Optimizing health across complex environmental conditions: A conversation with Juliano Morimoto

The NSF-Simons National Institute for Theory and Mathematics in Biology is composed of investigators at the forefront of innovative research at the interface of mathematics and biology. NSF-Simons NITMB Affiliate Members bring unique perspectives vital for developing new mathematics and inspiring biological discovery. One such NITMB Affiliate Member integrating mathematics and biology to drive ecological insight is Juliano Morimoto.

Juliano Morimoto, Senior Lecturer (Associate Professor) in Applied Mathematics and Ecology, University of Aberdeen 

Juliano Morimoto is a Senior Lecturer (Associate Professor) in Applied Mathematics and Ecology at the University of Aberdeen, and Professor of Ecology and Conservation at the Federal University of Paraná, Brazil. His work uses mathematics and statistics to develop new methods in nutrition, ecology, and biodiversity conservation, integrating biological insight with theoretical frameworks across disciplines.  

We spoke with Juliano Morimoto to learn more about his work applying mathematics, statistics, AI, and more to expand our understanding of ecology. 

What is a big question you’ve been asking throughout your research? 

“A central question in my research is how to quantify and optimize health and fitness across complex environmental conditions. I focus on developing and applying mathematical and statistical methods to analyze trade-offs in multidimensional datasets, enabling us to better understand how organisms navigate competing demands in nutrition and ecology.” 

What disciplines does your research integrate? 

“My research integrates applied mathematics, statistics, computational biology, ecology, evolutionary biology, and nutritional science. By combining theoretical modelling with empirical data, I bridge fundamental biology with quantitative frameworks, creating methods that can be applied across systems, from understanding the nutritional trade-offs in insects to guiding conservation strategies for biodiversity. This interdisciplinary approach allows insights from one field to inform and strengthen advances in another.” 

Where do you find inspiration? 

“My inspiration comes from curiosity and creativity in finding patterns within complex problems, and from seeking solutions across disciplines. I take great pleasure in ‘finding things out’ (as once said Feynman) and then adapting those insights to tackle challenges in entirely different contexts. I like to think of myself as a horizontal thinker: someone who learns from discipline-specific solutions and then reimagines and applies them to problems in other fields.” 

What aspects of your work could be interesting to mathematicians or applied to biology? 

“I am developing ways to formalize AI models that can predict optimal diets using hierarchically structured datasets. This involves equipping models with hyperbolic geometry structures that naturally occur in biological data, such as the evolutionary relationships among species, to enhance predictive accuracy. While rooted in biological applications, these methods are designed to be generalizable and ‘user-friendly,’ offering mathematicians and theorists a framework for integrating complex hierarchical relationships into models across many domains. This work is of interest to pure and applied mathematicians as well as computational scientists, as it requires new ways of thinking about how to represent and work with messy biological data, while also exploring strategies to maximize model performance.” 

What about the NITMB do you find exciting? 

“I believe the NITMB is a unique initiative with the potential to break down disciplinary barriers and foster exactly the kind of horizontal thinking that inspires my own work. By bringing together mathematicians, theorists, and biologists in a shared space for ideas, NITMB creates an environment where novel perspectives can flourish and where complex biological challenges can be tackled with innovative mathematical and computational tools. I am delighted and honored to be part of this community, and I see NITMB as a catalyst for collaborations that will both inspire my research and help remove structural barriers to truly interdisciplinary science.” 

What career achievement are you most proud of? 

“I am most proud of mentoring the next generation of scientists and fostering a collaborative, supportive community within my disciplines. Many of my students have gone on to win prestigious awards and secure competitive fellowships. For example, my former undergraduate student Nat Duffus received the 2020 Ian Alexander Prize for outstanding performance in Conservation Biology, a Certificate of Commendation for the Charles Darwin Award and Marsh Prize from the Zoological Society of London, and a fully funded NERC PhD studentship at the University of Oxford. Beyond individual mentorship, I have worked to create inclusive spaces, both in my research groups and across the wider scientific community, where interdisciplinary dialogue thrives and people feel empowered to contribute their ideas.” 

Outside of your research, what other interests do you have? 

“Outside of my research, I enjoy reading, writing, science communication, and learning new things, whether within my field or more often, beyond it. I was once a competitive swimmer, and I still value the discipline and focus that sport instilled in me. Most importantly, I love spending time with my family, especially with my energetic two-year-old son, who keeps me on my toes and reminds me daily of the joy of curiosity.” 

What are you hoping to work on in the future? 

“In the future, I am striving to advance my work on developing models that can predict optimal nutrition. As I mentioned, I am working on integrating hyperbolic geometry into AI models to better capture hierarchical structures in biological data, with a particular focus on predicting optimal diets across species. This direction not only addresses fundamental questions in nutrition and ecology but also has potential applications in conservation, biodiversity monitoring, and even human health. I am especially interested in building collaborations that bridge mathematics, computer science, and biology—bringing together theorists, experimentalists, and applied scientists to create tools that are both rigorous and accessible. I am also open to international collaborations, industry partnerships, and visiting roles or fellowships that would allow me to engage deeply with mathematicians, computer scientists, and researchers from other disciplines, fostering the exchange of ideas that is essential for innovation.” 

Is there anything else you would like the NITMB community to know about you? 

“I am deeply committed to the mission of NITMB and to building genuine, productive collaborations across disciplines. I approach my work with curiosity, openness, and a strong desire to keep learning—not only about my own research areas, but also about ideas and methods far outside my expertise. I value being mentored as much as mentoring others, and I believe that exchanging perspectives across career stages and disciplines is one of the most powerful ways to advance science. Above all, I am excited to connect with the NITMB community, share my ideas, and contribute to the cross-pollination of knowledge that the institute was created to foster.” 

More information on Juliano Morimoto’s work is available on his website, Google Scholar profile, University of Aberdeen profile, and LinkedIn. He is also open to discussing his work over email.