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Location:
Toronto, ON, Canada
Posted:
March 08, 2019

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Resume:

Iraj Koohi

613-***-**** ac8py0@r.postjobfree.com Toronto, Ontario - Available to relocate

linkedin.com/in/linkedin.com/in/iraj-koohi-data-scientist/ Authorized to work in Canada and US without sponsorship Data Scientist and Machine Learning Engineer

PROFESSIONAL SUMMARY

• Offering 15 plus years of progressive experience in developing Data Science, Artificial Intelligence, Deep Learning, and Machine Learning algorithms to develop and conduct different applications in several industries

• Excellent understanding of all Supervised/Unsupervised Machine Learning, and Deep Learning techniques and algorithms, such as K-Nearest Neighbors (KNN), Naive Bayes, Support Vector Machines, (SVM) Decision Trees, Decision Forests, linear/nonlinear Regression models, Clustering, Convolutional Neural Networks (CNN), Recurrent Neural Networks (RNN), etc.

• Professional in developing and implementing Data Science, and Machine Learning-based projects by adopting and improving Data Science toolkits, such as Anaconda Enterprise 5, Python, Numpy, Pandas, Matplotlib, Scipy, Scikit- Learn, TensorFlow, Keras, etc.

• Excellent Understanding of Machine Learning, Deep Learning use cases, infrastructure, hardware, and tools

• Strong desire and motivation to learn new skills and apply to solve business problems

• Strong Leadership ability to coordinate and work collaboratively with others, and navigate complex decision making

• Strong problem-solving and communication skills with an emphasis on productivity AREA OF EXPERTISE & SKILLS

• Programming

• Anaconda Enterprise 5

• Python

• Numpy

• Pandas

• Matplotlib

• Scipy

• Scikit-Learn

• TensorFlow

• Keras

• CV2

• R

• SQL

• SAS

• OpenCV

• C++

• Matlab

• JavaScript

• Statistics

• Data Visualization

• Data Management.

• Data Intuition

• Software Engineering

• ML, DL, Model Deployment

• Multivariable Calculus

• Linear Algebra

• Data Science

• Data Analysis

• Machine Learning

• Deep Learning

• Artificial Intelligence

• Data Modeling

• Developing Algorithms

• Image Processing

• Computer Vision

• Optimization

• Communication

• Leadership

EXPERIENCE

Self Employed Toronto, ON. Canada

Data Scientist Sep. 2018 – present

• Utilizing aggregation of Machine Learning techniques for categorizing cardiovascular diseases

• Utilizing advanced Machine Learning and Deep Learning models to determine trustworthiness of the measured blood pressure by commercial non-invasive monitoring devices

• Researching on Data Science and Machine Learning latest improvements and applications University of Ottawa Ottawa, ON. Canada

Postdoctoral Data Scientist Apr. 2017 – Aug. 2018

• Developing data collection models to prepare reliable and accurate datasets

• Data mining and analyzing data to discover patterns in large datasets that can be utilized by Machine Learning projects

• Developing data models and intelligent Machine Learning algorithms best suited to ongoing research projects

• Assessing effectiveness of the developed data models

• Image processing face expressions of the hospitalized cardiovascular patients to extract features for data analysis and training purposes

• Developing and training Convolutional Neural Networks (CNN) to continuously analyze recorded face expression features and medicate the patients

• Utilizing Deep Learning techniques and different Regression models to predict blood pressure from features extracted from morphological information of recorded oscillometric waveforms

• Developing processes and tools to monitor performance and accuracy of the implemented models

• Conducting studies of related literature and research to support the design and implementation of projects and the development of reports, ensuring conceptual relevance, comprehensiveness, and accuracy of the developed models University of Ottawa Ottawa, ON. Canada

Research Assistant Jan. 2012 – Mar. 2017

• Enhancing data collection procedures to include information that is relevant for building analytic systems

• Developing custom data models and algorithms to apply to datasets

• Processing, cleansing, and verifying the integrity of data used for analysis

• Assessing the effectiveness and accuracy of new datasets and data gathering techniques

• Designing and developing Machine Learning models

• Selecting features, building and optimizing classifiers using Machine Learning techniques

• Developing internal tools to ease development of the projects

• Cooperating with different functional teams to implement Machine Learning models and analyze performance of the results

• Presenting information using advanced visualization techniques such as Matplotlib

• Performing ad-hoc analysis of the developed Machine Learning models, and presenting results to the project owners

• Developing collaborative links with core scientific personnel in related program areas to gain exposure to, and build knowledge on experimental/research activities and approaches, in order to subsequently improve conceptual development and implementation of existing programs

• Utilizing appropriate and current techniques/protocols in experimental laboratory management to ensure the integrity and security of the experimental process, comprehensive documentation, and replicability of experimental procedures

• Designing and organize databases along project frameworks and experimental research design that support overall research management, including the monitoring and evaluation of project inputs, actions, and outcomes, as well as the subsequent integration of these databases to other databanks

• Identifying areas of improvements within the research structure using Machine Learning, Artificial Intelligence, and integrated management approaches in pursuit of capacity building/strengthening and the preservation of scientific rigor in research studies

• Providing assistance with the preparation of project-related reports, manuscripts, and presentations

• Writing and publishing articles in peer-reviewed journals/digests that highlight findings from research and experimental activities ensuring consistency with the highest standards of academic publication and showcasing the program’s scientific leadership

Rail Transportation Industries Tehran, Iran

Data Scientist (as Systems Development Manager) Apr. 2006 – Jul. 2011

• Developing systems that are designed to improve workflow information through the different departments

• Designing visualization tools for the purpose of supporting operations, maintenance and technical services departments in their daily management of key functions

• Designing and developing models and Machine Learning algorithms to track predicted outcomes of projects

• Preparing reporting systems that are required by current operations, maintenance and technical services departments

• Developing multi-layer dashboards as references for a business intelligence platform that was used for a company leadership development

• Developing predictive models for revenue forecasting of projects for financial budgeting purposes

• Utilizing a wide range of data analysis and Machin Learning algorithms as methodologies for solving business problems

• Designing and implementing predictive models and cutting edge algorithms utilizing diverse sources of data to predict demand, risk and productivity of projects

• Utilizing predictive modeling to increase and optimize customer experiences, revenue generation, ad targeting and other business outcomes

• Utilizing Artificial Recurrent Networks (RNN) for document analysis of finished and ongoing projects to predict probability of investment on new construction projects Islamic Azad University Tehran, Iran

Data Scientist (as Research Scientist) Sep. 1998 – Jul. 2011

• Leading Data Science and Machine Learning based projects

• Collating data sources and building databases which can be accessed by end-users according to their intent

• Data mining using state-of-the-art methods

• Building models to address business problems

• Utilizing analytical applications to identify trends and relationships between different pieces of data, draw appropriate conclusions and translate analytical findings into risk management and marketing strategies that drive value

• Developing statistical models to forecast inventory and procurement cycles

• Performing both advanced qualitative and quantitative analysis of high volume data bases as a means to identify developing trends, patterns and correlations that could improve overall business performance EDUCATION University of Ottawa Ottawa, ON. Canada

Ph.D. Electrical & Computer Engineering (GPA %100) May 2013 – Mar. 2017 University of Ottawa Ottawa, ON. Canada

M.S. Electrical & Computer Engineering (GPA %94) Jan. 2012 – Apr. 2013 Mazandaran University of Science & Technology Babol, Iran M.S. Industrial Engineering, Systems Management (GPA %90) Sep. 1995 – Jul. 1997 K.N. Toosi University of Technology Tehran, Iran

B.S. Electronic Engineering (GPA %80) Feb. 1986 – Feb. 1990



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