Breaking the mould in Biomedical Engineering: a conversation with Eva Martínez Luque

At the Bankinter Innovation Foundation, we are very proud of the alumni who have been trained in our Akademia programme.

The uniqueness of the program lies in its design and execution: it ranges from a demanding student selection process to a practical and avant-garde approach to the content of the classes, complemented by the excellence of the teachers. This combination results in students who are enthusiastic about innovation, ready to bring new ideas and creative solutions in their respective fields.

On this occasion, we interviewed Eva Martínez Luque, a former student of Akademia, biomedical engineer and passionate about the human brain.

Eva has an impressive career that extends from the Carlos III University of Madrid to the prestigious Ph.D. she is currently pursuing in Biomedical Engineering arising from the collaboration between the Georgia Institute of Technology and Emory University. Their research, which sits at the intersection of neuroimaging and machine learning, promises to break new ground in the detection and treatment of neuropsychiatric disorders.

Today, we dive into his story, his motivations, and what he expects from the future.

Below, we reproduce the interview we had with Eva:

What initially prompted you to choose Biomedical Engineering as your field of study?

From a very young age, I always had a natural inclination towards various academic areas. I was fascinated by both mathematics and biology, and I considered myself competent in these disciplines. This versatility presented me with a dilemma when deciding which career to study. On the one hand, I was attracted to the idea of studying mathematics, but then I wondered what to do with my interest in biology. How could I integrate it? On the other hand, if you were going for biology, how would you incorporate the engineering aspect?

The choice was far from simple at the time, as each option seemed to require him to give up some other interest. However, biomedical engineering emerged as the ideal career that allowed me to combine all these passions without having to sacrifice any. What attracted me most to this field was its direct applicability to the clinical world and its ability to have a tangible impact in real life. It was the perfect opportunity to apply all my interests in a practical and meaningful way. I chose this path at the age of 17, driven by the idea of being able to merge my skills and passions. Although now, with more experience and perspective, my reasons for choosing this field might be different, back then it was a decision motivated by the possibility of making fewer resignations and more integrations into my education and future professional career.

What was the defining moment when you knew you wanted to focus on the intersection of neuroimaging and machine learning?

Since my adolescence, I have always had a particular fascination with the brain. It seemed incredible to me how an organ governed by chemistry and biology is capable of molding our personality and emotions. Although I was initially torn between studying biomedical engineering or psychology, I knew that, in one way or another, my path would be linked to the study of the brain.

During my training in Biomedical Engineering, I discovered that I had three major areas of specialization to choose from: tissue regeneration, medical devices, and medical imaging. Of these, the medical image immediately caught my interest. It was in this field that I began to see the wide panorama of possibilities, especially when artificial intelligence began to be part of my curriculum. Artificial intelligence was already revolutionizing multiple sectors, and its integration into medicine, particularly neuroimaging, seemed essential to me. The volume and complexity of data handled in neuroimaging are enormous, making them ideal for the application of machine learning algorithms. I saw the limitless potential that the combination of neuroimaging and artificial intelligence could have, and I knew that there lay the future of the field. At the time, my decision was clear and much more mature than the concerns I had at 17. It was evident that my career should focus on exploring this intersection, where neuroscience converges to unravel the mysteries of the human mind.

As an Akademia alumna, what memories do you have of your experience in the program and how do you think it helped prepare you for your current career?

My experience in the Akademia program was very enriching and marked a turning point in my life. I remember that, after finishing high school, the next thing on my path was university. There, at the age of 20, I was completely immersed in academic demands: preparing finals, completing laboratories and fulfilling a series of endless tasks. It was as if I was wearing earmuffs, focused only on what was right in front of me. In this context, Akademia was presented as a fascinating bridge between student life and the real world, the one in which he would have to play an active role in technological advances. What I valued most was how the program treated us as future leaders in the sector. It was a parenthesis in my routine, an opportunity to take off my earmuffs and see the great expectations that society placed on us. We were expected to contribute innovative ideas and apply our knowledge to achieve great things.

Also, the emphasis on innovation was something I really appreciated. They constantly encouraged us to think differently, to step out of our comfort zone, and to use what we knew to try to do great things. This insight was instrumental and helped prepare me for a professional life full of challenges and opportunities.

You’ve mentioned your passion for the brain and your commitment to mitigating neuropsychiatric disorders. Could you share an experience or project in which you have participated that has reinforced this passion?

Yes, I certainly have a very strong personal connection to brain study, especially from a significant experience I had. Before I decided to undertake my PhD, I was playing rugby and suffered a concussion due to a severe blow to the head, from which it took me two months to recover. At the time, I was taking a course that delved into post-trauma brain recovery, which coincided with my own recovery process. This crossover between my personal experience and academic learning about the brain’s recovery potential really fueled my passion for this field from a very intimate and scientific point of view. In addition, I have always been very aware of the importance of mental health due to my own challenges with anxiety. During the COVID-19 pandemic, the situation worsened globally, with an alarming increase in suicide rates. This was a wake-up call about another silent pandemic we face in terms of mental health and neuropsychiatric disorders.

On the professional side, after the pandemic, I had the opportunity to intern at Georgia Tech, where I worked on a research project. This study focused on the neurological consequences of traumatic brain injuries in a context of chronic stress and an unhealthy diet. This experience was decisive and motivated me to start my PhD.

Currently, I am involved in a fascinating project related to HIV and neuroimaging. Despite the treatments available, there is no cure for HIV, and one of the big challenges is that the virus can cross the blood-brain barrier and form reservoirs in the brain that current treatments are not effective against. This results in chronic inflammation and neuronal damage which, in many cases, is associated with cognitive deficits. Neuroimaging based on magnetic resonance imaging plays a very important role because it is a non-invasive technique that allows us to evaluate various structural, functional and metabolic markers whose alterations inform us about brain damage.

We are currently in the midst of a phase two clinical trial (meaning the drug has already passed safety tests and we are now evaluating its efficacy), testing a drug that could potentially restore neuronal damage and eliminate the virus in the brain. We use neuroimaging not only to assess brain damage caused by the virus, but also to monitor treatment effects. This is the first time that this compound – studied for two decades in animal and cell models – has been used in people with HIV. We are working with 64 patients and, depending on how these trials evolve, the next step would be to conduct large-scale trials to evaluate other aspects and possible side effects of the treatment. We have already started with brain MRIs of several patients, which means that the project is progressing well and is in full development. The prospect of contributing to a solution that could address one of the major obstacles to HIV cure and alleviate the cognitive deficits that affect so many people is incredibly exciting and rewarding to me.

In terms of your current research, could you explain how the combination of neuroimaging and machine learning can transform the diagnosis and treatment of mental disorders?

The combination of neuroimaging and machine learning in my current research has transformative potential for the diagnosis and treatment of mental disorders, addressing a fundamental challenge in contemporary psychiatry. Traditionally, the diagnosis of mental disorders is based on the clinical observation of symptoms, following criteria established in diagnostic manuals dating back decades. This approach, while useful, can be subjective and often comes too late, when symptoms are already present and possibly intertwined with other disorders due to the complexity of the brain.

What we propose with the use of neuroimaging is a paradigmatic shift: non-invasive access to multiple features of the brain. For example, in my work with HIV protocols, we use the scanner to examine brain structure, metabolism, the functionality of various areas, water diffusion, and blood flow. This information is profuse and complex, ideal for analysis using machine learning techniques. The real innovation here lies in machine learning’s ability to handle and process a massive volume of data and complex variables. The idea is that we can synthesize all this data to identify objective biological markers, which do not depend exclusively on the manifestation of symptoms. These markers could allow us to differentiate between a brain at risk of developing a mental disorder and a healthy one, long before symptoms manifest. This approach promises, on the one hand, an earlier and more accurate diagnosis, and on the other, the personalization of treatment, adjusted to individual neurobiological characteristics, opening a new era in mental health management.

What do you see as the biggest challenges when applying advanced technologies, such as machine learning, in biomedical research, and how are you addressing them?

There are many challenges. There are three main challenges that I consider fundamental in this area:

First, the challenge of the “black box” in artificial intelligence. In a neural network, for example, we enter data, a series of internal processes happen, and finally, we get a result. However, for the medical community, simply knowing that “things happen” is not enough. We need the processes to be interpretable. It is crucial that we understand how artificial intelligence reaches its conclusions, so that these models can be applied clinically and gain the public’s trust. Currently, an important part of our work is focused on developing models that are not only accurate, but also understandable and logical.

The second great challenge is the creation of models that are generalizable. In medicine, factors such as age, gender, race, or ethnicity can significantly influence outcomes, and a model that works for one group may not be effective for everyone. Historically, medicine has tended to focus on studies conducted predominantly on white men, extrapolating those results to the rest of the population, which is a narrow and often inaccurate approach. We must avoid perpetuating these practices and work to include a wider diversity of data in our studies.

Finally, we face the problem of data collection. For a machine learning model to be effective and not overfit—that is, to fit too closely into a small, unrepresentative set of data—we need access to large volumes of information. However, obtaining this data is a considerable challenge, especially for smaller research centers with limited resources. Funding, available technology, and the availability of volunteers are just some of the barriers we must overcome to build robust and representative databases that allow the extrapolation of our models to the entire population.

Looking ahead, how do you hope your work will contribute to the field of biomedical engineering, and what impact do you hope to have on society with respect to neuropsychiatric disorders?

When we visit the doctor, multiple standard measurements are made such as weight and height, and we are classified into health ranges based on those parameters. However, something that has yet to be similarly established is a system for measuring brain health.

I am very excited because I will soon start a project that seeks to address precisely this. My goal is to use artificial intelligence to analyze neuroimaging data, which is incredibly rich in information, but not yet fully exploited. Through this analysis, I hope to develop quantifiable indicators, similar to height and weight charts, that will allow us to assess brain health.

This effort will advance our understanding of the brain and has the potential to transform how we address neuropsychiatric disorders in society. With more accurate tools to assess brain health, we could significantly improve the diagnosis, monitoring, and treatment of these disorders, positively impacting the lives of many people.

Although research in this field is progressing at a slow pace and it is still early to foresee exactly the impact of my work, I am committed and hopeful that we will be able to make significant contributions.

We know that the path to the Ph.D. is not easy. How do you maintain the balance between your personal life and your intense dedication to research while abroad?

At first, it was difficult for me to adapt to the completely new environment, with another culture and language, and facing enormous expectations of a doctorate. I am a very sociable person, I love to be in physical contact with others, hug, kiss, and that is different here.

Over time I’ve come to realize the importance of being very intentional about maintaining a work-life balance, especially in a society that values productivity so much. This balance is not achieved on its own, you have to work on it actively. I force myself to do things that I know benefit me. If you don’t take action, balance just doesn’t come. In the laboratory I have a joke with my classmates, who are younger and still in their grades. They often ask me how long I have to go or when I will leave that day. And I tell them that, technically, I could stay there for the rest of my life, but in reality, I’m leaving in two hours.

In addition, I have spent time choosing the people who are and will be by my side when the going gets tough. I also enjoy the city very much. I’m in Atlanta, which is an amazing city with a lot of diversity and lots of activities to do. On a culinary level it is fantastic, there is everything, except Spanish food, which I do miss a little.

Finally, what advice would you give to students who are considering pursuing a career in biomedical engineering and research?

Definitely, my advice would be not to be intimidated! For a long time, I felt intimidated and out of place. I had the feeling that I didn’t fit the typical profile of an engineer, you know, that image of the scientist in a white coat and very serious, and that sometimes made me doubt. But the important thing I have learned is that there is and should be room for everyone. And if not, then you believe it!

Really, it’s okay if you know exactly what you want to do with your life from the beginning, but if you don’t, that’s okay. As you grow as a person, so do your interests. I started without being very clear about where I was going. However, throughout my training and personal development, I began to discover my values and interests and see how my abilities aligned with my aspirations.

In addition, it is crucial to dare to have a broad vision, a ‘big picture’, even if at first you do not know how you are going to achieve it. Believing in the possibility of thinking and doing something great is fundamental. And although what you set out to do seems challenging and a long road, it is also important to enjoy that path, explore and learn throughout the process. So take heart and don’t shrink from the challenges!

Thank you very much, Eva!

If you’re interested in neuroscience and neurotechnology, don’t miss our Future Trends Forum report: Neurotechnologyfor Human Well-Being.

If you want to know the testimonies of other Akademia alumni, you can see them here.

And if you want to know more about the Akademia program, we invite you to visit the Foundation’s website.