Since I began my high school education in Chennai, I aspired to pursue a career in medicine and become a neurologist. Despite securing excellent grades in my high school examinations, my performance in a key state competitive examination was insufficient to secure admission to a state government medical college. Realising that a career in medicine was out of reach, I diligently explored university programs in neuroscience but didn’t receive the career guidance I anticipated. Feeling dejected and down, I enrolled in an engineering college in the state and eventually became a computer science engineer. My decision to pursue a career in engineering was influenced by the burgeoning information technology industry in the country, and partly because of family and peer pressure.

During the four years of my undergraduate education, I developed strong mathematical and computer programming skills through my degree in computer science. Upon graduation, I was fortunate to secure a job offer at a top software services company. But deep down, I had a strong passion for biomedical sciences, particularly in the field of neuroscience. 

At this juncture, I made a crucial decision that completely changed the trajectory of my career.

Against my family’s desires, I ultimately turned down the job offer and chose to pursue my passion. I went to the United Kingdom to pursue a Master’s program in Cognitive and Computational Neuroscience at the University of Sheffield, where I explored the intersection of life sciences and mathematical sciences. It was a risky move, but it turned out to be a truly rewarding experience. Shortly after graduating with a Master’s degree, I pursued a PhD at the University of Antwerp, Belgium, followed by a postdoctoral stint at the University of Michigan, Ann Arbor, in the United States. I was fortunate to be mentored by prominent scientists who significantly contributed to honing my academic and research skills. Despite the numerous detours, I eventually realised my dream.

Interdisciplinary skills and contemporary scientific questions

Despite its circuitous nature, my academic journey has broadened and strengthened my theoretical, analytical, and problem-solving skills, thanks to the interdisciplinary nature of modern science. Although I have switched my primary field of interest from computer science to neuroscience, the interdisciplinary (mathematical and computational) skills I acquired during my undergraduate education, and further refined during my masters, doctoral and post-doctoral training, have been invaluable assets for advancing of my research career in neuroscience. 

Understanding how the human brain functions requires a complex interplay of experimental and computational skills. Given the intricacy of the brain, with billions of neurons and trillions of synapses that connect them, strong computational skills are essential for deciphering its complex operations across multiple spatial and temporal scales.

The significance of computational skills must be acknowledged in advancing biomedical research. Computational skills have proven to be pivotal in various aspects, such as identifying promising drugs and drug combinations for treating deadly brain diseases, discovering biomarkers for various pathological conditions, automated classification of subjects suffering from psychiatric conditions using machine learning, and applying bioinformatics methods for identifying promising anticancer treatments. 

Computational skills are important

An event that is worth mentioning in my scientific career regarding the importance of computational skills is when my former advisor asked me to find promising drugs to prevent neuronal death after traumatic brain injuries. The field of traumatic brain injuries is quite challenging since there are no drugs to stop the flurry of cell death following the impact to the brain. I successfully employed my computational modeling skills and discovered that the combinatorial action of two drugs provides more benefits than the action of individual drugs. If such computational modelling expeditions precede experimental studies, this could save time and effort. 

Another vital application of computational skills in my research work emerged recently during my interactions with one of my students. We were trying to identify which co-morbidities were commonly observed after traumatic brain injuries, and one of my students came up with an excellent idea to represent the co-morbidities in the form of a graph network and study their associations. 

Such carefully crafted computational analysis could reveal unique insights into the underlying research question.

Teaching and mentoring undergraduate researchers

After completing my postdoctoral training at the University of Michigan, Ann Arbor, I joined Krea University as an Assistant Professor of Biological Sciences. At Krea, I teach various courses, from biological sciences to data sciences. Teaching is an enriching experience as it helps consolidate previously acquired knowledge. A typical class at Krea comprises students from diverse academic backgrounds, which requires me to apply a wide range of pedagogical methods to cater to their varying needs. I encourage my students to engage with a broad range of courses to equip them with the skills necessary to solve problems in their discipline of interest.

Motivated by my teaching, students have sought to undergo research training under my supervision. Undergraduate mentoring could be a gratifying experience as it helps to refresh one’s skills from scratch. Though time-consuming, if honed meticulously, undergraduate students could significantly contribute to a faculty member’s research program. It’s also an excellent opportunity for me as a faculty member to motivate and shape aspiring future scientists. Numerous undergraduate students with a keen interest in learning new things and from diverse academic backgrounds have contributed to my research, working specifically on applying computational and data science methods to problems in the domain of biomedical sciences.

At Krea, there is always an opportunity to collaborate with other faculty members and interweave my research work with different branches of sciences and social sciences. In this regard, I have started collaborating with faculty members from other disciplines, making my research program more and more interdisciplinary.