Usman Mushtaq

- Software architect planning, modelling and development for recommendation system , churn prediction, anamoly detection, time series analysis and other predictive models (continuous integration and deployment). -  Developing fully automated pipelines for data extraction, data cleaning, feature engineering, statistical and methamtical modeling, predictive analysis and report generations for desired used caes in production using python, GIT, Cassandra, SQL, pyspark, R. - Training, testing, validation and optimization of machine learning models such as regression, classification and clustering for different used cases. - Deploying machine learning models in production using flask, Django, docker and AWS. - NLP using NLTK, Spacy and LDA /HLDA in Python for topics modelling and sentimentanalysis. - Time series analysis  and forecasting for financial and marketing data using statistical models and fbprophet.   - WritingETL pipelines in python for Google analytics, Instagram, Facebook and LinkedIn. - Developing dashboards withTableau. - Software documentation and project management in GitLab and plantuml.

-  Development, maintenance and release of R packages for internal usage -  Developing fully automated pipelines for data extraction, data cleaning, feature engineering, statistical and methamtical modeling, predictive analysis and report generations for desired used caes in production using SQL, R, rmd scripts, SVN and Infineon internal tools. - Training, Testing, Validation and Optimization of Machine Learning models such as regression and classification for different sensors. - Time series and yield analysis of sensors. -  Data Analysis and reports generations using Infineon internal tools

- Development, maintenance and release of fully automated pipelines for data wrangling, statistical and mathematical modeling, predictive analysis and finally reports generation of electronic components using SVN, Python, Autoit, LabVIEW, Batch scripts, SQL and Jenkins. - Software architect development and documentation using mmd/HTML and plantuml files - EDA and presenatation prepartion of sensors data using Jupyter Notebook, SQL. - Time series and yield analysis for different sensors.

Topic: Maximum power prediction of Li-ion batteries and analysis of primary batteries for portable devices -Developed fully autonomous lab test bench for characterization of different batteries to extract battery model for power management IC’s using LabVIEW, Python and Excel-VBA -Analysis of large data using Python to validate the battery maximum power prediction model.

-Developed and maintained visualization tool in Matlab. -Developed hardware models of power management components -Maintaining/updating existing HW models -Coding and debugging control logic/finite-state-machines in SystemC -Writing test benches for unit testing in SystemC -Writing test cases for system validation in C -Enhancing a LabView Tool for formal system test case definition

-Developed lab setup for micro energy harvesting from PVDF sensor in LabVIEW and Python. -Measurement data analysis and electrical modelling of PVDF sensor using Python. -Simulation of model predictive control of stationary battery system for photovoltaics’ in Matlab. -Analyzed the performance of stationary batteries with respect to depth of cycles, temperature and humidity.

-Supervised labs of Python, C++ and Statistical courses. -Delivering lab lectures, supervising lab projects, preparing exams and quizzes.

Master Thesis Title: Maximum Power Prediction of Li ion Battery Grade: Good (1,7/1)

Specialization in Robotics and Automation Grade: Good (3,5/4)