RJ Nowling is an associate professor of Computer Science at the Milwaukee School of Engineering.

RJ earned a Bachelor’s in Computer Science and Math from Eckerd College. RJ focused on data analysis, processing, and storage since early on. During the summers, RJ worked with a research group at the University of Connecticut Health Center to develop tools for integrating and automating the analysis of NMR spectroscopy data. RJ went on to earn a Ph.D. in Computer Science & Engineering from the University of Notre Dame. For the first four years of his Ph.D., RJ worked with a research group developing physical models, numerical algorithms, and software for computational chemistry. RJ later changed labs and finished his Ph.D. with a focus on the application of data science to genomics.

After his Ph.D., RJ expanded on his academic training with four years at leading tech companies. From May 2014 to August 2016, RJ was a software engineer at Red Hat, Inc. with a focus on open-source software for scalable data processing. RJ was part of a group evaluating potential analytics stack using open-source software such as Apache Spark and the Gluster distributed file system. He was a contributor to Apache Bigtop and Apache Spark projects and gave talks at ApacheCon Big Data 2015 and Spark Summit East 2016.

After two years at Red Hat, RJ became a data science engineer at the online advertising company AdRoll. He was part of a team that developed and maintained a recommendation system to expose users to new companies. Through this work, RJ gained experience with ML production systems and what would later come to be called MLOps.

RJ joined the faculty of MSOE in Fall 2018. MSOE is a primarily-undergraduate polytechnic offering students a challenging academic environment with small classes that emphasize hands-on learning and high faculy-student engagement. Somewhat uniquely, Computer Science majors at MSOE are require to take courses in data science and machine learning. RJ has been intimately involved in designing and teaching courses in data science, machine learning, and algorithms, which provide opportunities to bring his research and industry experience into the classroom.

Shortly after joining MSOE, RJ established a research group that applies machine learning and data science to advance our understanding of genomics. The group received funding from a NSF CISE CRII grant and startup funds from MSOE. Since Fall 2018, more than 15 undergraduate students have participated in the group. Through collaborations with faculty at R1 universities, students are exposed to fields outside of computer science, the nature of interdisciplinary work, and research-intensive environments. Four of the students have since pursued graduate studies.

RJ is part of a team that recently established a Master’s and graduate certificate programs in machine learning. RJ recently expanded the focus of his research activities to data-intensive systems, especially those involving machine learning models. This shift was driven by the recognition that students need to know how to put ML models into production, not just develop them offline. To meet this need, RJ developed and regularly teaches courses such as ML Production Systems, Recommendation Systems, and Distributed Storage Systems. In Spring 2023, RJ established the MSOE Data-Intensive Systems Education (DISE) Project. The MSOE DISE project aims to encourage profileration of similar courses at other universities by providing course materials and example system implementations under an open-source license.