Esther Ugwueke is a biomedical expert and PhD student at the University of Nebraska Medical Center, United States, where she studies and researches lung cancer using bioinformatics, artificial intelligence (AI), and deep-learning tools. Apart from academics, she is into volunteering and community endeavours. In this interview by Kingsley Alumona, she speaks about her research, work, and life in the US.
So far, how would you describe your postgraduate studies in Russia (MSc) and the United States (PhD in view), and how have they shaped your worldview, research, and career?
My postgraduate journey has truly shaped who I am, both as a researcher and as a person. Studying in two very different countries has given me a unique perspective on education, research, and global health challenges.
During my MSc in Russia, I focused on breast cancer detection using computer vision, where I developed a decision-support system to help identify microcalcifications in mammograms. That experience sharpened my technical skills in image analysis and AI.
Now, in my PhD studies in the US, I have taken things further by combining medical imaging with genomic data through deep learning, with a focus on lung cancer. This shift into bioinformatics and systems biology has broadened my view of what is possible when disciplines come together.
Overall, these international experiences have made me more adaptable, globally minded, and committed to using interdisciplinary research to solve real-world health problems.
Your master’s and PhD work revolve around cancer research. Why cancer? What is the motivation behind your interest in cancer studies?
I developed a strong interest in cancer research after observing how delayed diagnosis of breast lumps, often due to limited access to specialised imaging and interpretation, leads to late-stage detection, especially in low-resource settings. These delays reduce both survival chances and treatment options.
During my MSc, I focused on addressing this issue by developing a system to help doctors detect microcalcifications in mammograms, which shows an early indication of breast cancer. That experience deepened my commitment to using AI and bioinformatics to improve early diagnosis, particularly in underserved communities.
I am satisfied with the progress I have made so far. The results have been meaningful and encouraging, and they continue to drive my passion for creating practical, accessible tools that enhance early cancer detection and improve patient care.
For me, my journey has only just begun, as I want to dedicate more time to research collaboration, improving and developing new models, and translating research results into practical clinical tools that will benefit the most affected populations. I aim to contribute to enduring solutions that both detect cancer at an earlier stage and protect lives throughout various regions of the world, particularly in Africa.
You studied biomedical technology for your undergraduate studies in Nigeria. For PhD studies, you are now focusing on bioinformatics and systems biology in the Department of Genetics, Cell Biology, and Anatomy, University of Nebraska Medical Center, Omaha, United States. How do you combine biomedical technology and bioinformatics for your cancer research?
The combination of biomedical technology with bioinformatics has established a strong basis for my cancer research work. Through my biomedical technology education, I learned about medical imaging systems, which explains their ability to capture, process, and deliver clinical information. My practical experience allows me to grasp both the technical aspects of medical images and their clinical applications.
On the other hand, bioinformatics introduced me to a new analytical approach that enables the examination of intricate biological data, including gene expression profiles.
I am currently developing deep learning models that merge imaging data with genomic information in my research work. The main objective of my work is to enhance cancer detection methods and classification based on malignancy risk, which will lead to personalised treatment solutions. It is exciting to work at this intersection, where technology and biology come together to offer real hope for better outcomes.
What do you hope to achieve with your PhD work in cancer studies?
My PhD research is centred on lung cancer, specifically detecting and classifying malignant nodules from CT scans. Lung cancer remains the leading cause of cancer-related deaths globally, mainly because it is often diagnosed at a late stage. I am working on developing AI models that not only detect these nodules but also assess their risk of being cancerous.
What makes my work unique is the integration of deep learning with bioinformatics by using gene expression and transcriptomic data alongside imaging. By linking imaging features with molecular profiles, I hope to reduce diagnostic uncertainty and support more personalised treatment decisions for patients.
Ultimately, my goal is to build practical diagnostic systems that can deliver better outcomes, especially in resource-limited settings. I am passionate about bridging the gap between computational research and real-world clinical care, making these tools accessible to the people who need them most.
What is the latest innovation in lung cancer research, or cancer research in general, utilizing bioinformatics methods?
Although I am still in the early stage of my PhD, I am already exploring deep-learning frameworks to develop 3D convolutional neural networks for detecting lung nodules and classifying their malignancy. I currently work with large, publicly available imaging datasets and plan to integrate transcriptomic data to explore radiogenomic patterns, that is, how imaging features relate to molecular changes in cancer.
One of the most exciting advances in medical diagnostics right now is multimodal learning, where radiological images are combined with molecular data to build more comprehensive and accurate diagnostic tools. In this space, precision oncology is being driven by new methods like attention mechanisms and transformer architectures, which are incredibly powerful for capturing complex feature relationships. It is an exciting time to be doing this kind of work, and I am focused on contributing to solutions that can make a real impact in clinical care.
Cancer cases are seemingly rising in Nigeria. What do you think the government and the healthcare system should do to curb the rise and manage patients well?
Tackling the growing cancer burden in Nigeria calls for a well-rounded and strategic approach. We need to work on several fronts at once, starting with strong prevention efforts, early detection, accessible treatment, and investment in research.
Public health education should be a priority, along with integrating cancer awareness into primary care. National screening programmes, especially those using mobile units and AI-powered tools, can help reach underserved communities. We also need to expand health insurance coverage and train more medical specialists while making sure our diagnostic centres and cancer treatment facilities are fully equipped and accessible. Just as important is building our local research capacity by developing cancer registries, supporting homegrown studies, and forming international partnerships.
To truly reduce the cancer burden across the country, these efforts must be implemented systematically and fairly, ensuring that every Nigerian, no matter their location or income, has access to life-saving cancer care.
What kind of biomedical or bioinformatics cancer research do you want Nigerian universities and researchers to embark on to be on par with their US, India, Russia, and China counterparts? What unique things should they emulate from these countries for effective results and impact?
Nigerian universities need to take a more strategic approach to cancer research by focusing on areas that align with our local strengths while addressing global health challenges. We should prioritise applied cancer genomics, radiomics, and artificial intelligence as fields that can help us build and develop solutions that truly fit our context. Creating dedicated bioinformatics hubs and offering interdisciplinary training within our institutions will be key to driving this progress.
We can learn from countries that have made strong strides in this area. The US offers a great model with its focus on translational research and collaboration across disciplines. China’s investment in infrastructure and large-scale studies, India’s cost-effective innovations and growing bioinformatics capacity, and Russia’s emphasis on theoretical strength and international partnerships are all examples we can adopt.
To move forward, Nigerian researchers need strong support through public-private partnerships and global collaborations that give them access to advanced tools and training in cancer bioinformatics.
Apart from your academic and research work, what else do you do in Nebraska? Are you involved in any leadership, business, social, community, or teaching endeavour?
Beyond academics, I stay actively involved in leadership, community service, and personal development. I serve in nonprofit organisations focused on empowerment and development, and at UNMC, I am part of student associations that promote advocacy, inclusion, and health awareness.
Volunteering remains a big part of my life, as I am always looking for ways to give back. These experiences do not just complement my academic journey, but they shape who I am becoming. They help me grow personally, connect with others, and build the skills I will need to make a lasting impact both in science and in society.
What is your advice to Nigerians striving to study or live in the US? What two mistakes did you make in your early months in the US that you would advise them to avoid?
For Nigerians planning to study or live in the US, it is important to know that success takes more than just good grades. You need to be mentally, emotionally, and financially prepared. Before you arrive, take time to understand your school, the city you will live in, and the lifestyle.
Don’t wait ─ start connecting with people on LinkedIn and build a support system early. When you get here, be ready to learn and adjust. Things like healthcare, classroom expectations, and even everyday life can feel overwhelming at first. But with the right mindset, you will find your way.
One thing I have learned is that success here goes beyond academics. Building relationships, finding mentors, and getting involved in your community are just as important. And do not be afraid to ask for help because there are people and resources ready to support you. Stay resilient, stay open, and be willing to grow. That is how you thrive in the US.
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