As a University of Delaware graduate student working toward her MBA and Ph.D. in biology, Malek Elsayyid certainly already had enough on her academic plate.
But when she received an email fromAndrea Hartman, the Lerner College’s graduate business academic program manager describing a new Introduction to AI course being offered in the Alfred Lerner College of Business and Economics, she was intrigued.
“I knew AI was becoming a very hot topic at the time, and I didn’t really know anything about it, and I’m always interested in learning new things,” she said. “I didn’t have a goal going into it, but just wanted to get a background on something that is clearly going to revolutionize the way that we work and have an impact on all different types of sectors.”
The Introduction to AI class, which Elsayyid took last spring, was taught by Professor of MIS Harry Wang and showed all the different ways the students could use AI. One that stood out was having them create a song from scratch.
“It wasn’t just making the lyrics using ChatGPT, but also then inputting them into another AI site that would make the vocals and musical elements to create a full two-minute song,” she said. “You could even tell it what types of vibes you wanted the song to have.
Then we shared all our songs, and everybody was having so much fun with it. I don’t think I’ve ever been in a class where people were genuinely so interested in the material, having fun with it and pushing the limits as to what they could do.”
Due to the success of the class and the students’ interest in learning more about AI and its different applications, the Lerner College introduced two other classes: AI and Data Visualization and AI in Business Analytics. Completing all three would earn students the graduate certificate.
In the data visualization class, taught by Assistant Professor of Economics Kathryn Bender, Elsayyid learned about the importance of ensuring her data sets were clean before generating different types of graphs. The business analytics class, taught by Ming Zhao forced her to think about how to train AI and the main difference between using AI versus regular regression models.
Elsayyid took both classes during the fall, and in December became the first UD student to complete the Generative AI for Business graduate certificate.
Elsayyid is currently working on a research paper for her doctoral program on worms and characterizing a type of protein and how it impacts intracellular signaling. She was able to immediately put her AI knowledge to use.
“I’m working with a data set I collected back in 2022, and for the longest time, I’ve been putting off analyzing those images because the technology was not there yet,” she said. “It would have taken way too much time to even analyze a single image, because it would have to be done manually. So when an AI tool came out, it made it possible to analyze those images much faster.”
When Elsayyid and her partners want to label specific worm cells, they use a piece of DNA that normally activates a molecule found only in those cells. Instead of producing that molecule, they modify the DNA to turn on a fluorescent green protein. This makes only the target cells glow green, allowing the researchers to easily identify and study them among all the other cells in the worm.
“With this AI tool, I’m able to train it to know what fluorescent signals are real and not real, so it can more accurately label the cells I’m looking at. Then I can just look at protein localization within those cells,” she explained.
Elsayyid needs to be very accurate with where the cell starts and ends, to determine whether the protein is actually inside or outside the cell.
“That has been a huge breakthrough for this data,” she said. “Once we publish this paper, I think we’re going to be the first people to use this tool for this research topic. The data on this type of imaging hasn’t been done before.”
Although Elsayyid is using worms as a model, the process happens in humans as well, so there is a lot of interest in using this intracellular signaling mechanism as a way for diagnosing diseases early on.
“We have these signals in our bloodstream, and hopefully in the future you could take a blood sample, analyze the proteins that are in it, and see if there are any tumor-derived proteins being shipped across your body,” she said.
“That way you could have an early detection system for diseases such as cancer, without using a biopsy. That’s a big picture, but in our lab we do basic science that could hopefully lead to these big breakthroughs in diagnostics and medicine.”
Once she is done with her analysis, Elsayyid will start to write her thesis which will be submitted by end of May or early June. She will then hope to obtain a job where she can use her expertise in both AI and biology research.
“I’ve been going through a lot of job applications now, and a lot of them are really looking for AI (experience.) I’m unsure how much they really expect out of a biologist, but the fact that I can say on my resume that I have a certificate in AI on top of my biology Ph.D. definitely sets me apart,” she said.
“Having that basic understanding of how AI works just gives me that one leg up.”
Elsayyid noted that she recently attended a presentation in the FinTech Innovation Hub featuring representatives from a local company that is using AI to help develop antibodies against different targets. A computer scientist and a biologist shared the stage, and admitted they didn’t know much about the other’s field.
“It seems like there aren’t enough people who are at the interface of computer science and biology and able to facilitate communication between the two. It really shows the importance of having people who are involved in AI. I think there is a huge future using AI in biology or chemistry, not just business or computer science,” Elsayyid said.
She hopes to find a position to bridge the gap between the two fields.
“I would like to be able to advise computer scientists on determining the important aspects to consider for a biological question and using AI to answer that,” she said.
“I think I’m a good communicator, so I think my ideal job would be to communicate a complex biological concept to someone who is not in that field, and be able to develop tools to make it easier to solve those problems. There is so much knowledge and expertise out there, and if we can break up the silos a little more and get more cross collaboration, I feel like we could accomplish so much.”