Dr.Ir.Maryam Miradi
Date of Birth: 21/09/ 1976
Work Phone: 0153611676
E-mail: maryam.miradi@profoundanalytics.com
Current Status
Director, Profound Analytics
Mail: Caro van Eycklaan 1, 2642 BM Pijnacker
Mobile Phone: 0655878855
website: www.profoundanalytics.com
since January 2010
Activities
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Advanced Business Analytics, data mining, knowledge discovery with artificial
intelligence.
Intelligent database marketing.
Giving insight into business by analysing/modelling data.
Developing Classification/Regression, Clustering, and forecasting Models in
order to solve Business and Science Problems
Employing Artificial Intelligence/Computational Intelligence based techniques
such as Artificial Neural Network, Support vector machines, support vector
regressions, classification and regression trees, fuzzy logic, rough set theory,
time series, feature selection methods for modelling and analysis.
Visualisation and presentation of results using Tableau, Microsoft Excel, and
Microsoft Powerpoint
Publications of scientific papers in field of artificial intelligence
Previous Experience
Business Intelligence Specialist, Logica
January 2009 – December 2009
Project
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Ahold Europe, Business Analytics
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Developing forecasting, classification or clustering models Using artificial
intelligence based algorithms and techniques such neural network, support
vector machines, fuzzy logic etc. to discover knowledge from data
Giving advice based on analysis
Leading Master Students in their Traineeship/Graduation project
Creating an analysis task from a business problem
Communicating with Business and presenting analysis results to them
Responsibilities
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Achievements
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Reduction Shrinkage : Analysis “fat finger issue” – proving non-existing
shrinkage of € 5 mio and 15.000 errors per year
Analysis of most critical factor concerning remains in Non Food
Forecasting initial logistic supply and the optimal moment for last delivery
Assortment Differentiation: Intelligent feature selection to determine the most
important factors influencing profits of each assortment based on data from
assortments shelf space, competitor stores, and demographic profiles
Predicting for individual customers what they will buy in their next trips
Analysis of how individual customers group their products in order to discover
smarter product groups in near future
Analysis of potential changing customer behavior during financial crisis
Customer Driven-Marketing: Use of customer data to segment, target, and
personalize offerings
E-commerce Customer Analysis: Clustering the customers based on their
spending and their shopping frequency and the determination of the most
important factors to increase the profitability of customers with low frequency
and/or low spending pattern.
M.Miradi/1
PhD Researcher, Delft University of Technology
Responsibilities
July 2003 – December 2008
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Conducting an original and internationally highly qualitative PhD Research
Publication of papers
Writing research proposals
Writing the PhD dissertation
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24 International Publications (2004-2009) (see pages 4 and 5)
5 International Awards and Grants (2006-2009)
Achievements
1. Best Young European Researcher, Transportation Research Arena in “Future
vision”, Slovenia (2008)
2. Best session presentation award, IEEE World Congress in Computational
Intelligence, Canada (2006)
3. Student Travel Grant from European Soft Computing (ESC), Spain (2007)
4. Student Travel Grant from International Neural Network Society, USA, (2007)
5. Travel Grant from NWO, Netherlands (2006)
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Produced research proposal that secured € 175,000 funding from
Rijkswaterstaat (RWS/DWW) (2003-2004)
Invited talk for Gent University, Faculty of Computer Science and Applied
Mathematics, Gent, Belgium (2006)
Program committee member/referee/reviewer of 6 journals and conferences:
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Springer Annals Information Systems (AIS) (2008)
Journals of Materials in Civil Engineering (2007)
IEEE Conference on Soft Computing in Industrial Applications (2008)
International Conference in Data Mining (2006 and 2007)
International Joint Conference in Neural Network (2007)
IEEE World Congress in Computational Intelligence (2006)
 Successfully Passed 8 courses successfully and a number of workshops
 Presented 15 research papers in national and international conferences
Project summary
 Title: Knowledge Discovery and Pavement Performance – Intelligent Data Mining
 Supervisors: Prof.Molenaar(Civil) and Prof.Babuska(Artificial intelligence)
 Abstract: The project applies artificial intelligence (AI)-based techniques to
Dutch road pavement problems. These problems are related to porous asphalt
concrete (in Dutch: ZOAB), dense asphalt concrete, and the base layer under
the asphalt. The importance of the three mentioned areas for the Netherlands
lies in the facts that more than 70% of Dutch highways are covered with
porous asphalt and city roads are mainly covered with the dense asphalt.
Also, the overestimation of the quality of the base regularly causes crucial
problems for Dutch road contractors. Some of the AI-techniques which have
been used are artificial neural network, support vector machines, rough sets,
and decision trees. This study resulted in 20 intelligent models. To be certain
that the input variables of the models selected are the most influential ones,
eight different feature selection methods were applied. The methods used
were decision trees, genetic polynomial, artificial neural network, rough set
theory, correlation based variable selection with bidirectional and genetic
search, wrappers of neural network with genetic search, and relief ranking
filter. The models were developed in MATLAB. After Building a GUI for the
models, they turned into practical systems which are used by Dutch Ministry
of Transport and Water Management and road contractors. The project might
drastically cut road maintenance costs, which are about 180 million Euros
annually. Next to that, the analysis of the results could also lead to a better
asphalt mixture with a longer lifespan.
M.Miradi/2
Software Engineer, Shahd Iran
1998–2000
Responsibilities
Programming a new computer system using Visual C++ which would work directly with
the stock market and maintaining the existing system.
Achievements
Implemented a new computer system, programmed a new company website.
Director, Computer Institute Olympia
2000–2001
Responsibilities
I established a Computer Institute called Olympia, hired employees and teachers. The
courses were given in area of Programming languages such as C/C++/Visual
C++/Foxpro or graphic/animation softwares such as 3D studio and Corel Draw.
Achievements
Improved management skills, Implemented an animated TV commercial.
Educations
PhD in Artificial Intelligence, Delft University of Technology, Delft
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24 Publications
5 international awards/grants
PhD Dissertation of 308 pages
15 international presentations
International invitation talks
Reviewer of 6 conferences/journals
€ 175,000 funding from Dutch Ministry of Transport and Water Management
Successfully passed 8 courses.
MSc. in Computer Science, Vrije Universiteit, Amsterdam
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2002-2003
Average Mark: 8.18
Dutch Diploma, Ministrie van Onderwijs, Cultuur en Wetenschap
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2003-2008
2001-2002
Staatsexamen NT2/Program II
MEng. in Software Engineering, Mashhad AZAD University, Iran
1994-1998
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Award of Best Graduated Student (1998)
Certificate of Top Student (1996-1997)
Average Mark: 8.77
Director of Scientific Student Committee (1995-1998)
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Graduation project: Speech Recognition Software for Persian using Time Delay
Neural Network, Kohonen, and self organizing map. The system worked for a
dictionary of 2000 words obtained from 28 speakers.
Subjects: Differential Equations, Discrete Structures, Engineering Statistics,
Numerical Analysis, Advanced Programming, Logic Circuits, Engineering
Mathematics, Machine Languages, Computer Architecture, Algorithmic Design,
Information Storage and Retrieval, Computer Networks, Compiler Design,
Operating Systems, Programming Languages Design, Database Design,
Business Programming, Computer Graphics, Microprocessors, Neural Network.
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M.Miradi/3
High School Diploma in Mathematics, Khatami School, Iran
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1990-1994
Achievement: Best Student Award (1994)
Average Mark: 8.61
Some of the Study subjects: Mathematics, Algebra, Physics, Computer,
Chemistry, Biology, Economy, English, History, Persian, Arabic.
Other Experiences
ICT skills
Programming Languages:
- MATLAB
- SAS (Base, JMP, Enterprise Guide)
- C/C++/Visual C++, Java, Pascal
- Foxpro, SQL, SQL/PL
- GPSS, Assembly, Basic
- HTML
 Software knowledge:
- Weka, RapidMiner(Yale), Rosseta, Rose, Alyuda NeuroIntelligence, QNet
- Frontpage
- Tableau, Microsoft Excel, Microsoft Access, Microsoft Word
- Toad (Oracle)
- CorelDraw X4, 3D Studio, Adobe Premiere, Ulead Media Studio Pro
Certificates/Diplomas/Licences
 Certificate of SAS programming 1 & 2 (2010)
 Certificate of Advanced English, TU Language centre (2007-2008)
 Certificate of Common European Framework level for English: C1 (2007)
 Dutch Language Diploma (NT2/Program II, Staatsexamen) (2002)
 Certificate of “Managing Director of a Computer Institute”: Licence to establish
a Computer Institute (2000)
 Certificate of “Computer Teacher”: Licence for teaching computer skills (2000)
Languages
 Fluent (in writing and speaking): Dutch, English, Persian
 Reasonable (in writing and speaking): German
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Publications
Book/BookChapters
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Maryam Miradi, Andre A. A. Molenaar, Martin F. C. van de Ven (2009). Knowledge Discovery and Data
Mining Using Artificial Intelligence to Unravel Porous Asphalt Concrete in the Netherlands. Intelligent
and Soft Computing in Infrastructure Systems Engineering 2009. Pp. 107-176.
Miradi, M. (2009). Knowledge Discovery and Pavement Performance – Intelligent Data Mining, Pp. 308,
ISBN 978-90-8570-278-8, Wohrmann Print Service, Zutphen, The Netherlands.
Articles
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Miradi, M, Molenaar, AAA & Ven, MFC van de(2009). Back calculation procedure for the stiffness
modulus of cement treated base layers using computational intelligence based models. In s.n. (Ed.),
TRB 88th Annual Meeting, Compendium of Papers DVD (pp. 1-13). St. Louis, USA: MIRA Digital
Publishing.
Miradi, M, Molenaar, AAA, Ven, MFC van de & Molenaar, S. (2009). Backcalculation of the stiffnesses of
cement treated base courses using artificial intelligence. In E Tutumluer & IL Al-Qadi (Eds.), Bearing
Capacity of Roads, Railways and Airfields (pp. 633-642). Leiden, The Netherlands: CRC Press/Balkema.
Miradi, M, Molenaar, AAA & Ven, MFC van de (2009). Performance modelling of porous asphalt
concrete using artificial intelligence. Road materials and pavement design, 10, 263-280.
Miradi, M, & Molenaar, AAA (2008). Comprehensible artificial intelligence-based models for raveling of
porous asphalt. In s.n (Ed.), Samenvattingenbundel, Bijdragen CROW Infradagen 2008 (pp. 1-11).
Ede: CROW. (TUD)
Miradi, M (2007). Extraction of rules from artificial neural network for Dutch porous asphalt Concrete
pavement, In 2007 IEEE International Joint Conference in Neural Networks (pp. 4450-4456). Orlando,
USA:IEEE.
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Miradi, M & Molenaar, AAA (2007). Neural network models for porous asphalt (PA) lifespan. In TRB
2007 Annual Meeting (pp. 1-15). Washington, D.C.: Transportation Research Board.
Miradi, M & Molenaar, AAA (2006). Application of artificial neural network (ANN) to PA lifespan:
forecasting models. In 2006 IEEE World Congress on Computational Intelligence (pp. 7070-7076).
Vancouver, Canada: Omnipress.
Miradi, M (2006). Artificial neural network (ANN) for porous asphalt maintenance. In T Vogel, N
Mojsilovic, & P Marti (Eds.), Proceedings 6th International PhD Symposium in Civil Engineering (pp. 18). Zurich: Institute of Structural Engineering (IBK).
Miradi, M & Molenaar, AAA (2006). Artificial neural network (ANN) models for PA lifespan. In
Wegbouwkundige Werkdagen 2006 (pp. 1-12). Ede: CROW.
Molenaar, A.A.A. , Meerkerk, A.J.J. , Miradi, M. & Steen, T. van der (2006). Performance of porous
asphalt concrete. Journal of the association of asphalt paving technologists, 75, 1053-1094.
Miradi, M , & Molenaar, AAA (2005). Development of artificial neural network (ANN) models for
maintenance planning of porous asphalt wearing courses. 7-05-137-2. Delft: Delft University of
Technology.
Miradi, M (2005). ANN models for Dutch highway network. In HR Arabnia & R Joshua (Eds.),
Proceedings of the 2005 International Conference on Artificial Intelligence (pp. 208-214). Las Vegas,
USA: CSREA Press.
Miradi, M (2005). Prediction of raveling on Dutch motorways using ANN. In MP Clements, F Collopy, JG
de Gooijer, & BK Ray (Eds.), The International Journal of Forecasting (pp. 69-69). San Antonio,
Texas, USA: ISF.
Miradi, M (2004). Artificial neural network (ANN) models for prediction and analysis of ravelling
severity and material composition properties. In M. Mohammadian (Ed.), CIMCA 2004 (pp. 892-903),
Gold Coast, Australia.
Miradi, M (2004). Neural network models for analysis and prediction of raveling. In 2004 IEEE
Conference on Cybernetics and Intelligent Systems (pp. 1226-1231). Singapore: IEEE.
Miradi, M (2004). Development of artificial neural network (ANN) models for raveling. In BHV Topping
& CA Mota Soares (Eds.), Proceedings of The 4th Int.Conf. on Engineering Computational Technology
(pp. 1-15). Stirling, Scotland: Civil-Comp Press.
Miradi, M (2004). Development of intelligent models for ravelling using neural network. In W Thissen,
P Wieringa, M Pantic, & M Ludema (Eds.), 2004 IEEE International Conference on Systems, Man &
Cybernetics (pp. 3599-3606). Den Haag: Omnipress.
Miradi, M (2004). Prediction and analysis of raveling porous asphalt top layers using artificial neural
network (ANN). In HR Arabnia (Ed.), The 2004 Int. MultiConference in Computer Science & Computer
Engineering (pp. 1-8). s.l.: CSREA Press.
Miradi, M (2004). Predictions of raveling and analysis of climate influences using neural networks. In
Joost Walraven, Tom Scarpas & Johan Blaauwendraad, B.Snijder (Eds.), Proceedings of the 5th
Int.PhD Symp. in Civil Engineering (pp. 103-110). Leiden: A.A. Balkema Publishers.
Miradi, M (2004). Application of artificial neural network in prediction of raveling severity. In LS Smits,
A Hussain, & I Aleksander (Eds.), Brain Inspired Cognitive Systems 2004 (pp. 1-7). Stirling: University
of Stirling, Dept. Computing Science and Math..
Miradi, M (2004). Neural network models predict raveling and analyse material/construction
properties. In MH Hamza (Ed.), Proceedings of the 6th IASTED International Conference (pp. 346351). Honolulu, Hawaii, USA: ACTA Press.
Miradi, M (2004). Project ITC/ANN. In Dutch, Delft: Delft University of Technology.
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