Ian Kropp

Environmental and Computer Science Engineer

Meet Ian Kropp

I am an assistant professor of computer science at Ohio Northern University. My research covers both fields of my Ph.D.: Biosystems Engineering and Computer Science Engineering. I design algorithms that develop sustainable agricultural management practices, while simultaneously balancing environmental, social, and economic goals. My primary research interest is in merging mathematical optimization and human decision making through multi-objective optimization.


The natural world and computers have long been complimentary joys in my life. Growing up, I used my parents' Nikon D40 to catalog the neighborhood birds and refurbished old PCs to record my findings. We searched, edited, and printed maps for upcoming hikes and measured and recorded our distances with handheld pedometers. These early experiences taught me that computers are best used to better understand the natural world around us.

I completed my Bachelor's of Science in 2015 in Computer Science and Engineering from Ohio State University. During these years, I developed a passion for Linux, C, and Java. I worked full time in industry for 3 years as both a software developer and a front-end web developer. These years imparted in me practical strategies for developing web applications from the server through the front end – skills I subsequently used in my graduate research. I then went on to complete a dual Ph.D. in Biosystems Engineering and Computer Science Engineering.

Research: Multi-objective optimization and agriculture

With the goal to better utilize computers to understand the natural world, I joined the Decision Support and Informatics Lab at Michigan State University under Dr. Nejadhashemi as a Masters Candidate. During my Masters, I fell in love with multi-objective optimization (MO) and its applications in the natural world.

Why multi-objective optimization? To start, agricultural and environmental sciences are full of problems with multiple conflicting objectives: how to minimize irrigation usage while maximizing yield? How to maximize economic input while minimizing environmental degredation? Problems like these are difficult to solve, because they lack a single solution that can adequately resolve these opposing conflicts. By using multi-objective optimization algorithms, stakeholders can optimize these conflicting objectives, while interactively incorporating their individual preferences between the two objectives. This results in a hybrid human-machine system that leverages both human and machine brilliance.

Using this framework, my research focuses on improving agricultural management practices by integrating crop models to into multi-objective optimization frameworks. See my CV for details on research and my publications.