Imagine a world where computers evolve, just like living organisms do in nature. Researchers at GVSU’S College of Computing are harnessing the power of evolution to solve complex problems automatically. Evolutionary computation, a rapidly growing field that mimics natural selection, is used to create smarter robots, more resilient software, improve financial decision-making, and analyze medical data. At the heart of this research are six faculty members making groundbreaking discoveries and mentoring students to become the next generation of innovators. With deep ties to the renowned BEACON Center at Michigan State University (MSU) and support from the National Science Foundation (NSF), GVSU faculty, alumni, and undergraduate researchers are shaping the future of computing. 

Evolutionary computation is not a single technology but a broad set of approaches that use evolution-inspired techniques to tackle real-world problems. In the College of Computing, faculty researchers apply these methods in different yet interconnected ways from optimizing software engineering and simulating digital evolution to advancing artificial intelligence and robotics. Together, their work demonstrates the interdisciplinary nature of evolutionary computation. 

Optimizing Software and Engineering Systems

Evolutionary computation is a way to make software and engineering systems smarter and more efficient. Dr. Byron DeVries, a leader in expanding this field at GVSU after being hired in 2017, focuses on applying these algorithms to software verification. By using evolutionary methods, he enhances the ability to detect flaws in software systems, helping those complex applications to operate as expected. His work is critical to reducing software errors and making technology more reliable. 

Similarly, Dr. Erik Fredericks applies genetic algorithms and novelty search techniques to optimize software systems. His research extends into generative art, demonstrating that evolutionary algorithms can do more than just improve software, they can foster creativity. His work in self-reconfiguring systems, automated testing, and adaptive software solutions highlights the problem-solving power of these methods.

Evolving Intelligence

Beyond software, evolutionary computation also plays a critical role in understanding and simulating artificial intelligence. Dr. Austin Ferguson, recently hired in the College of Computing in the Fall 2024 semester, explores digital evolution. This field uses computer-based simulations to study how evolution works. Inspired by his early research in evolving virtual creatures, Ferguson now uses evolutionary computation to study how digital organisms adapt and evolve over time. In collaboration with Kindschi Fellow and undergraduate researcher Marcos Sanson, Ferguson’s current research focuses on developing a baseline metric for evolvability, which is a challenge that has puzzled many evolutionary biologists for years. 

Meanwhile, Dr. Jared Moore, associate dean for undergraduate education and outreach, applies evolutionary algorithms to robotics so he can improve how machines learn and adapt. His research explores how these algorithms can optimize a robot’s neural network with specific emphasis in pre-training controllers for quadruped robots and many-objective optimization. By bridging evolutionary principles with artificial intelligence,
Moore’s work advances the potential of autonomous systems and adaptive robotics. 

Bridging Biology and Computing 

While some researchers use evolutionary computation to make technology more efficient, others use it to study biology. Dr. Alex Lalejini secured an NSF grant to study how symbiotic relationships influence species evolution. His work investigates how different interactions between species shape their evolutionary paths, providing insights into natural evolution and computational problem-solving. Lalejini’s research spans many applications from guiding robotic navigation to improving medical data analysis. As part of the NSF funding, he is mentoring several students. One of those students is part of the Kindschi Fellowship program, Grant Gordon. Lalejini’s goal is to help students become the next generation of scientists in computing and biology.

Dr. Jie Du was the first faculty member hired at GVSU in evolutionary computation back in 2013. She takes a distinct approach to evolutionary computation, incorporating specific domain knowledge to enhance algorithmic efficiency. Du’s research has applied this approach using artificial intelligence and machine learning to financial investments and health care. She created a financial ontology to guide the algorithm’s crossover and mutation processes. Additionally, she has utilized evolutionary computation models to help solve health care problems in which she discovers the root cause and determines the best solution. By incorporating real-world knowledge into the evolutionary process, Du’s research makes these algorithms more effective in practical applications.

Future of Evolutionary Computation 

Beyond their research, these faculty members are deeply committed to mentoring students, ensuring academic growth and professional confidence. As Lalejini puts it, he “loves research and science, but gets more joy out of working with students and seeing their confidence grow.” One of the many successful mentees is Max Foreback, a GVSU alumnus now pursuing a doctorate at MSU, the same institution and department where many of these faculty began their work in evolutionary computation. His research applies evolutionary computation to swarm robotics, where he explores how different controller representations enhance the adaptability and efficiency of robotic systems. Through hands-on research opportunities, conference experiences, and industry collaborations, GVSU faculty equip students with the expertise and confidence to contribute to the future of evolutionary computation.

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