From Nigeria to the US: Nigerian physicist blending Physics and Machine Learning for global impact

Growing up in Nigeria, Oreoluwa Alade had limited access to research infrastructure and modern scientific tools — a contrast to the high-tech labs he now works in as a PhD in Physics candidate at North Dakota State University (NDSU).

“I had no idea what machine learning or high-performance computing was when I first moved to the US for my PhD,” says Alade. “I didn’t even know what microgels were — and that’s what my research is about.”

Alade is one of the 85,000 Nigerians studying abroad, with 20,029 in US universities during the 2023-24 academic year, making them the seventh-largest group of international students in the US.

There, universities welcome Nigerians to add diversity and enrich learning and research on campus. But for Nigerians, like Alade, an American degree is so much more: it’s a shot at a brighter future.

Alade, a PhD in Physics candidate, with his poster presentation at the American Physics Society (APS) Global Summit held in Anaheim, California, US. Source: Oreoluwa Alade

The biggest difference between a PhD in Physics in Nigeria vs the US

It was towards the end of his bachelor’s degree at the Federal University of Technology, Akure (FUTA), when Alade decided to pursue a PhD in Physics.

“I was completing my Bachelor of Technology in Physics with Electronics, and I was looking for PhD opportunities, and I stumbled upon Professor Alan Denton from the Department of Physics at North Dakota State University (NDSU),” he shares. 

“I remembered his name because he worked with another physics professor, the late Professor Neil Ashcroft, as I used the textbook he wrote during my undergraduate years for a solid-state physics course. Professor Denton researches computational and theoretical modelling of soft materials, and I became interested in it.”

Nestled in Fargo, North Dakota, NDSU is a public land-grant research university with over 11,000 students. The university is ranked 231st in national universities and 126th in top public schools in the US, according to US News and World Report. Its physics department holds a national ranking of 189.

NDSU’s Department of Physics is dedicated to preparing the next generation of innovators to advance science, engineering, and industry. With a strong emphasis on real-world problem-solving, the department equips students with the skills and knowledge to push the boundaries of science and technology.

This commitment is reflected in several research achievements, such as uncovering what makes a prominent paint glow dark for hours and discovering the possibility of enhancing the brightness and efficiency of blue and green light emitted from silicon carbide nanocrystals.

Alade took a chance and applied to NDSU for a PhD in Physics. A month or two after he sent in his application, he got an interview and then followed his acceptance with a full scholarship.

In 2022, he packed his things and moved halfway across the world to pursue his dreams.

“Studying in the US is like going to a different world,” he says. “If you signed up for a two-year programme in the US, then you’re doing a two-year programme, no more than that. If you’re getting a six-year PhD in Physics in the US, it’s strictly a six-year degree. Plus, the US government takes education seriously and supports it; Nigeria does not do that. They don’t provide support for students and even professors.”

Alade has participated in nine published physics journal articles during his time as a PhD in Physics candidate. Source: Oreoluwa Alade

The word “access” is a “very big word” for Alade.

“In the US, there’s more access to research tools, funding, and high-performance computing clusters. I even get to attend and present at prestigious physics conferences. I just returned from the American Physical Society Conference a week ago,” he shares.

Hailing from Nigeria, Alade was no stranger to limitations in learning. Apart from lacking funding and facilities, Nigerians lacked textbooks and well-trained, well-paid teachers.

During strikes by the Academic Staff Union of Universities (ASUU), Alade and many other students even had classes cancelled.

“My class was the most affected by the strikes, so I graduated in 2024, rather than 2020, my initial graduation year,” he shares.

Alade, a PhD in Physics candidate, with his poster presentation at the International Soft Matter Conference (ISMC) held in Raleigh, North Carolina, US. Source: Oreoluwa Alade

Microgel, machine learning, and internships in AI

For Alade, pursuing a PhD in Physics in the US is boundless and has opened new opportunities for him. 

Once unfamiliar concepts to him, he can now use machine learning, microgels, and high-performance computing as the core of his groundbreaking research at NDSU.

Microgels — tiny, soft hydrogel particles — are emerging as transformative materials with far-reaching applications in medicine, biotechnology, and environmental engineering. 

From drug delivery and tissue engineering to climate-responsive packaging and biosensors,  these materials are poised to reshape how we build, heal, and interact with the world. 

Alade’s work focuses on he physics underlying how microgels behave in external environments, and it’s done through advanced simulations and artificial intelligence to model their structural and phase behaviour.

“It’s important to understand how these particles adapt to external conditions like temperature or ph levels,” he explains. “That’s what makes the microgels so promising for real-world use — they’re smart, responsive, and heal themselves.”

A 2022 study found that microgels possess high mechanical performance, long-term sustainability, and convenient operation ability in emergency medicine. The microgel has rapid response properties that allow emergency medical personnel to help stop bleeding.

Alade’s research brings a unique computational physics lens to this field, helping scientists design better-performing microgels from the ground up.

Now, you may be wondering, how does microgel relate to physics? Shouldn’t it be chemistry or even biology?

Well, Alade uses machine learning and computer vision AI to conduct his research on microgels. 

Machine learning helps solve complex physics problems, so he trains the machines to learn patterns for stimulations to see if the microgel shrinks or swells. 

Alade applies machine learning tools such as Physics-Informed Neural Networks (PINNs) to simulate how microgels swell or compress under various conditions. 

These simulations not only accelerate physical discovery but also reduce the need for costly and time-intensive lab experiments.

Working in this interdisciplinary space has fueled his passion for artificial intelligence.

“My background in computational physics has been instrumental in preparing me for machine learning systems,” he says. “It’s what led to my current internship at one of the top firms in the US, where I’ll be working on generative AI and large language models.”

Alade’s ability to translate physical intuition into machine learning pipelines is rare and valuable. His work connects theoretical models with real-world applications — from medical devices to materials design to AI algorithms that learn from physical constraints.

While Alade was attending NDSU on a student visa, he managed to get a CPT (Curricular Practical Training) visa for his internship.

“All I needed was the right support from my university,” he says. “Once I had that, I pursued opportunities that aligned with my skills, and companies were eager to bring that value onboard.”

In a past project, Adale tackled one of the most pressing challenges in computer vision: how to enhance object detection in fisheye camera images, which are notoriously distorted and difficult to interpret.

Basically, to reduce the clip distortion caused by the nature of CCTV cameras (fish-eye lens).

His framework combined frequency-domain attention mechanisms with a dual aggregation transformer, significantly improving detection accuracy across surveillance datasets.

The simulations and patterns that he has to teach the machine tie it all back to physics and its systems. On top of that, physics and math equations are used in the mix.

This work has wide-reaching implications, from urban safety systems and autonomous vehicles to smart infrastructure. By addressing fisheye distortion using physics-based transformations, Alade built a bridge between real-world sensory data and AI reasoning frameworks.

“Physics and mathematics are the foundation of everything AI is achieving today,” Alade asserts. “From optimisation to probabilistic modelling, these concepts are rooted in the same equations that govern the physical universe. Without this, the world wouldn’t be able to move forward.”