Tianshi Luan

Tianshi Luan has worked in the software engineering and customer solutions engineering fields since 2019, when they began working at Mindtech Global Limited. Prior to that, they were an Innovation and Application Engineer at SAIC Motor UK Technical Centre Limited, starting in 2018. Tianshi also worked as a Doctoral Researcher at the University of Birmingham from 2011-2018. During their research, they worked on developing micro mechanical resonant sensors with optical actuation and interrogation in the Micro-engineering and Nano-technology Research Group. Her research also included analytical modelling and FEA simulation using MatLab and COMSOL, as well as 3 years of cleanroom experience working with silicon, SOI wafers, SU-8 and PDMS. Additionally, they performed successful optimisation to reduce the sidewall roughness of thick photoresist structures and deep etched silicon structures, and micro structure characterisation.

Tianshi Luan obtained a Bachelor's degree in Mechanical Engineering from Huazhong University of Science and Technology between 2007 and 2009. Tianshi then continued their education at the University of Birmingham, where they obtained a Bachelor of Engineering (BEng) in Mechanical Engineering between 2009 and 2011, followed by a Doctor of Philosophy - PhD in Micro Opto-Mechanical Resonant Senor Development between 2012 and 2017. Additionally, they have obtained numerous certifications from LinkedIn and Coursera, including Google Cloud Platform Essential Training, Learning Docker, Learning Linux Command Line, Natural Language Processing in TensorFlow, Sequences, Time Series and Prediction, TensorFlow in Practice Specialization, Building and Deploying Deep Learning Applications with TensorFlow, Convolutional Neural Networks, Deep Learning Specialization, Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization, Sequence Models, Structuring Machine Learning Projects, Machine Learning, Neural Networks and Deep Learning, Convolutional Neural Networks in TensorFlow, and Introduction to TensorFlow for Artificial Intelligence, Machine Learning, and Deep Learning.