Michael Stewart, also known as "Stu," is a machine learning and deep learning expert currently working as a Staff Research Engineer at Opendoor. With a magna cum laude degree in B.A. from Pomona College, he declined a National Science Foundation Graduate Research Fellowship award to pursue private sector interests. With his experience and expertise, he regularly gives workshops or invited talks on deep learning and optimization at conferences including PyGotham, PyBay, and ODSC East. His impressive accomplishments include two particularly noteworthy talks, including "Deep Learn You a Neural Net for Great Good!" and "Gradient Descent, Demystified." Prior to his current role at Opendoor, he was a Software Engineer - Data at Uber and a Researcher at the Federal Reserve Bank of New York, Research and Statistics Function. Moreover, his skills and interests also cover various data and modeling tools such as Scala, Spark, Hadoop/Hive, Presto, MemSQL, Pandas+Dask, Flink, Postgres, Redis, PyTorch, Jax, Tensorflow, Keras, and more.