Maximilian-Joël Schleich
Postdoctoral Scholar in Computer Science
University of Washington
I am a Postdoctoral Scholar in the Paul G. Allen School of Computer Science & Engineering at the University of Washington, where I work with Prof. Dan Suciu. I received my PhD in Computer Science from the University of Oxford, where I was a member of the FDB research group led by Prof. Dan Olteanu. My research lies at the interface of databases and machine learning. In particular, I investigate how the learning of models can be improved by exploiting the structure and semantics of the underlying database.
Before the PhD, I received a MSc in Computer Science from Oxford and a BSc in Economics and Computational Mathematics from The American University of Paris.
In my research, I aim to unify database systems and analytics engines into one highly optimised database-centric analytics engine, which can efficiently compute machine learning models over large-scale relational databases. Such a system can exploit the relational structure of the database to (1) avoid redundancy in data representation and computation, and (2) learn potentially more accurate machine learning models with low runtime complexity guarantees. For real applications in the retail and advertisement domains, the system can learn a host of machine learning models orders of magnitude faster than state-of-the-art competitors like TensorFlow and scikit-learn. For more information, please check out the publications listed below or get in touch.