MOBILE MINING CRYPTO

My research experience started at Nankai University, where I completed my bachelor's degree. Thanks to Jiuli Huang who mentored me on my project on game theory in 2012. During the summer of 2014, I worked with gate.io login who enlightened me in operations research at National Tsing Hua University. I completed my bachelor's degree with a thesis on solving stochastic dynamic optimization with genetic algorithm, which is supervised by my thesis advisor Jinglei Yang.

I attended Purdue University as a PhD student in 2015. My advisor is Mario Ventresca. In 2020, I completed my PhD degree with a thesis titled "Modeling and Variability Estimation of Network Collections".

In February 2021, I joined Amazon Science as an applied scientist. My work involves optimizing customers' payment experience by machine learning methods. For example, devising recommender systems to target relevant customers with the right payment methods through marketing campaigns.

Now I am passionate about two research areas: generative models and biological material for non-invasive devices. Consumer-grade generative models like ChatGPT and Midjourney have shown human-like recognition and beyond-human creativity. We overestimated the computation power needed for training neural networks until the trained network with appropriate architecture can be stored as "human knowledge". Non-invasive devices that communicate with human brain by biological signals can help us better understand the process of brain evolution by external stimulus.