the
Year) 2014, Norwe-
gian Lung Cancer
Group
For the poster Robin Mjelle, Trygve Andreassen, Vincen-
zo Lagani, Konstantinos Kerkentzes, Ioannis Tsamardi-
nos, Tone Bathen, Erik Larsson, Oluf Dimitri Røe,
“HUNTing” early diagnostic biomarkers for lung cancer /
mesothelioma : a pilot analysis from the Cancer-
Biomarker-HUNT study”, http://www.nlcg.no/node/122
Nov.
2013
ARISTEIA II Grant
Recipient
Greek National Excellence Grant for the proposal
“Causal-Based Variable Selection for Omics Data”
Nov.
2013
ERC Consolidator
Grant Recipient
European Excellence Grant for the proposal “Next Gen-
eration Causal Analysis: Inspired by the Induction of Bio-
logical Pathways from Cytometry Data”
Oct.
2012
HSCBB 2012 Best
Poster Award
Triantafilou, Tsamardinos “Predicting associations from
multiple “omics” data sets”, HSCBB 2012
Dec.
2011
Board of Directors,
ChaLearn
ChaLearn (Challenges in Machine Learning) is a non-
profit corporation organizing research challenges in the
field http://www.chalearn.org/index.html
Jun.
2011
Most Cited Papers of
2010 of the Phil.
Rans. R. Soc. A
Journal
For the paper Peter Hunter, et. al., Phil. Trans. R. Soc. A
2010 368, 2595-2614
Jun.
2011
Editorial Board
Member
Frontiers in Bioinformatics and Computational Biology
Jun.
2008
Best Performance in
one out of the four
tasks of the competi-
tion First Causality
Challenge Competi-
tion
Team members: Laura E. Brown (unofficial submission
due to perceived conflict of interest),
http://www.causality.inf.ethz.ch/home.php
2005 Science Direct Top
25 Hottest Articles of
For the paper Alexander Statnikov, et. al., International
Journal of Medical Informatics, 74(7-8):491-503, 2005
the International
Journal of Medical
Informatics
Sep.
2005
ISMB 2005 Best
Poster Winner
A. Statnikov, I. Tsamardinos, C. F. Aliferis, Intelligent
Systems for Molecular Biology 2005. https://www.iscb.org/ismb2005/posters.html
2003-
2007
Editorial Board
Member
Journal of Artificial Intelligence Research
Sep.
2004
Gold Medal,
Student Paper Compe-
tition as student’s co-
advisor
A. Statnikov, C. F. Aliferis, I. Tsamardinos, Proceedings
of 11th World Congress in Medical Informatics (ME-
DINFO ’04), 2004
Sep.
2000
Andrew Mellon Fel-
low 2000-2001
University of Pittsburgh
Apr.
2000
Outstanding Student
Paper Award
I. Tsamardinos, M. E. Pollack, J. F. Horty, Proceedings of
the 5th International Conference on AI Planning and
Scheduling (AIPS 2000), April, 2000
Sep.
1999
Andrew Mellon Fel-
low 1999-2000
University of Pittsburgh
Jul.
1999
NASA Group
Achievement Award
NASA Ames, as a member of the Remote Agent group
Jul.
1995
Graduated 2nd in
class
CSD-UOC
Jul.
1994
Undergraduate Schol-
ar Fellowship for Best
Students
Ranked 5th for year 1993-1994,
CSD-UOC
Jul.
1993
Undergraduate Schol-
ar Fellowship for Best
Students
Ranked 2th for year 1993-1994,
CSD-UOC
Jul.
1992
Undergraduate Schol-
ar Fellowship for Best
Students
Ranked 2th for year 1992-1993,
CSD-UOC
Invited and Keynote Talks
(only accepted invitations are included; numerous invitations have been declined due to family and
other professional constraints)
(only invitations to a restricted audience are included; massive invitations are not included)
Dates Forum Title
Nov. 2017 Conference of the Pathology and Oncology
Clinic of the General University Hospital at
Heraklion (PAGNI)
Automated Data Analysis for the Con-
struction of Predictive and Diagnostic
Cancer Models
Oct. 2017 Invited presentation, Hellenic Society for
Computational Biology and Bioinformatics
(HSCBB) congress 2017
TBA
Aug. 2017 Keynote presentation, KDD 2017, Causal
Discovery Workshop
Advances in Causal-Based Feature Se-
lection
Jun. 2017 Invited talk, 2nd Congress “Evolution and
Cancer: Cancer across life”
From Human to Artificial Intelligence,
to Artificial Intelligence for Cancer Re-
search
Apr. 2017 Invited talk, Data Learning and Inference
(DALI 2018)
Causal Inference from Single Cell, Mass
Cytometry Data: an Integrative Ap-
proach
Nov. 2016 Συνέδριο Μεταφραστικής και Κλινικής
Ογκολογίας (Translational and Clinical
Oncology Conference), Εταιρεία Στήριξης
Αντικαρκινικής Έρευνας (Society for the
Support of Cancer Research)
Automated Identification of Biomarkers
and Biosignatures in Oncological Data
(Αυτόματη εύρεση βιοδεικτών και βιοϋ-
παγραφών σε ογκολογικά δεδομένα)
Nov. 2016 Department of Informatics and Telecom-
munications, National and Kapodistrian
University of Athens
Logic-Based Causal Discovery for Het-
erogeneous Datasets
Nov. 2016 Dept of Digital Systems, ICT School,
University of Piraeus
Advances in Feature Selection in Data
Analytics
Aug. 2016 Distinguished Lecturer in Causal Modeling
and Discovery at our NIH BD2K Center
for Causal Discovery (CCD) colloquium
series
Logic-based Causal Discovery
https://www.youtube.com/watch?v=ydg
mwJLB87o
Aug. 2016 Laboratory for Analytic Sciences, North
Carolina, State University
Logic-Based Causal Discovery for Het-
erogeneous Datasets,
https://coe.online.ncsu.edu/online/Play/4
a1cfc31c2844be4a0b237fb819d77a21d
June 2016 1st International Symposium on
Current and Future Clinical Biomarkers of
Cancer: Innovation and Implementation,
Norwegian University of Science and
Technology
Automated Computational Discovery of
Biomarkers and Biosignatures from Da-
ta Using Machine Learning,
https://biomarkerstrondheim.wordpress.
com/
June 2016 Data Driven World, Alumni of Computer
Science Department, UoC
Just Add Data: Automating Data Ana-
lytics and Causal Discovery
(http://uocpga.gr/wp-
content/uploads/2016/05/ddw-
timetable_final.jpg )
May 2016 9th Hellenic Conference on Artificial Intel-
ligence (SETN 2016), Nectar Talk
Constraint-based Causal Discovery
from Multiple Interventions over Over-
lapping Variable Sets
http://setn2016.csd.auth.gr/
Apr. 2016 DIGIFEST, 6th Student Festival of Digital
Creativity
Analyzing an Ocean of Data,
http://www.digifest.info/
Feb. 2016 Workshop “Infrastructures for Life Sci-
ence’s Big Data - and the role of ELIXIR”
Tools and Algorithms for Predictive
Biomarker Signatures and Causal Dis-
covery
Feb. 2016 Laboratory of Information, Networking
and Communication Sciences (LINCS)
Logic-Based Integrative Causal Discov-
ery with Business Applications,
https://www.lincs.fr/
Feb. 2016 Laborotoire De Recherche en Informa-
tique, Paris, Saclay
Logic-Based Integrative Causal Discov-
ery with Business Applications,
https://www.lri.fr/info.pratiques.php
Oct. 2015 Greek National Clinical Chemistry Confer-
ence
Bioinformatics Advances for Automat-
ing Predictive Biomarker and Biosigna-
tures from Data (www.eekx-
kb.gr/pdf/A_AN_13PSKX.pdf )
Jun. 2015 ETH Zurich, Seminar für Statistik Integrative Causal Analysis
May 2015 Bioinformatics Approaches for the Discov-
ery of Molecular Biosignatures
Workshop for the MARIAGE (Initial
Training Network,
http://www.ageingnetwork.eu/
Jan 2015 National Documentation Center, RECODE
conference on Open Access Data
Open BioMedical Data for Integrative
Analysis
(http://openaccess.gr/conferences/confer
ence2015/ )
Dec. 2014 Session: Bayesian Networks in Official
Statistics, ERCIM WG on Computational
and Methodological Statistics, University
of Pisa, Italy
Advances in integrative causal analysis
and connections to statistical matching
Oct. 2014 Max Planck Institute for Intelligent Sys-
tems
Advances in Integrative Causal Analysis
and Applications to Mass Cytometry
Data
May 2014 Intelligent Systems Laboratory, University
of Amsterdam
Advances in Integrative Causal Analysis
and Applications to Mass Cytometry
Data
Apr. 2014 Workshop Bioinformatics in Oncology,
Thessaloniki
Discovering
Molecular and Clinical Signatures
of Cancer
Oct 2013 Workshop: Case Studies of Causal Discov-
ery with Model Search, Carnegie Mellon
University, Pittsburgh, PA, USA
Causal Discovery from Mass Cytometry
Data
May 2013 University of Helsinki Causally Inspired Approaches
to Variable Selection, Molecular Signa-
ture Identification, and Integrative
Analysis of Heterogeneous Datasets
June 2011 Norwegian University of Science and
Technology, Trondheim, Norway
Advances in Causal-Based Analysis
Methods for Biomedical Data
May 2011 Department of Philosophy at
Carnegie Mellon University,
University of Pittsburgh,
University of Michigan,
University of Massachusetts at Amherst
New York University
Towards Integrative Causal Analysis of
Heterogeneous Datasets and Prior
Knowledge
Sep. 2007 Consiglio Nazionale delle Ricerche, Pisa,
Italy
Advances in Machine Learning Feature
Selection and Causal Discovery
Jun. 2004 University of Macedonia, Greece Advances in Bayesian Network Learn-
ing, Causal Discovery, and Variable
Selection in Massive Datasets with Ap-
plications in Biomedicine
Jun. 2004 Institute of Computer Science, Foundation
for Research and Technology, Hellas
Advances in Bayesian Network Learn-
ing, Causal Discovery, and Variable
Selection in Massive Datasets with Ap-
plications in Biomedicine
Sep. 2003 As part of the Center for Computational
Biology Seminar Series Center for Compu-
tational Biology, University of Colorado
Advances in Bayesian Network Learn-
ing, Causal Discovery, and Variable
Selection in Massive Datasets with Ap-
plications in Biomedicine
Jun. 2003 Plan Execution Workshop, International
Conference in Automated Planning and
Scheduling (ICAPS), 2003
Panel Member, discussion on Planning
and Execution issues
Sep. 2000 Instituto di Psicologia, Consiglio Na-
zionale delle Ricerche (IP-CNR), Rome
Reformulating Temporal Plans for Effi-
cient Execution
Sep. 2000 Instituto di Psicologia, Consiglio Na-
zionale delle Ricerche (IP-CNR), Rome
Algorithms and Applications of New
Constrained-based Temporal Reasoning
Frameworks
Feb. 2000 Symposium on Intelligent Agents in Soft-
ware Engineering for Planning, Ghent,
Belgium
On Plan Management Issues
Research Funding
Participation in Funded Research Programs
STREP : Specific Targeted Research Projects RO1: Research Project Grant Program
IP: Integrated Project P20: Exploratory Grants
Title Source / Budget
Role Dates
Smart End-to-end Mas-
sive IoT Interoperability,
Connectivity and Securi-
ty
HORIZON 2020, IoT-
03-2017, € 4.995.000
Co-author / Co-
investigator
01/01/2018-
31/12/2021
ELIXIR-GR: The
Greek Research Infra-
structure for the Man-
agement and Analysis of
Data in Biosciences
“H Ελληνική
Ερευνητική Υποδομή
για Διαχείριση και
Ανάλυση Δεδομένων
στις Βιοεπιστήμες”
€3.991.100, GSRT
(budget managed by
UOC on my projects
around ~€110.000)
Co-author, co-
investigator, UOC scien-
tific responsible for the
specific sub-project
1/1/17 -
31/12/19
Feasibility study to-
wards the Next Genera-
tion Statistical Text to
Speech Synthesis Sys-
tem
TOSHIBA RESEARCH
EUROPE LIMITED,
€49163,02
Principal Investigator 5/7/2015 -
14/7/2016
The Early Detection of
Lung Cancer
Bonnie J. Addario Lung
Cancer Foundation and
International Association
for the Study of Lung
Cancer (IASLC),
~$300000 additional
contribution to “Cancer
in Biomarkers HUNT”
project
Co-author, co-
investigator, UOC scien-
tific responsible
6/2016 –
5/2018
Cancer Biomarkers in
HUNT
5,7 million NOK (Nor-
wegian Krone), Central
Norway Regional Health
Authority (Helse Midt-
Norge RHF)
Co-author, co-
investigator, UOC scien-
tific responsible
1/2/2015 –
1/6/2018
No 617393, CAUSAL-
PATH: Next Generation
Causal Analysis: In-
spired by the Induction
of Biological Pathways
from Cytometry Data
€1.724.000
EU FP7, ERC Consoli-
dator Grant
Principal Investigator 1/1/2015 –
31-12-2020
No 3446, EPILOGEAS :
Causal Based Variable
Selection for Omics Da-
ta
€236.000
GSRT
Principal Investigator 1/1/2014 –
6/1/2015
ΒΙΟΣΥΣ' ΑΝΑΠΤΥ-
ΞΗ ΔΙΕΠΙΣΤΗΜΟΝΙ-
ΚΩΝ ΕΡΕΥΝΗΤΙΚΩΝ
ΔΡΑΣΤΗΡΙΟΤΗΤΩΝ
ΣΤΗΝ ΚΑΤΕΥΘΥΝΣΗ
ΤΗΣ ΒΙΟΛΟΓΙΑΣ ΣΥ-
ΣΤΗΜΑΤΩΝ
€2.517.000
GSRT
Co-author, Co-
investigator, WP leader
1/7/2013 –
30/9/2015
No 316223 InnovCrete:
Unlocking the innova-
tive capacity of multi-
disciplinary structural
biology-driven research
in Crete
€4.003.534
EU FP7
Co-author, Co-
investigator
1/11/2012 –
31/10/2015
No 11ΣΥΝ_10_415,
eMoDiA: electronic
Molecular Diagnostics
Assistant
€776.430
GSRT
Co-author, Co-
investigator
1/1/2013 –
30/6/2015
No 318552 IdeaGar-
den, An Interactive
Learning Environment
Fostering Creativity
€2.398.571
EU FP7
Co-author, Co-
investigator
1/10/2012 –
30/9/2015
No 306000, STREP,
STATegra, User-driven
Development of Statisti-
cal Methods for Experi-
mental Planning, Data
Gathering, and Integra-
tive Analysis of Next
Generation Sequencing,
Proteomics, and
Metabolomics Data
€6.000.000
EU FP7
Co-author, Co-
investigator, WP Leader,
FORTH’s scientific re-
sponsible, responsible for
coordinating the WP re-
garding the development
of integrative analysis al-
gorithms for omics data
1/10/2012 –
30/9/2015
No 288533, IP, RO-
BOHOW.COG, Web-
enabled and Experience-
based Cognitive Robots
that Learn Complex
Everyday Manipulation
€9.454.834,
EU FP7
Member, responsible for
dimensionality reduction
algorithms applied to vi-
sion
01/02/2012
–
31/01/2016
Tasks
ARISTEIA 2010,
CoRLAB, Developing
the Foundations for
Modeling & Analysis of
Spectrum Markets
€386.000,
GSRT
Co-author, Co-
investigator, responsible
for applying integrative
causal analysis algorithms
to network data
1/7/2012 –
30/6/2015
ΘΑΛΗΣ 20332,
Συμβιωτικά βακτήρια
και Ομικές τεχνολογίες
στην προοπτική νέων,
φιλικών προς το περι-
βάλλον, μεθόδων ελέγ-
χου επιβλαβών εντόμων:
το παράδειγμα της Με-
σογειακής μύγας
(ΣΥΜΒΙΟΜΙΚΗ))
€600,000
Υπουργείο Παιδείας, Δια
Βίου Μάθησης και Θρη-
σκευμάτων (Ministry of
Education, Lifelong
Learning and Religion)
Co-author,
Co-investigator,
analysis of proteomics data
and construction of classi-
fication models
1/7/2012 –
30/6/2015
No 248590, IP
REACTION , Remote
Accessibility to Diabetes
Management and Thera-
py in Operational
Healthcare Networks
€14.412.539
EU FP7
Co-author, Co-
investigator, Responsible
for the construction of de-
cision support systems for
risk assessment of diabetes
complications
01/03/2010-
28/02/2014
No 2934, medium-size
university grants,
Inducing Causal Models
from Studies over Dif-
ferent Variable Sets
€1400
ELKE University of
Crete
Author, Principal Inves-
tigator, involved in all
aspects of the project
1/7/2010 -
21/03/2011
EC GA no 223920, NoE
VPH NoE, The Virtual
Physiological Human
Network of Excellence
€806.877
EU FP7
Member, Responsible for
coordinating the writing of
the first draft “Roadmap to
VPH”
01/06/2008-
30/11/2012
No 027107, STREP
HEARTFAID, A
Knowledge based plat-
form of services for
supporting medical -
clinical management of
heart failure within el-
derly population
€3.220.115
EU FP6
Member, Responsible for
constructing predictive
models of occurrence of
heart failure events
01/02/2006-
31/01/2009
LM-7948-01, RO1
Principled Methods for
Very Large-Scale Caus-
al Support Discovery
$631.180
National Library of Med-
icine, USA
Co-author, Co-
investigator. Involved in
all aspects of the proposal.
01/07/2003
–
030/06/2006
LM007613-0, P20
Biomedical Information
$226.500
National Library of Med-
Member, Involved in bio-
logical data analysis
01/09/2002
–
Science and Technology
Initiative (BISTI), Pilot
Project Computational
Models of Lung Cancer:
Connecting Classifica-
tion, Gene Selection,
and Molecular Sub-
typing
icine, USA 30/08/2004
Innovation and Commercialization
Consulting Services
Jan. 2004, Prediction Sciences, http://www.predict.net/
Patents
Patent Number: 7117185, Methods, system, and apparatus for causal discovery and variable se-
lection for classification, Issue Date: 10/3/2006, Mail Code: CCE84101
Patent Number: 7912698, Method and system for automated supervised data analysis , Issue
Date: March 22, 2011
Gnosis Data Analysis IKE
Prof. Tsamardinos is a co-founder of Gnosis Data Analysis IKE (www.gnosisda.gr ) ,
a University of Crete start-up company founded in October 2013. Gnosis does research in data
analytics methods and tools, provides data analysis services, educational tutorials on advanced
data analytics techniques to the industry, and data analytics products and tools. Some of Gnosis’
past and current contracts include:
Gnosis has contracted with the Rockwell and companies to provide a multi-session
tutorial over several weeks on advanced causal analytics to their data analysis staff.
Gnosis has been contracted by the Norwegian University of Science and Technology (NTNU) for
the bioinformatics analysis of the Cancer-Biomarkers in HUNT project
(http://www.mensxmachina.org/cancer_biomarker_hunt/) . The Cancer-Biomarkers in HUNT is
an international project comprising of five universities in five countries that collaborate to im-
prove the survival of lung cancer and mesothelioma through innovative early biomarker discov-
ery.
Gnosis has been contracted with the Rockwell and companies to provide causal dis-
covery and causal analytics on their data.
Gnosis has been collaborating with (https://impactwrap.com/ ) to provide predictive
models on their data.
Gnosis has been contracted the University of Huddersfield to provide an analysis of clinical data
for the prediction of suicide.
Gnosis is working on the Just Add Data Bio or JAD Bio product to be released in early 2018.
JAD Bio implements a fully automated predictive and diagnostic supervised machine learning
analytics pipeline on the cloud. JAD Bio is optimized for typical biological omics data, but also
works on other types of data. Using a beta version of JAD Bio several publications in the scien-
tific literature have been released with results obtained by the tool already:
Orfanoudaki, M. Markaki, K. Chatzi, I. Tsamardinos, and A. Economou, "MatureP: prediction of
secreted proteins with exclusive information from their mature regions", Scientific Reports 7,
2017
O. Simantiraki, P. Charonyktakis, A. Pampouchidou, M. Tsiknakis, and M. Cooke, "Glottal
Source Features for Automatic Speech-based Depression Assessment", INTERSPEECH, 2017
(to appear)
G. Borboudakis, T. Stergiannakos, M. G. Frysali, E. Klontzas, I. Tsamardinos, and G. E. Frou-
dakis, "Chemically-intuited, large-scale screening of mofs by machine learning techniques", Na-
ture Computational Materials, 2017 (In Press)
Gnosis is currently employing two full time employees and several freelance data analysts and
other professionals.
Last Updated September 2017