


Maryam Ashrafi


Courses

Engineering Statistics(SPRING_2018)
Aims:
Understand the key principles of statistics; Interpret and evaluate the kinds of data found in everyday life; Perform and interpret results from simple statistical estimation and analyses.
Syllabus:
 introducing the course objectives and method;Descriptive statistics: common techniques for presenting and summarizing data
 Descriptive statistics (2): common techniques for presenting and summarising data
 Patterns in Data Regression (1)
 Patterns in Data Regression (2)
 Collecting Data (1)
 Collecting Data (2)
 Estimation
 Point Estimation
 Interval Estimation (1)
 Interval Estimation (2)
 Statistical Testing (1)
 Statistical Testing (2)
 Analysis of variance (1)
 Analysis of variance
 Conclusion
 Pls check course outline on LMS
Text Book:
 Hogg, RV & Tanis, Probability and Statistical Inference, 8th Ed., PrenticeHall, 2010.

Evaluation, Forecasting & Transfer of Technology(SPRING_2018)
Aims:
Introduction and application of all technology management process including technology identification, assessment, selection and acquisition
Syllabus:
 Technology Acquisition (2):
 Technology Acquisition (3):
 Technology Strategy (1)
 Technology Strategy (2)
 Presentation of projects results
 Course Introduction, objectives and teaching methods;
 Technology Identification
 Technology Assessment (1)
 Technology Assessment (3)
 Technology Audit
 Technology Future Study (2)
 Technology Future Study (3)
 Technology Acquisition (1):
 Conclusion
 Technology Assessment (2)
 Technology Future Study (1)
Text Book:
 Dilek Cetindamar and Rob Phaal, (2015) Technology Management: Activities and Tools, Macmillan. Khalil T. M. (2000), Management of Technology: The Key to Competitiveness and Wealth Creation, McGraw Hill. Chiesa V., (2001), R&D Strategy & Organization, Imperial College Press. United Nations, Industrial Development Organization, (2005),UNIDO Technology Foresight Manual, Volume 1,2.

HealthCare Systems Engineering Internship(I) & (II)(SPRING_2018)
Aims:
Introduction to Health Systems
Syllabus:
 project determination
 Internship
 Final Report
Text Book:

Stochastic Processes(SPRING_2018)
Aims:
Introduction to a variety of random processes and their attributes; Random process Application and Modeling to Predict and analyze Phenomena.
Syllabus:
 Concepts and goals Introduction; Probability theory and related Theorems review;
 Random variables Discrete and continuous distributions
 Random processes Theorems and attributes
 The Poisson Process (1)
 The Poisson Process (2)
 The Poisson Process (3)
 Brownian motion (1)
 Brownian motion (2)
 Discrete Markov Chain (1)
 Discrete Markov Chain (2)
 Continuous Markov Chain (1)
 Continuous Markov Chain (2)
 Continuous Markov Chain (3)
 Continuous Markov Chain (4)
 Conclusion
Text Book:
 ? Ross, Sheldon, (2010) Introduction to Probability Models, Elsevier, Tenth Edition.? Grimmett, Geoffrey R., Stirzaker, David R, (2001) Probability and Random Processes, Oxford University Press.

Stochastic Processes(SPRING_2018)
Aims:
Introduction to a variety of random processes and their attributes; Random process Application and Modeling to Predict and analyze Phenomena.
Syllabus:
 Concepts and goals Introduction;Probability theory and related Theorems review;
 ? Random variables? Discrete and continuous distributions
 ? Random processes? Theorems and attributes
 ? The Poisson Process (1)
 ? The Poisson Process (2)
 ? The Poisson Process (3)
 Brownian motion (1)
 Brownian motion (2)
 Discrete Markov Chain (1)
 Discrete Markov Chain (2)
 ? Continuous Markov Chain (1)
 ? Continuous Markov Chain (2)
 ? Continuous Markov Chain (3)
 Presenting selected articles
 Conclusion
Text Book:
 ? Ross, Sheldon, (2010) Introduction to Probability Models, Elsevier, Tenth Edition.? Grimmett, Geoffrey R., Stirzaker, David R, (2001) Probability and Random Processes, Oxford University Press.

Engineering Statistics(FALL_2017)
Aims:
Understand the key principles of statistics; Interpret and evaluate the kinds of data found in everyday life; Perform and interpret results from simple statistical estimation and analyses.
Syllabus:
 introducing the course objectives and method;Descriptive statistics: common techniques for presenting and summarizing data
 Descriptive statistics (2): common techniques for presenting and summarising data
 Patterns in Data Regression (1)
 Patterns in Data Regression (2)
 Collecting Data (1)
 Collecting Data (2)
 Estimation
 Point Estimation
 Interval Estimation (1)
 Interval Estimation (2)
 Statistical Testing (1)
 Statistical Testing (2)
 Analysis of variance (1)
 Analysis of variance
 Conclusion
 Pls check course outline on LMS
Text Book:
 Hogg, RV & Tanis, Probability and Statistical Inference, 8th Ed., PrenticeHall, 2010.

Project Risk Management and Analysis(FALL_2017)
Aims:
Understanding the concepts and principles of risk, project risk and risk management; Introducing project risk identification methods and their application; Introducing project risk analysis methods and their application; Introducing project risk treatment and controlling methods.
Syllabus:
 ? Introduction of lessons and goals? Understanding concepts: uncertainties, risk sources, risk and project risk, project risk factors
 ? Risk and decision analysis? Decision making tools
 ? Project risk management and its processes? Project Risk Management Standards? Project risk management planning
 Project risk Identificationrisk breakdown structurerisk identification techniques
 Qualitative analysis of project risk and its techniques
 ? Quantitative analysis of project risk and its techniques
 Planning risk response
 Risk and contract types
 Risk controlling
 ? Introduction of some risk assessment techniques
Text Book:
 ? Identifying and Managing Project Risk (2009), Tom Kendrick, American Management Association; USA.? Risk Management for Project Managers: Concepts and Practices, (2014), ASME, 2 Park Avenue, New York, NY 10016, USA.? Project Management Institute (2009), Project Risk Management Practice Standard, Second Edition, Project Management Institute, Inc. USA.? Project Management Institute (2013), A Guide to the Project Management Body of Knowledge (PMBOK® Guide) —Fifth Edition, Project Management

Engineering Statistics(SPRING_2017)
Aims:
Understand the key principles of statistics; Interpret and evaluate the kinds of data found in everyday life; Perform and interpret results from simple statistical estimation and analyses.
Syllabus:
 introducing the course objectives and method;Descriptive statistics: common techniques for presenting and summarizing data
 Descriptive statistics (2): common techniques for presenting and summarising data
 Patterns in Data Regression (1)
 Patterns in Data Regression (2)
 Collecting Data (1)
 Collecting Data (2)
 Estimation
 Point Estimation
 Interval Estimation (1)
 Interval Estimation (2)
 Statistical Testing (1)
 Statistical Testing (2)
 Analysis of variance (1)
 Analysis of variance (2)
 Conclusion
 Pls check course outline on LMs
Text Book:
 Hogg, RV & Tanis, Probability and Statistical Inference, 8th Ed., PrenticeHall, 2010.

Evaluation, Forecasting & Transfer of Technology(SPRING_2017)
Aims:
Introduction and application of all technology management process including technology identification, assessment, selection and acquisition
Syllabus:
 Course Introduction, objectives and teaching methods;
 Technology Identification
 Technology Assessment (1)
 Technology Assessment (2)
 Technology Assessment (3)
 Technology Audit
 Technology Future Study (1)
 Technology Future Study (2)
 Technology Future Study (3)
 Technology Acquisition (1):
 Technology Acquisition (2):
 Technology Acquisition (3):
 Technology Strategy (1)
 Technology Strategy (2)
 Presentation of projects results
 Conclusion
Text Book:
 Dilek Cetindamar and Rob Phaal, (2015) Technology Management: Activities and Tools, Macmillan. Khalil T. M. (2000), Management of Technology: The Key to Competitiveness and Wealth Creation, McGraw Hill. Chiesa V., (2001), R&D Strategy & Organization, Imperial College Press. United Nations, Industrial Development Organization, (2005),UNIDO Technology Foresight Manual, Volume 1,2.

Project Risk Management and Analysis(SPRING_2017)
Aims:
1Understanding the concepts and principles of risk, project risk and risk management; 2 Methods of risk identification;3 Introduction of project risk analysis methods and their application; 4 methods of monitoring and responding to project risk
Syllabus:
 Introducing the course and obkectivesConcepts: uncertainty, risk resources, risk and project risk, project risk factors
 Project risk management processesProject risk management standards
 Project risk planningRisk identification and risk breakdown structure, project identification techniques (1)
 Risk identification and risk breakdown structure, project identification techniques (?)
 Qualitative risk analysis and its techniques(1)
 Qualitative risk analysis and its techniques(2)
 Reporting the progress of projectsQuantitative risk analysis and its techniques (1)
 Quantitative risk analysis and its techniques (2)
 Quantitative risk analysis and its techniques (3)
 Quantitative risk analysis and its techniques (4)
 Reporting the progress of projects
 Risk reaction process
 Risk control process
 Lesson Learned
 some project risk analysis software
 Conclusion
Text Book:
 Project Management Institute (2009), Project Risk Management Practice Standard, Second Edition, Project Management Institute, Inc. USA.Loosemore, M. Raftery, J. Reilly, C. Higgon, D. (2006), Risk Management in Projects —Second Edition, Taylor & Francis, NY

Stochastic Processes(SPRING_2017)
Aims:
1Understanding random processes types and their specifications; 2Using and modeling random processes to predict and analyze phenomena
Syllabus:
 Understanding the concepts and objectives;Reviewing probability and related theorems, discrete and continuous random variables and distributions.
 Random processesTheorems and properties
 Poisson process (1)
 Poisson process (2)
 Poisson process (3)
 Poisson process (4)
 Wiener Process (1)
 Wiener Process (2)
 Wiener Process (3)
 Discrete Markov chain (1)
 Discrete Markov chain (2)
 Discrete Markov chain (3)
 Continuous Markov Chain (1)
 Continuous Markov Chain (2)
 Continuous Markov Chain (3)
 Conclusion
Text Book:
 Ross, Sheldon, (2010) Introduction to Probability Models, Elsevier, Tenth Edition.
 Ross, Sheldon, (1970) Applied Probability Models with Optimization Applications, Dover Publications, INC., New York.

Engineering Statistics(FALL_2016)
Aims:
Introduction to Random variables, Probability distribution function, Statistical hypothesis testing and ...
Syllabus:
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Engineering Statistics and Probability(FALL_2016)
Aims:
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Stochastic Processes(FALL_2016)
Aims:
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Technology Transfer Agreements and Intellectual Property Rights(FALL_2016)
Aims:
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