A look at Halil Bisgin’s published research shows an eclectic selection of topics: an analysis of the structure of ISIS propaganda, detecting automated activity on Twitter, predicting fetal development diseases, drug repositioning, assessing the performance of cancer panels, and identifying food-contaminating beetles to name a few.

His work spans such a wide number of fields, from bioinformatics to social computing, that one may be left wondering what his particular area of expertise actually is.

In fact, Bisgin is an assistant professor of computer science in UM-Flint’s College of Arts & Sciences, with expertise in data mining and machine learning.

And while, for many of us, the term “computer science” conjures up images of building computer programs and smartphone apps, Bisgin’s interdisciplinary approach has allowed him to make advances in numerous fields outside the typical realm of computer science.

Halil Bisgin has used his artificial intelligence expertise in collaborations with the U.S. Food and Drug Administration and the Beaumont Health System. (Photo by UM-Flint)
Halil Bisgin has used his artificial intelligence expertise in collaborations with the U.S. Food and Drug Administration and the Beaumont Health System. (Photo by UM-Flint)

Two of his most recent collaborations have been with the U.S. Food and Drug Administration and Beaumont Health System.

Insect pests can contaminate as much as 10 percent of the total food produced in the United States. Identifying the species involved usually requires a food inspection analyst with years of training to determine the microscopic differences.

Bisgin worked with the FDA to create an artificial-intelligence system that automatically detects insect contaminants from images. The research project focused on 15 of the most common beetle species detected in food inspections.

“We cropped the images into smaller pieces because, with processed food, the whole beetle will probably not remain intact,” Bisgin said. “I also used the Great Lakes supercomputer at U-M Ann Arbor to train my model because this is a very computationally demanding process.”

With an overall accuracy rating of 80 percent, Bisgin’s program can quickly identify the species contaminating stored foods, which in turn informs possible causes and solutions to the infestation.

In a collaboration with the Beaumont Health System, Bisgin used machine learning to identify specific biomarkers associated with a condition known as Intrauterine Growth Restriction.

With IUGR, developing babies don’t grow to normal weight during pregnancy. A common defining feature of the condition is a birth rate lower than the 10th percentile, controlling for factors such as gender and ethnicity. Still, it is important to distinguish IUGR from other causes of small stature to avoid unnecessary medical testing and interventions during pregnancy.

Beaumont research scientist Ali Yilmaz would share files with hundreds of metabolic data points from blood samples — both from pregnant women with IUGR and without the condition.

From those hundreds of data points, Bisgin’s approach can narrow it down to a handful of potential biomarkers associated with the condition. Medical researchers can then spend their time and resources more effectively.

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“It would take quite some time to figure out what is happening without an efficient method. (Bisgin) was a huge help,” Yilmaz said. “These are proof-of-concept studies, and hopefully it will lead us to working with thousands of samples and identifying countless potential biomarkers for disease.”

The innovative manner in which Bisgin has applied his computer science expertise in solving real-world issues exemplifies the creative mindset embraced by both students and faculty in UM-Flint’s College of Arts & Sciences.

“Dr. Bisgin has shown incredible flexibility in utilizing his skillset to solve complex issues across disciplines,” said Susan Gano-Phillips, dean of CAS. “This work highlights the value of creativity in solving new problems, something we emphasize every day in the college and across the UM-Flint campus.”

Q&A

What memorable moment in the workplace stands out?

I usually observe the back row when I’m teaching because mostly the shy students or the students who feel less confident tend to sit there in my experience. In one of these classes, I noticed a student leaving early with a puzzled and desperate face. I knew that the student was not really doing good, but that moment made me feel that somebody was going to get lost in the course, and eventually fail. I reached out to the student and asked about this. The answer was not surprising. I offered my help and the student started to come to my office hours and finally passed the course with a good grade.

What can’t you live without?

Data.

Name your favorite spot on campus.

The area just off East Kearsley Street, between Murchie Science Building and French Hall, where I sometimes sit on one of these concrete benches and relax, especially in spring.

What inspires you?

Transferability of knowledge between different research domains after taking roles in several interdisciplinary projects which helps me think outside the box.

What are you currently reading?

“Limitless Mind: Learn, Lead, and Live Without Barriers” by Dr. Jo Boaler. The book shed light on a common misbelief that our potential is limited, which is mostly due to our failures. She, instead, shows that we can transform our potential with a “growth mindset” as opposed to a fixed mindset. As I read the book, I realize that it’s well aligned with my teaching philosophy where I also believe every student has the potential to learn, but it’s the instructor who needs to guide.

Who had the greatest influence on your career path?

Dr. Weida Tong who was my both Ph.D. co-adviser and postdoctoral supervisor from whom I learned a lot.

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