Download CURRICULUM VITAE 1. Personal details - liacs

CURRICULUM VITAE
1. Personal details
Surname
First names
Nijssen
Siegfried Gerardus Remius
Sex
Nationality
Place and date of birth
Male
Belgian and Dutch
The Hague, April 29, 1978
Address Leiden
Room 110
LIACS, Leiden University
Niels Bohrweg 1, 2333 CA, Leiden, The
Netherlands
Phone: (31) 715278919
Address Leuven
Room 04.34
Department of Computer Science, KU Leuven
Celestijnenlaan 200A, B-3001, Heverlee,
Belgium
Phone: (32) 16327567
Fax: (32) 16327996
E-mail
[email protected]
[email protected]
[email protected]
Institution where current position is held
Function
Universiteit Leiden
Assistant professor (tenure track)
2
2. Academic degrees
Master’s degree
Title of degree at master level:
Grade obtained (ex. “distinction”)
University
Country
Year
Doctorandus / Master of science
Cum laude
Universiteit Leiden
The Netherlands
2000
PhD degree
Area
Title of the dissertation
Supervisor
Grade obtained (ex. “distinction”)
University
Date
Computer science
Mining structured data
Prof.Dr. Joost N. Kok
Not applicable.
Universiteit Leiden
May 15, 2006
3
3. Full career
Function or duty
Institution or employer
Country
Start date
End date
Student assistant
Universiteit Leiden
September 1998
December 2000
PhD student (100%)
Universiteit Leiden
January 2001
August 2005
Postdoctoral researcher
on EU project (100%)
Postdoctoral researcher
on EU project (100%)
FWO Postdoctoral
researcher (100%)
FWO Postdoctoral
researcher (50%)
Assistant professor
(tenure track, 50%)
Postdoctoral researcher
on EU project (50%)
Assistant professor
(tenure track, 80%)
Postdoctoral researcher
on EU project (15%)
Assistant professor
(tenure track, 100%)
Albert-Ludwigs-Universität Freiburg
The
Netherlands
The
Netherlands
Germany
September 2005
August 2006
KU Leuven
Belgium
September 2006
September 2008
KU Leuven
Belgium
October 2008
August 2012
KU Leuven
Belgium
September 2012
September 2014
Universiteit Leiden
The
Netherlands
Belgium
September 2012
December 2014
October 2014
November 2014
The
Netherlands
Belgium
January 2015
June 2015
December 2014
June 2015
The
Netherlands
July 2015
August 2018
KU Leuven
Universiteit Leiden
KU Leuven
Universiteit Leiden
4
4. Teaching
DIDACTIC SKILLS
Universiteit Leiden evaluates all lecturers by means of questionnaires. My courses are rated very highly by the students. These
are the evaluations for all my courses:
Computational intelligence 2011-2012:
Computational intelligence 2012-2013:
Computational intelligence 2013-2014:
Computational intelligence 2014-2015:
Contribution to the bachelorclass 2013-2014:
Contribution to data science for policy makers:
7.8
9.0
8.5
8.3
7.7
4.4
(on a scale of 10)
(on a scale of 10)
(on a scale of 10)
(on a scale of 10)
(on a scale of 10 – highest rated speaker)
(on a scale of 5 – highest rated speaker)
I obtained my Basis Qualitication English on October 11, 2013 (C1 qualification in terms of the Common European
Framework of Reference for Languages), and am scheduled to obtain my Dutch National Basis Qualification Education on
November 25, 2015.
EXPERIENCE WITH EDUCATION
Institution
Start and end date
Universiteit Leiden
September 1998 –
December 2004
KU Leuven
February 2007 – June
2014
4
KU Leuven
February 2011 –
April 2011
May 2011, November
2012, November 2013
May 2011 – May 2014
4
September 2011 –
November 2015
November 2014 –
December 2014
November 2013 –
August 2016
4
November 2014,
March 2015,
November 2015
February 2013,
February 2014,
February 2015
2
KU Leuven
University of
Antwerp
Universiteit Leiden
Universiteit Leiden
Universiteit Leiden
Universiteit Leiden
Universiteit Leiden
Number of
hours per
week
2
2
2
2
2
5
Subject, course title
Assistant (full semester) in exercise sessions, one
course per semester: Programming methods
(1998-2004), Computer architecture (2000),
Compiler construction (1999), Algorithms
(2001, 2002), Databases (2003), Complexity
(2004)
Assistant (full semester) in exercise sessions of
Fundamentals of computer science, in the spring
semester.
Substitute lecturer (half semester) of
Fundamentals of computer science
2 lectures per semester of Capita Selecta
Artificial Intelligence
1 lecture per semester in the Master Course on
Data Mining
Lecturer (full semester) of Computational
Intelligence in the autumn semester.
Substitute lecturer (2 lectures) of data mining,
including all examinations.
Coordinator (full semester) of the bachelor class,
with 2 hours of lecture every two weeks in the
spring semester.
Presenter for 2 hours within the course data
science for policy makers, organized for
governmental employees in The Netherlands.
Presenter for 2 weeks of the pre-university
college for highschool students.
5
DUTIES RELATED TO EDUCATION
Currently, I am chair of the education committee (“opleidingscommissie”) for all masters programmes in computer science at
Universiteit Leiden. It is my responsibility to organize regular meetings with students and professors to ensure the quality of
these prorgammes.
I acted as “ombuds” for the bachelor computer science at KU Leuven, in the period 2008-2011.
6
5. Academic curriculum
5.1. Publications
Within square brackets […] the number of citations according to Google Scholar is mentioned. According to Google Scholar
my h-index is 22 and my i10-index is 32. ✰ indicates the publications I consider to be the most important.
Articles
1. T. Guns, A. Dries, S. Nijssen, G. Tack, L. De Raedt. MiningZinc, a declarative framework for constraint-based mining.
Accepted in: Artificial Intelligence journal, 2016.
2. M. Mampaey, S. Nijssen, A. Feelders, R.M. Konijn, A.J. Knobbe. Efficient algorithms for finding optimal binary features
in numeric and nominal labeled data. In: Knowl. Inf. Syst. 42(2), pages 465-492, 2015. (2011: 2.225)
3. V. Dzyuba, M. van Leeuwen, S. Nijssen, L. De Raedt. Interactive Learning of Pattern Rankings. In: International Journal
on Artificial Intelligence Tools 23(6), 32 pages, 2014. (2013: 0.321)
4. H. Sun, T. Guns, A.C. Fierro, L. Thorrez, S. Nijssen, K. Marchal. Unveiling combinatorial regulation through the
combination of ChIP information and in silico cis-regulatory module detection. In: Nucleic Acids Research, volume 6,
issue 40, pages 1-16, 2012. (2012: 8.278, 2013: 8.808) [8]
5. J . Renkens, G. Van den Broeck, S. Nijssen. k-Optimal: A Novel Approximative Inference Algorithm for ProbLog. In:
Machine Learning, 2012. (2012: 1.454, 2013: 1.689) [1]
6. T. Guns, S. Nijssen, L. De Raedt. k-Pattern set mining under constraints. In: IEEE Transactions on Knowledge and Data
Engineering, 2011. (2011: 1.657, 2012: 1.892) [3]
7. T. Guns, S. Nijssen, L. De Raedt. Itemset mining: A constraint programming perspective. In: Artificial Intelligence,
volume 175 (12-13), pages 1951-1983, 2011. (2011: 2.252, 2012: 2.194) [28]
8. S. Nijssen, E. Fromont. Optimal Constraint-based Decision Tree Induction from Itemset Lattices. In: Data Mining and
Knowledge Discovery, volume 21(1), pages 9-51, 2010. (2009: 2.950, 2010: 1.238) [6]
9. A. Dries, S. Nijssen, L. De Raedt. Mining Predictive k-CNF Expressions. In: IEEE Transactions on Knowledge and Data
Engineering, volume 22(5), pages 743-748, 2010. (2010: 1.851, 2011: 1.657) [9]
10. J. Ramon, S. Nijssen. Polynomial Delay Enumeration of Monotone Graph Classes. In: Journal of Machine Learning
Research, volume 10, pages 907-929, 2009. (2009: 2.789, 2010: 2.974) [10]
11. J. Kazius, S. Nijssen, J.N. Kok, T. Bäck, A.P. IJzerman. Substructure Mining Using Elaborate Chemical Representation. In:
Journal of Chemical Information and Modeling, volume 46, pages 597-605, 2006. (2007: 2.986, 2008: 3.528) [68]
12. Y. Chi, S. Nijssen, R. Muntz, J.N. Kok. Frequent Subtree Mining - An Overview. In: Fundamenta Informaticae, volume
66, pages 161-198, IOS Press, 2005. (2006: 0.586, 2007: 0.693) [249]
13. S. Nijssen and T. Bäck. An analysis of the behaviour of simplified genetic algorithms on trap functions. In IEEE Transactions
on Evolutionary Computation, volume 7(1), pages 11-22, 2003. (2004: 3.206, 2005: 1.568) [30]
Chapters in books (no conference proceedings)
1. A. Zimmermann, S. Nijssen. Supervised Pattern Mining and Applications to Prediction. In: C. Aggarwal, J. Han,
Frequent Pattern Mining, pages 425-441, Springer, 2014.
2. S. Nijssen, A. Zimmermann. Constraint-based Pattern Mining. In: C. Aggarwal, J. Han, Frequent Pattern Mining, pages
146-162, Springer, 2014.
3. A. Dries, S. Nijssen, L. De Raedt. BiQL: A Query Language for Analyzing BisoNets. In: Biosociative Networks, Springer,
2012.
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4. J. Besson, J-F. Boulicaut, T. Guns, S. Nijssen. Generalizing Itemset Mining in a Constraint Programming Setting. In:
Inductive Databases and Queries: Constraint-Based Data Mining, S. Dzeroski, B. Goethals, and P. Panov (Eds), pages
467-482, Springer. 2010.
5. B. Bringmann, S. Nijssen, A. Zimmermann. From Local Patterns to Classification Models. In: Inductive Databases and
Queries: Constraint-Based Data Mining, S. Dzeroski, B. Goethals, and P. Panov (Eds), pages 127-154, Springer. 2010.
6. R.D. King, A. Schierz, A. Clare, J. Rowland, S. Nijssen, J. Ramon. Inductive Queries for a Drug Designing Robot
Scientist. In: Inductive Databases and Queries: Constraint-Based Data Mining, S. Dzeroski, B. Goethals, and P. Panov
(Eds), pages 425-451, Springer. 2010.
7. S. Nijssen. Constraint-based Mining. In: Encyclopedia of Machine Learning, pages 221-225, Springer. 2010.
8. S. Nijssen. Tree Mining. In: Encyclopedia of Machine Learning, pages 991-999, Springer. 2010.
Books as editor (including editor of conference proceedings)
1. L. De Raedt, S. Nijssen, B. O'Sullivan, M. Sebag: Constraint, Optimization and Data. (Dagstuhl Seminar 14411).
Dagstuhl Reports 4(10), 2014.
2. H. Blockeel, K. Kersting, S. Nijssen, F. Zelezný. Special section of selected papers from ECML PKDD, Machine Learning,
2013.
3. H. Blockeel, K. Kersting, S. Nijssen, F. Zelezný. Special section of selected papers from ECML PKDD, Data Mining and
Knowledge Discovery, 2013.
4. H. Blockeel, K. Kersting, S. Nijssen, F. Zelezný. Machine Learning and Knowledge Discovery in Databases – European
Conference, ECMLPKDD 2013. Proceedings, Part I–III. Lecture Notes in Artificial Intelligence, 2013.
5. L. De Raedt, S. Nijssen, B. O'Sullivan, P. Van Hentenryck: Constraint Programming meets Machine Learning and Data
Mining (Dagstuhl Seminar 11201). Dagstuhl Reports 1(5), 2011.
6. S. Nijssen, L. De Raedt. Proceedings of the International Workshop on Constraint-Based Mining and Learning, 2007.
7. B. Goethals, S. Nijssen and M.J. Zaki. Proceedings of the Open Source Data Mining Workshop. ACM Press, 2005.
8. S. Nijssen, T. Meinl, G. Karypis. Proceedings of the Third International Workshop on Mining Graphs, Trees and
Sequences. 2005.
Papers in prominent conferences
These are international conferences with an acceptance rate below 50%, with at least 50 submissions. For each submission
between […] brackets the number of citations according to Google Scholar is indicated. Furthermore, acceptance rates for
these publications are indicated.
1. B. Babaki, T. Guns, S. Nijssen, L. De Raedt. Constraint-Based Querying for Bayesian Network Exploration. In:
Proceedings of the International Symposium on Intelligent Data Analysis (IDA), pages 13-24, 2015. (Poster
presentation)
66 submissions, 15 accepted as regular paper, 17 accepted for poster presentation; overall acceptance rate: 48.4%
2. T. Le Van, M. van Leeuwen, S. Nijssen, L. De Raedt. Rank Matrix Factorisation. In: Pacific-Asian Conference on
Principles of Knowledge Discovery in Databases (PAKDD), pages 734-746, 2015.
405 submissions, 90 accepted; acceptance rate: 22.2%
8
3. B. Babaki, T. Guns, S. Nijssen. Constrained Clustering Using Column Generation. In: Integration of AI and OR
Techniques in Constraint Programming - 11th International Conference (CPAIOR), LNCS 8451, pages 438-454,
Springer; Cork, Ireland, May 19-23, 2014. [1]
70 submissions, 33 accepted; acceptance rate: 47.1%
4. T. Le Van, M. van Leeuwen, S. Nijssen, A.C. Fierro, K. Marchal, L. De Raedt. Ranked Tiling. In: Machine Learning and
Knowledge Discovery in Databases - European Conference (ECML/PKDD), LNCS 8725, pages 98-113, Springer;
Nancy, France, September 15-19, 2014. [1]
588 submissions, 130 accepted; acceptance rate: 22.1%
5. R. Cachucho, M. Meeng, U. Vespier, S. Nijssen, A.J. Knobbe. Mining multivariate time series with mixed sampling rates.
In: The 2014 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp), pages 413423, ACM Press; Seattle, Washington, September 13-17, 2014.
454 submissions, 71 accepted; acceptance rate: 15.6%
6. T. Guns, A. Dries, G. Tack, S. Nijssen, L. De Raedt. The MiningZinc framework for Constraint-based Itemset Mining
(demo). In: Proceedings of the IEEE International Conference on Data Mining (ICDM), pages 1081-1084, IEEE
Computer Society; Dallas, Texas, December 7-10, 2013. (Short paper)
809 submissions, 94 accepted as regular paper, 65 accepted as short paper; acceptance rate regular papers: 11.6%,
overall acceptance rate: 19,7%
7. B. Negrevergne, A. Dries, T. Guns, S. Nijssen. Dominance programming for itemset mining. In: Proceedings of the IEEE
International Conference on Data Mining (ICDM), pages 557-566, IEEE Computer Society; Dallas, Texas, December
7-10, 2013. (Regular paper) [8]
8. V. Dzyuba, M. van Leeuwen, S. Nijssen, L. De Raedt. Active Preference Learning for Ranking Patterns. In: Proceedings
of the IEEE International Conference on Tools with Artificial Intelligence (ICTAI), pages 532-539, IEEE Computer
Society; Washington DC, November 4-6, 2013. (Best paper award, regular paper) [2]
299 submissions, 77 accepted as regular paper, 43 accepted as short paper; acceptance rate regular papers: 25.8%,
overall acceptance rate: 40.1%
9. T. Guns, A. Dries, G. Tack, S. Nijssen, L. De Raedt. MiningZinc: A Modeling Language for Constraint-Based Mining. In:
Proceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI); Beijing, China, August 3-9,
2013. [11]
1473 submissions, 413 accepted; acceptance rate: 28.0%
10. S. Gilpin, S. Nijssen, I. Davidson. Formalizing Hierarchical Clustering as Integer Linear Programming. In: Proceedings
of the Twenty-Seventh AAAI Conference on Artificial Intelligence (AAAI); Bellevue, Washington, July 14-18, 2013.
[2]
690 submissions, 203 accepted; acceptance rate: 29.4%
11. A. Dries, S. Nijssen. Mining Patterns in Networks using Homomorphism. In: Proceedings of the SIAM International
Conference on Data Mining (SDM), pages 260-271, SIAM/Omnipress; Anaheim, California, April 26-28, 2012. (Oral
presentation) [6]
363 submissions, accepted 53 for oral presentation and 46 for poster presentation; acceptance rate for oral
presentations: 14.6%, overall acceptance rate: 27.3%
9
12. M. Mampaey, S. Nijssen, A. Feelders, A. Knobbe. Efficient Algorithms for Finding Richer Subgroup Descriptions in
Numeric and Nominal Data. In: the IEEE International Conference on Data Mining (ICDM), pages 465-492, IEEE
Computer Society; Brussels, Belgium, December 10-13, 2012. (Regular paper) [4]
756 submissions, 81 accepted as regular paper, 70 accepted as short paper; acceptance rate regular papers: 10.7%,
overall acceptance rate: 20.0%
13. T. Guns, S. Nijssen, L. De Raedt. Evaluating Pattern Set Mining Strategies in a Constraint Programming Framework. In:
Proceedings of the 15th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD), LNCS 6635,
pages 382-394; Shenzhen, China, May 24-27, 2011. (Long paper) [6]
331 submissions, 32 accepted as long paper, 58 accepted as short paper; acceptance rate long papers: 9.7%, overall
acceptance rate: 27.2%
14. J. Renkens, G. Van den Broeck, S. Nijssen. k-Optimal: A novel approximate inference algorithm for ProbLog. In:
International Conference on Inductive Logic Programming (ILP); Windsor, United Kingdom, July 31-August 3, 2011.
(Best student paper award, accepted for special issue of journal) [3]
66 submissions, 31 accepted, 5 invited for special issue of journal; invited for special issue: 7.6%, overall acceptance
rate: 47.0%
15. T. Guns, H. Sun, K. Marchal, S. Nijssen. Cis-regulatory Module Detection using Constraint Programming. In:
Proceedings of the IEEE International Conference on Bioinformatics and Biomedicine (BIBM), pages 363-368, IEEE
Computer Society; Hong Kong, China, December 18-21, 2010. (Regular paper) [4]
355 submissions, 62 accepted as regular paper, 69 accepted as short paper; acceptance rate regular papers: 17.5%,
overall acceptance rate: 36.9%
16. S. Nijssen, T. Guns. Integrating Constraint Programming and Itemset Mining. In: Proceedings of the 14th European
Conference on Machine Learning and Knowledge Discovery in Databases (ECMLPKDD), LNCS 6322, pages 467-482,
Springer; Barcelona, Spain, September 20-24, 2010. [7]
658 submissions, 120 accepted; acceptance rate: 18.2%
17. L. De Raedt, T. Guns, S. Nijssen. Constraint Programming for Data Mining and Machine Learning. In: Proceedings of
the 24th AAAI Conference on Artificial Intelligence (AAAI), AAAI Press; Atlanta, Georgia, July 11-15, 2010. (Nectar
track) [28]
48 submissions to the Nectar track, 12 accepted; Acceptance rate: 25%
18. A. Dries, S. Nijssen, L. De Raedt. A Query Language for Analyzing Networks. In: Proceedings of the 18 th ACM
Conference on Information and Knowledge Management (CIKM), pages 485-494, ACM Press; Hong Kong, China,
November 2-6, 2009. (Full paper) [25]
847 submissions, 123 accepted as full paper, 171 accepted as short paper; acceptance rate full papers:
14.5%, acceptance rate short papers: 34.7%
19. S. Nijssen, T. Guns, L. De Raedt. Correlated Itemset Mining in ROC Space: A Constraint Programming Approach. In:
Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD),
pages 647-656, ACM Press; Paris, France, June 28-July 1, 2009. (Short presentation) [64]
10
537 submissions, 50 accepted for long presentation, 55 accepted for short presentation; overall
acceptance rate: 19.6%
20. S. Nijssen, L. De Raedt. Grammar Mining. In: Proceedings of the SIAM International Conference on Data Mining
(SDM), pages 1026-1037, SIAM; Sparks, Nevada, April 30-May 2, 2009. (Full paper)
Acceptance rate for 2009 is not known; in 2012 the acceptance rate for full papers was 14.6%
21. B. Bringmann and S. Nijssen. What is Frequent in a Single Graph? In: Advances in Knowledge Discovery and Data
Mining, 12th Pacific-Asia Conference (PAKDD), LNCS 5012, pages 858-863, Springer; Osaka, Japan, May 20-23, 2008.
(Short paper) [89]
312 submissions, 37 accepted as long paper, 35 accepted as short paper; overall acceptance rate: 23.1%
22. L. De Raedt, T. Guns, S. Nijssen. Constraint Programming for Itemset Mining. In: Proceedings of the 14th ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 204-212, ACM Press;
Las Vegas, August 24-27, 2008. (Short presentation) [97]
510 submissions, 50 accepted for long presentation, 45 for short presentation; overall acceptance rate: 18.6%
23. S. Nijssen. Bayes Optimal Classification for Decision Trees. In: Machine Learning, Proceedings of the Twenty-Fifth
International Conference (ICML), pages 696-703, ACM Press; Helsinki, Finland, July 5-9, 2008. [1]
583 submissions, 158 accepted; acceptance rate: 27.10%
24. S. Nijssen and E. Fromont. Mining Optimal Decision Trees from Itemset Lattices. In: Proceedings of the 13th ACM
SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 530-539, ACM Press;
San Jose, California, August 12-15, 2007. [26]
513 submissions, 92 accepted; acceptance rate: 17.9%
25. B. Bringmann, A. Zimmermann, L. De Raedt and S. Nijssen. Don't be afraid of simpler patterns. In: Proceedings of the
10th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), LNCS 4213,
pages 55-66, Springer; Berlin, Germany, September 18-22, 2006. (Long paper) [58]
564 submissions, 82 accepted as long paper, 62 accepted as short paper; acceptance rate long papers:
14.5%, overall acceptance rate: 25.5%
26. S. Nijssen and J.N. Kok. Ideal refinement of datalog clauses using primary keys. In: Proceedings of the 16th European
Conference on Artificial Intelligence (ECAI), pages 520-524, IOS Press; Valencia, Spain, August 22-27, 2004. ( Oral
presentation) [2]
653 submissions, 181 accepted for oral presentation, 87 accepted for poster presentation; acceptance
rate oral presentations: 27.7%, overall acceptance rate: 41.0%
27. S. Nijssen and J.N. Kok. A quickstart in frequent structure mining can make a difference. In: Proceedings of the 10th
ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD), pages 647-652, ACM
Press; Seattle, Washington, August 22-25, 2004. (Poster presentation) [438]
337 submissions, 40 accepted for oral presentation, 45 for poster presentation; overall acceptance rate: 25.2%
11
28. S. Nijssen and J.N. Kok. Efficient frequent query discovery in FARMER. In: Proceedings of the 7th European
Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD), LNAI 2431, pages 350-362,
Springer; Cavtat, Croatia, September 22-26, 2003. [57]
332 submissions, 80 accepted; acceptance rate: 24.1%
29. S. Nijssen and J.N. Kok. Faster association rules for multiple relations. In: Proceedings of the Seventeenth International
Joint Conference on Artificial Intelligence (IJCAI), pages 891-896, Morgan Kaufmann; Seattle, Washington, August 410, 2001. [103]
796 submitted, 197 accepted; acceptance rate: 24.7%
Invited Contributions, National Conferences, Workshops
These are invited contributions to conferences, workshops with high or unknown acceptance rates, or national conferences.
1. E. Aksehirli, S. Nijssen, M. van Leeuwen, B. Goethals. Finding Subspace Clusters using Ranked Neighborhoods. In:
Proceedings of ICDM workshop on High Dimensional Data Mining (HDM), 2015.
2. T. Guns, A. Dries, G. Tack, S. Nijssen and L. De Raedt. Automatic solver chaining in MiningZinc. In: Proceedings of the
Fourteenth International Workshop on Constraint Modelling and Reformulation (ModRef), 2015.
3. T. Le Van, C. Fierro, T. Guns, M. van Leeuwen, S. Nijssen, L. De Raedt, K. Marchal. Mining Local Staircase Patterns in
Noisy Data. In: the International Workshop on Co-Clustering and its Applications (CoClus), 2012.
10 submissions, 6 accepted; acceptance rate: 60%
4. H. Blockeel, K. Kersting, S. Nijssen, F. Zelezný. A Revised Publication Model for ECML PKDD, CoRR abs/1207.6324,
2012.
5. T. Guns, S. Nijssen, A. Zimmermann, L. De Raedt. Declarative heuristic search for pattern set mining. In: Workshop on
Declarative Pattern Mining in conjunction with the 11th IEEE International Conference on Data Mining, pages 11-14,
IEEE Computer Society, 2011.
9 submissions, 6 accepted; acceptance rate: 66.7%
6. S. Nijssen, T. Guns, and A. Jimenez. Constraint-based Pattern Mining in Multi-Relational Databases. In: Workshop on
Declarative Pattern Mining in conjunction with the 11th IEEE International Conference on Data Mining, pages 1-5,
IEEE Computer Society, 2011.
7. L. De Raedt, S. Nijssen. Towards Programming Languages for Machine Learning and Data Mining (Extended Abstract).
In: Foundations of Intelligent Systems - 19th International Symposium (ISMIS), LNCS 6804, pages 25-32, 2011.
8. A. Dries, S, Nijssen. Analyzing Graph Databases by Aggregate Queries. In: Proceedings of the Eighth International
Workshop on Mining and Learning with Graphs (MLG), 2010.
9. T. Guns, H. Sun, S. Nijssen, A. Sanchez-Rodriguez, L. De Raedt, K. Marchal. Proximity-based cis-regulatory module
detection using constraint programming for itemset mining. Poster at the 9th European Conference on Computational
Biology (ECCB), Ghent, September 26-29, 2010.
10. M. Verbeke, B. Berendt and S. Nijssen. Data mining, interactive semantic structuring, and collaboration: A diversityaware method for sense-making in search. In: Living Web, 2009.
12
11. B. Bringmann, S. Nijssen and A. Zimmermann. Pattern-based Classification: A Unifying Perspective. In: Proceedings of
`From Local Patterns to Global Models': Second ECML PKDD Workshop (LeGo), 2009.
12. T. Guns, S. Nijssen and L. De Raedt. Constraint Programming for Correlated Itemset Mining (abstract). In: Proceedings
of the 21th Belgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2009.
13. H. Blockeel and S. Nijssen. Induction of Node Label Controlled Graph Grammar Rules. In: Proceedings of the Sixth
International Workshop on Mining and Learning with Graphs (MLG), 2008. [6]
14. J. Ramon and S. Nijssen. General Graph Refinement with Polynomial Delay. In: Proceedings of the Fifth International
Workshop on Mining and Learning with Graphs (MLG), 2007. [3]
43 submissions, 16 accepted; acceptance rate: 37.2%
15. S. Nijssen and E. Fromont. Apprentissage d'arbres de décision optimaux à partir de treillis d'itemsets. In: Proceedings of
the Conférence francophone sur l'apprentissage automatique, 2007.
16. S. Nijssen and E. Fromont. Learning Optimal Decision Trees. In: Proceedings of the Annual Machine Learning
Conferene of Belgium and The Netherlands (Benelearn), pages 53-60, 2007.
17. S. Nijssen. Mining Interpretable Subgraphs. In: Proceedings of the Fourth International Workshop on Mining and
Learning with Graphs (MLG), 2006.
18. S. Nijssen and J.N. Kok. Multi-Class Correlated Pattern Mining, extended version. In: Proceedings of the Fourth
International Workshop on Knowledge Discovery in Inductive Databases (KDID), revised and selected papers, LNCS
3933, pages 165-187, Springer, 2006.
19. S. Nijssen and J.N. Kok. Frequent Subgraphs: Runtimes Don't Say Everything. In: Proceedings of the Fourth
International Workshop on Mining and Learning with Graphs (MLG), 2006.
20. S. Nijssen and J.N. Kok. On Multi-Class Correlated Pattern Mining (abstract). In: Proceedings of the 18th
Belgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2006.
21. S. Nijssen and J.N. Kok. The Gaston tool for frequent subgraph mining. In: Proceedings of the International Workshop
on Graph-Based Tools (Grabats), volume 127 of Electronic Notes in Theoretical Computer Science, pages 77-87, 2004.
(Invited contribution)
22. S. Nijssen and J.N. Kok. Frequent graph mining and its application to molecular databases. In: Proceedings of the IEEE
International Conference on Systems, Man and Cybernetics (SMC), invited sessions, 2004. (Invited contribution)
23. S. Nijssen and J.N. Kok. Efficient discovery of frequent unordered trees. In: Proceedings of the First International
Workshop on Mining Graphs, Trees and Sequences (MGTS), 2003.
24. S. Nijssen and J.N. Kok. Proper refinement of datalog clauses using primary keys. In: Proceedings of the 15th
Belgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2003.
25. S. Nijssen and T. Bäck. An analysis of the behavior of simplified evolutionary algorithms on trap functions (abstract). In:
Proceedings of the 14th Belgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2002.
26. S. Nijssen and J.N. Kok. Tree sets: Towards a set-oriented view on multi-relational data mining. In: Proceedings of the
14th Belgium/Netherlands Conference on Artificial Intelligence (BNAIC), 2002.
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5.2. Scholarly activities
a) International or national conferences I have organized
1. Co-organizer of the Dagstuhl Seminar on “Constraints, Optimization and Data”, 2014.
2. Co-organizer of Data mining: beyond the horizon workshop in Bristol, November 19-21, 2014.
3. Chair of the European Conference on Machine Learning and the European Conference on Principles and Practice of
Knowledge Discovery in Databases (ECML PKDD), 2013, with over 500 participants.
4. Tutorial co-chair of the European Conference on Machine Learning and the European Conference on Principles and
Practice of Knowledge Discovery in Databases (ECML PKDD), 2012.
5. Co-chair of the ECML PKDD Workshop on Instant and Interactive Data Mining (IID), 2012.
6. Publicity co-chair of the IEEE International Conference on Data Mining (IEEE ICDM), 2012.
7. Workshop and tutorial co-chair of the European Conference on Machine Learning and the European Conference on
Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2008.
8. Co-chair of the ECML PKDD Workshop on Constraint-based Mining and Learning (CMILE), 2007.
9. Co-chair of the International Workshop on Open Source Data Mining (OSDM), 2005.
10. Co-chair of the International Workshop on Mining Graphs, Trees and Sequences (MGTS), 2004.
11. Co-organizer of the Dagstuhl Seminar on “Constraint programming meets machine learning and data mining”, 2011.
12. Co-organizer of the International Workshop on Mining Graphs, Trees and Sequences (MGTS), 2003.
b) Invited talks and tutorials
For all conference and workshop publications there was a corresponding conference presentation. In addition, I gave
several invited talks and tutorials:
1. S. Nijssen. Relational Constraint Programming. Invited talk at the Orleans workshop on constraint programming and
data mining, November 2014.
2. S. Nijssen. Constraint programming and data mining. Invited talk at the First Workshop on Combining Constraint
Solving with Mining and Learning, August 2012.
3. L. De Raedt, S. Nijssen. Machine Learning and Data Mining: Challenges and Opportunities for Constraint
Programming. Invited tutorial at the 17th International Conference on Principles and Practice of Constraint
Programming (CP), 2011.
4. B. Bringmann, S. Nijssen, N. Tatti, J. Vreeken, A. Zimmermann. Mining sets of patterns – Next Generation Pattern
Mining. Tutorial at the IEEE International Conference on Data Mining (ICDM), 2011.
5. B. Bringmann, S. Nijssen, N. Tatti, J. Vreeken, A. Zimmermann. Mining sets of patterns. Tutorial at the 14th European
Conference on Machine Learning and Knowledge Discovery in Databases (ECMLPKDD), 2010.
6. S. Nijssen. Constraint programming for itemset mining. Advanced SIKS-course on computational intelligence. October,
2011.
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7. S. Nijssen. Mining Structures. Autumn days of the Institute for Programming research and Algorithmics (IPA),
November 24, 2004.
c)
Obtained research funding
1. NWO TOP Module 2 grant: Probabilistic Features for Intelligent Declarative Data Science (ProFIDDS), January 2016 –
December 2019. (1 PhD student)
2. NWO Creative Industry programme grant: Making Sense of Illustrated Handwritten Archives, together with Jaap van
den Herik, Aske Plaat, Katy Wolstencroft, Michael Lew, Fons Verbeek, Joost Kok, Lambert Schomaker (Universiteit
Groningen), Lissa Roberts (University of Twente), René Dekker (Naturalis), Andreas Weber (University of Twente),
Maarten Heerlien (Naturalis), Michiel Thijssen (Brill), January 2016 – December 2019. (1 PhD student)
3. NWO Indo-Dutch Joint Research Programme for ICT 2014 EW: A Systems Approach towards Data Mining and
Prediction in Airlines Operations (SAPPAO), together with Thomas Bäck, Michael Emmerich, Dhish Kumar (IIT
Roorke), November 2015 – August 2019. (1 PhD student)
4. FWO Project Grant, joint with L. De Raedt, B. Goethals, N. Tatti, J. Vreeken. “Instant Interactive Data Exploration”,
January 2012 – December 2015. (1 PhD student)
5. FWO Post-doc Grant. “An Integrated Solver for Data Mining”, October 2011 – September 2014. (Personal post doc
grant)
6. FWO Project Grant, joint with L. De Raedt and B. Goethals. “Principles of Knowledge Discovery in Pattern Sets”,
January 2009 – December 2012. (1 PhD student)
7. FWO Post-doc Grant. “From Constraints to Knowledge”, October 2008 – September 2011. (Personal post doc grant)
d) Promotorship or regular supervision activities related to doctoral dissertations
I was co-promotor of Tias Guns, who defended his PhD in 2012.
I was member of the jury of Anton Dries (Leuven, 2010), Eelke Van der Horst (Leiden, 2012), Calin Garboni
(Antwerp, 2012), Tayena Hendrickx (Antwerp, 2015), Bo Gao (Leuven, 2015), Yan Wu (Leuven, 2015), Ugo Verspier
(Leiden, 2015).
I am co-promotor of Thanh Le Van at KU Leuven.
5.3. Membership of program committees
1.
Senior member of the program committee of ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining (KDD), 2015, 2016.
2.
Area chair of the IEEE International Conference on Data Mining (ICDM), 2014, 2015.
3.
Member of the program committee of the ACM SIGKDD International Conference on Knowledge Discovery and
Data Mining (KDD), 2009-2014.
4.
Member of the program committee of the European Conference on Machine Learning and the European Conference
on Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), 2006-2012, 2014, 2015.
5.
Senior member of the program committee of the International Joint Conference on Artificial Intelligence (IJCAI),
2011, 2013.
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6.
Senior member of the program committee of the ACM Conference on Information and Knowledge Management
(CIKM), 2011.
7.
Member of the program committee of the International Joint Conference on Artificial Intelligence (IJCAI), 2009.
8.
Member of the program committee of the SIAM International Conference on Data Mining (SDM), 2008-2011.
9.
Member of the program committee of the European Conference on Artificial Intelligence (ECAI), 2008, 2010, 2012.
10. Member of the program committee of the IEEE International Conference on Data Mining (ICDM), 2006-2013.
11. Member of the program committee of the International Conference on Discovery Science (DS), 2009.
12. Member of the program committee of the ACM Conference on Information and Knowledge Management (CIKM),
2007.
13. Member of the program committee of the International Workshop on Mining and Learning with Graphs (MLG),
2006-2007, 2009.
14. Member of the program committee of the International Workshop on going From Local Patterns to Global Models
(LeGo), 2008-2009.
15. Member of the program committee of the International Workshop on Knowledge Discovery in Inductive Databases
(KDID), 2006.
16. Member of the program committee of the International Workshop on Knowledge Discovery from XML documents
(KDXD), 2006.
5.4 Reviewer for journals
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
11.
12.
Journal of Machine Learning.
Journal of Machine Learning Research.
Journal of Data Mining and Knowledge Discovery.
Journal of Intelligent Data Analysis.
Journal of Knowledge and Information Systems.
International Journal of Data Mining and Bioinformatics.
IEEE Transactions on Nanobioscience.
IEEE Transactions on Knowledge and Data Engineering.
SIGKDD Explorations.
ACM Transactions on Knowledge Discovery from Data.
Fundamenta Informaticae.
Theoretical Computer Science.
5.5 Positions as editor
1.
Member of the editorial board of the Data Mining and Knowledge Discovery journal (DMKD) of Springer, since
2015.
2.
Associate editor of the editorial board of the Knowledge and Information Systems journal (KAIS) of Springer, since
2014.
3.
Member of the editorial board of the Machine Learning journal (ML) of Springer, since 2010.
4.
Member of the guest editorial board of the journal track of ECMLPKDD, since I founded this track in 2012.
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5.6 Participation in projects
Next to the projects that I was co-promotor of, I participate or participated in a number of other research
projects:
1.
January 2012 – June 2015: EU IST-FET project “ICON”
Partners: Katholieke Universiteit Leuven (Luc De Raedt and myself, Belgium), University College Cork (Barry
O’Sullivan, Ireland), Universita di Pisa (Dino Pedreschi, Italy), Université de Montpellier (Christian Bessiere, France)
Role: I wrote large parts of the project proposal, coordinated the preparations, and am a principal investigator in the
project.
2.
September 2008 – August 2011: EU IST-FET project “BISON”
Partners: University of Konstanz (Michael Berthold, Germany), University of Ulster (Werner Dubitzy, United
Kingdom), Jozef Stefan Institute (Nada Lavrac, Slovenia), Katholieke Universiteit Leuven (Luc De Raedt, Belgium),
Otto-von-Guericke Universität Magdeburg (Andreas Nürnberger, Germany), University of Helsinki (Hannu
Toivonen, Finland), University of Bristol (Trevor Martin, United Kingdom), European Centre for Soft Computing
(Christian Borgelt, Spain)
Role: I attended several meetings of this project and contributed scientifically. I was not employed on the project.
3.
September 2005 – August 2008: EU IST-FET project “Inductive Querying” (IQ)
Partners: Katholieke Universiteit Leuven (Luc De Raedt, Belgium), University of Antwerp (Bart Goethals, Belgium),
Jozef Stefan Institute (Saso Dzeroski, Slovenia), INSA Lyon (Jean-François Boulicaut, France), University of Wales in
Aberystwyth (Ross D. King, Wales) and University of Helsinki (Heikki Mannila, Finland).
Role: I was full time employed as a researcher on this project, and was responsible for reporting KU Leuven’s
contributions.
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6. Academic honours and awards or prizes
Academic honours and awards or prizes
1
2
3
4
5
Description
Winner of the yearly Master's Thesis price of the district South-Holland of the Dutch Computer
Science Foundation.
Nominated for the “discovery of the year” award of the Faculty of Mathematics and Natural Sciences,
Leiden University.
Innovation award of the “Mining Patterns and Subgroups” workshop at the Lorentz center, Leiden,
together with Tias Guns and Luc De Raedt for the contribution “k-Pattern Set Mining under
Constraints”.
Best student paper award of the International Conference on Inductive Logic Programming (ILP),
together with Joris Renkens and Guy Van den Broeck for the contribution “k-Optimal: A novel
approximate inference algorithm for ProbLog”.
Best paper award of the IEEE International Conference on Tools with Artificial Intelligence (ICTAI),
together with Vladimir Dzyuba, Matthijs van Leeuwen, and Luc De Raedt, for the contribution
“Active Preference Learning for Ranking Patterns”.
Period
2001
2006
2010
2011
2013
Also, I am proud that my PhD student Tias Guns, for whom I was the daily supervisor, has won several prizes with our work,
including the dissertation award of the European Coordinating Committee for Artificial Intelligence (ECCAI, 2013), the
dissertation award of the Association for Constraint Programming (ACP, 2013) and the ORBEL Wolsey award for best ORrelated open source implementation (2013). I have contributed extensively to this research as well.