Osman M.


440 dollar
10 ans

Mon expérience

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Pacific Northwest National LaboratoryOctober 2019 - Présent

• Developed a machine learning framework for the rupture time prediction in high temperature alloy materials. Used variational autoencoder (VAE) to generate synthetic alloy samples from the latent space to devise a reinforcement learning scheme for novel materials discovery. 
• Developing a model for micro-structural feature generation from TEM image using image processing

• Developing an NLP framework for information extraction from raw unstructured scientific articles
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Stanford University, Menlo ParkSeptember 2017 - September 2019

• Created a high-throughput automated workflow to generate a massive adsorption energy database
• Developed a hybrid machine learning model by stacking a physics based model and data driven model to predict the adsorption energies on bimetallic alloy catalyst
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University of South CarolinaJanuary 2012 - January 2017

• Accomplished 3 projects under NSF and DOE grants, authored 9 peer reviewed articles (3 first author), and ed research at 5 prestigious chemical engineering conferences 
• Developed and validated a microkinetic model from first principles computation to elucidate the reaction kinetics occurring in solid/liquid interface

Mes compétences

TensorFlow, Tableau Software, Software Development, Seaborn, Scikit-Learn, Python, PostgreSQL, Pandas, NumPy, MySQL, MongoDB, Matplotlib, Matlab, Machine Learning, Keras, Image Processing, Fortran, C/C++, C++