Data Scientist | Machine Learning Engineer
Years of Experience
grenoble inp ense3, innoenergy, ku leuven, national university of science and technology
siemens, elichens, tetra pak, national university of sciences and technology nust
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2020 - Present
Machine Learning Engineer
• Spearhead all aspects of the development of novel methods for validating grid compliance tests of wind turbines through employment of machine learning and neural networks. • Lead the creation and development of pipelines to pre-process data and extract hidden features through utilization of new research methods. • Play a key role by carrying out the development of time series classification and regression models using libraries, such as sktime, scikit-learn, and TensorFlow. • Perform research into and develop state of the art techniques in the field of ML, and DL to ensure success. • Partner closely with software engineers, data scientists, data engineers, ML engineers, researchers, and designers across all operations.
2019 - 2020
• Conducted the automation of the control of HVAC Systems for ENSE3 building in Grenoble through utilization of expertise. • Drove the development of reinforcement learning model to identify optimum mass-flow rate through vents based on parameters including temperature, humidity, CO2 concentration, and more.
2017 - 2017
• Charged with operating on Tetra Pak’s machine data to provide support to the Technical Services team with predictive maintenance. • Leveraged computer science applications, modeling, statistics, analytics, and math to uncover insights in data sets. • Conducted data wrangling operations to perform the cleaning of data from a wide variety of sources.
2016 - 2016
national university of sciences and technology nust
• Served as an intern with Dr. Ahmed Salman at Nust and led the development of a MATLAB-based neural network application for face recognition. • Operated in a pivotal capacity by extending VGGFace Model developed at Oxford University for face verification by extracting and comparing facial features. • Demonstrated a track record of success with the project being sold for industrial application. • Piloted the development and implementation of new models to extract more value from collected data and information. • Employed machine learning and statistical modeling techniques to develop and examine algorithms to improve performance, quality, data management, and accuracy.
Machine Learning (ML)
Natural Language Processing (NLP)
2019 - 2020
grenoble inp ense3
Smart Grids and Buildings
2018 - 2020
Energy for Smart Cities
2018 - 2019
2014 - 2018
national university of science and technology
Bachelor of Engineering - BE