About

Liang W. is a professional machine learning engineer with over 5 years of experience in deep learning, optimization, and statistical modeling. With a diverse academic background in statistics, operations research, electrical engineering, and physics, Liang has an in-depth knowledge of basic supervised and unsupervised learning algorithms, as well as state-of-the-art CNN, RNN, and GAN models. He also possesses extensive expertise in optimization algorithms and applied statistics techniques, along with a working knowledge of experimental design and hypothesis testing. As a seasoned software developer, Liang is proficient in Python, C++, and Java in a Linux environment. He also has a working knowledge of the big data stack, such as Hadoop and Spark. Liang is an excellent team worker with superb interpersonal skills, making him a valuable addition to any team. Currently, Liang is a Senior Machine Learning Engineer at meta, where he applies his expertise to develop and optimize machine learning models. Prior to this, he worked at Amazon as a Machine Learning Engineer and Research Scientist Intern, where he was responsible for developing and implementing machine learning algorithms and models. Liang's educational background includes a Ph.D. Candidate in Electrical Engineering from Washington University in St. Louis, as well as a Master's degree in Data Analytics and Statistics, Operations Research and Operations Management, and a Bachelor's degree in Economics from Peking University. He also holds a Bachelor of Engineering in Engineering Physics/Applied Physics from Tsinghua University. Liang's tech stack includes ML, Research Scientist, Supervised Learning, CNN, RNN, GAN, Deep Learning, Spark, Big Data, test, Hadoop, Software Engineer, Python, and Java. With over 8 years of relevant experience, Liang is a highly skilled machine learning engineer who is passionate about developing innovative solutions to complex problems.