Chen An Fan

I am Chen-An Fan, a newly graduated Master of IT (with specialisation in Artificial Intelligence) student from the University of Melbourne. I have 1.5 years of machine learning research and software development experience at McKinsey & Company. I worked as an intern cooperating with team members from different countries and was responsible for researching and developing machine learning models to automatically estimate the manufacturing cost of clients’ products.

Last December, I graduated with Distinction (first class honours) from the University of Melbourne. During my master’s degree, I have extensive experience in deep learning, statistical machine learning, natural language processing, and computer vision. I finished my master’s thesis under the supervision of Dr. Kris Ehinger. My master’s thesis topic is “Low-resolution scene context for rapid object detection”. I developed a vision transformer (ViT) model to replace convolutional neuron networks (CNNs) to better simulate the contextual priming mechanism in the human brain. I believe, my past experiences could demonstrate my understanding of different Machine Learning techniques and my independent fast learning capability.

I am a detail-oriented person with proficiency in python, C/C++, Java, Matlab, SQL. Moreover, I am familiar with most data processing libraries and deep learning libraries. I would greatly appreciate the opportunity to discuss more specifically how I could apply my background to meet your company’s needs. Moreover, I am ready to work as soon as possible.

Thank you for your consideration.