Concr

•  Designed and developed a recommender for targeted cancer treatment based on clinical, genetic, mutation and chemotherapy data
•  Developed novel machine-learning methods to model cancer survival
•  Investigated the impact of computer vision features on patient survival during chemo treatment

Computational Scientist

Heriot-Watt University

•  Developed a deep learning computer vision project that uses convolutional neural networks to identify fracture conductivity. This includes data gathering, augmentation, model building, training, cross-validation, and testing using various CNN architectures 
•  PhD thesis: “Development of computational modelling methods for solid and fluid mechanics in fractures”. 
•  Applied automatic machine learning for predicting the semi-analytical equation when it fails

PhD in Computational Science/Machine Learning

Baker Hughes, a GE company

•  Completed 4 mathematical modelling consulting projects for the clients, amounting to 0.6M USD in revenue for the company.
•  Applied statistical Bayesian approach using mathematical modelling that dealt with large volumes of data to understand and predict oilfield performance.

Reservoir Simulation Engineer 

Tethys Petroleum Ltd

• Completed 2 mathematical modelling projects using the Bayesian approach for optimization of the oilfield and production facilities

Reservoir Engineer 

I am a Scientist at Concr.co techbio company, located in Cambridge, UK, where my focus lies in the advancement and application of Machine Learning modelling methods to tackle challenges in the field of cancer research. My professional journey includes a background in the UK's oil & gas sector, where I specialized in mathematical modelling.

In addition, I offer academic expertise in research software development within Computational Physics and the application of Deep Learning to Computer Vision.

Taplio

Aidan Kubeyev, PhD's Linkedin Analytics

Aidan Kubeyev, PhD

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