Dr. Maryam Amir Haeri

Dr. Maryam Amir Haeri
Post:TU Kaiserslautern
Postfach 3049
67663 Kaiserslautern
Room: 48-669
Email: haeri [at] cs.uni-kl.de
Phone: +49 631 205 3351
ORC ID:
Google Scholar: Here
Researchgate:

Research interest

I am interested in the following research areas:
  • Big Data Analytics
  • Fairness in Machine Learning
  • Complex Networks (Social Network Analysis)
  • Large Scale Machine Learning
  • Data Mining
  • Evolutionary Computation

Education

09/2009 – 08/2014 AmirKabir University of Technology
Ph.D. in Artificial Intelligence
Thesis Title: Statistical Genetic Programming for Solving Symbolic Regression Problems.
Thesis Degree: Excellent
0.9/2011–0.3/2012 ICAR-CNR (Institute for High Performance Computing of the Italian National Research Council), Rende, Italy
Ph.D. Visiting Student
09/2007 – 08/2009 Sharif University of Technology
M.Sc. in Information Technology
Thesis Title: Analyzing Alert Correlation in Intrusion Detection Systems
09/2003 – 08/2007 Sharif University of Technology
B.Sc. in Software Engineering
Thesis Title: Data Mining Using Adaptive Local Searches Based on Meta- Lamarckian Learning

Teaching

Fall (2019) Data Science Literacy — Teaching graduate course, CS department of TU Kaiserslautern.
Spring (2016 & 2017 & 2018) Complex Networks Algorithms (Social Network Analysis) — Teaching graduate course, CEIT department of AmirKabir University of Technology.
Fall (2015 & 2016 & 2017 & 2018) & Spring (2015 & 2017 ) Big Data Analytics — Teaching graduate course, CEIT department of AmirKabir University of Technology.
Fall (2015, 2016) & Spring (2018) Fuzzy sets and systems — Teaching graduate course, CEIT department of AmirKabir University of Technology.
Fall (2018) Evolutionary Computations — Teaching graduate course, CEIT department of AmirKabir University of Technology.
Spring (2016 & 2017 & 2018), Fall (2018) Probability and Statistics — Teaching under graduate course, CEIT department of AmirKabir University of Technology.
Fall (2015 & 2016& 2017) Database Systems — Teaching under graduate course, CEIT department of AmirKabir University of Technology.

Publications

Journal Papers

  • S. A. Fadaee, and M. Amir Haeri. "Classification Using Link Prediction." Neurocomputing, Vol 359, 2019.
  • M. Mirkhan, M. Amir Haeri, and M. R. Meybodi. "Analytical Split Value Calculation for Numerical Attributes in Hoeffding Trees with Misclassification-Based Impurity." Annals of Data Science, (first Online), 2019.
  • M. H. Amini, M. Abdollahi, M. Amir Haeri. Rule-centred genetic programming (RCGP): an imperialist competitive approach, recently accepted in Applied Intelligence, 2019.
  • M. Amir Haeri, M. M. Ebadzadeh , and G. Folino. "Statistical Genetic Programming for SymbolicRegression." Applied Soft Computing, Vol 60, 2017.
  • E. Radkani, S. Hashemi, A. Keshavarz-Haddad, and M. Amir Haeri. "An entropy-based distancemeasure for analyzing and detecting metamorphic malware." Applied Intelligence, Vol. 48, No. 6,Springer International Publishing, 2018.
  • M. Amir Haeri, M. M. Ebadzadeh , and G. Folino, Improving GP Generalization: A Variance-Based Layered Learning Approach, Journal of Genetic Programming and Evolvable Machines,Vol. 16, No. 1, pages 27–55. Springer International Publishing, 2015.
  • M. Amir Haeri and M. M. Ebadzadeh, Estimation of Mutual Information by the Fuzzy Histogram,Journal of Fuzzy Optimization and Decision Making, Vol. 13, No. 3, pages 287–318. SpringerInternational Publishing, 2014.
  • H. Farhadi, M. Amir Haeri, and M. Khansari, Alert Correlation and Prediction Using Data Miningand HMM, ISC International Journal of Information Security (ISeCure Journal), Vol. 3, No. 2,2011.

Book Chapters

  • G. Folino, M. Guarascio, M. Amir Haeri, Deep Learning on Big Data, Springer InternationalPublishing, Cham, 2018, pp 1-10, doi:10.1007/978-3-319-63962-8_307-1, URLhttps://doi.org/10.1007/978-3-319-63962-8_307-1M.
  • Amir Haeri, M. M. Ebadzadeh, and G. Folino. Statistical Genetic Programming: The Role ofDiversity. In V. Snel, P. Krmer, M. Kppen, and G. Schaefer, editors, Soft Computing inIndustrial Applications, volume 223 of Advances in Intelligent Systems and Computing, pages37–48. Springer International Publishing, 2014.

Conference Papers

  • G. Folino, F. S. Pisani, L. Pontieri, P. Sabatino, and M. Amir Haeri. "Using genetic programming for combining an ensemble of local and global outlier algorithms to detect new attacks." In Proceedings of the Genetic and Evolutionary Computation Conference Companion (GECCO), ACM, 2019.
  • R. Al-taei, M. Amir Haeri. "An Ensemble Angle-Based Outlier Detection for Big Data." International Congress on High-Performance Computing and Big Data Analysis. Springer, Cham, 2019.
  • M. M. D. Khomami, M. Amir Haeri, M. R. Meybodi, and A. M. Saghiri. "An Algorithm for Weighted Positive Influence Dominating Set Based on Learning Automata." IEEE 4th International Conference on Knowledge-Based Engineering and Innovation (KBEI), 2017.
  • A. Khoshkbarchi, A. Kamali, A. Amjadi, M. Amir Haeri, "A modified hybrid Fuzzy clustering method for big data." Telecommunications (IST), 8th International Symposium on. IEEE, 2016.
  • M. Elyasi, A. rezvaian, M. Meybodi, M. Amir Haeri, "A fast algorithm for overlapping community detection." Information and Knowledge Technology (IKT), 2016 Eighth International Conference on. IEEE, 2016.
  • M. Amir Haeri, and R. Jalili, RTEAS: A Real Time Algorithm for Extracting Attack Scenarios from Intrusion Alert Stream, in Proceedings of the 6th International ISC Conference on Information Security & Cryptology, 2009.
  • M. S. Dousti, M. Amir Haeri, and R. Jalili, Privacy-Preserving Single-Layer Perceptron, in Proceedings of the 6th International ISC Conference on Information Security & Cryptology, 2009.
  • P. Bahreini, M. Amir Haeri, and R. Jalili, A Probabilistic Approach to Intrusion Alert Correlation, in Proceedings of the 5th International ISC Conference on Information Security & Cryptology, 2008.
  • M. Amir Haeri, Z. Ahmadi, J. Habibi, and M. Saniee Abadeh, Classification of Network Intrusions Using Adaptive Local Searches Based on Meta-Lamarckian Learning, in Proceedings of the 1st International eCity Conference, 2008. (In Persian)