Rohit Ravi

Tennis was a large part of my life. I played first singles on an elite team at Northern Highlands, and during the COVID lockdown I often spent six hours a day on court. Training gave my days structure, and physical effort was something I could depend on.

When I became ill at the beginning of college, activities that had once been routine became inaccessible. I lost the physical capacity I had depended on, and long stretches of illness narrowed the world around me.

It took over a year to begin understanding what was happening. After multiple procedures, including an endoscopy and a complete gastrointestinal workup, we learned that the problem was neurological: dysfunction involving the neural circuits that regulate the GI tract. Investigations had found no structural explanation for the severity of the symptoms. Yet during episodes, I experienced pain and nausea more intense than anything I had previously known.

That recognition gave us a direction. We sought out specialists in neurogastroenterology, hoping that understanding which system was involved would bring us closer to an explanation. I began to appreciate how much uncertainty could remain even within specialist care. Identifying the neurological nature of the illness did not establish its underlying mechanism or provide a clear path to resolving it.

Dr. Wilfrid Raby, whose care made an enormous difference to my life, approached that uncertainty with candor and commitment. From our first conversation, he acknowledged that we were working in territory that was not fully understood. We would use the information available, work carefully, and try to reduce the symptoms and periods of pain. Over time, we made immense progress. Treatment made the condition manageable, and I remain deeply grateful for his persistence and care.

But the improvement left questions I could not put aside. The year before becoming ill, I had been in the best physical condition of my life. Now there were periods when I could barely get out of bed, let alone train or play tennis. How could such a profound change occur without a prior history or a structural explanation on imaging? What had changed in the system, and why was it so difficult to identify?

Those questions opened a further search. I wanted to understand how neural circuits could become so profoundly disrupted, what responses to treatment might reveal about their mechanisms, and how computational tools could help investigate problems that remained difficult to answer clinically. The distance between what I was experiencing and what we could explain became a reason to keep learning—and to develop the technical skills to investigate further.

During that period, I began exploring my roots and reading the Eastern philosophical texts that became personally meaningful to me. Vedanta gave me a way to think about suffering and identity when illness had disrupted much of the life I knew. Reading it also drew me further toward the science of consciousness. Questions about the self, perception, and experience became things I wanted to understand through neuroscience and computation as well as philosophy.

I became interested in reconciling perspectives I had often encountered as opposites: science and philosophy. I wanted to understand where they could illuminate the same questions, where they differed, and what each could reasonably explain. That search drew me toward philosophy of mind and gave my technical interests a broader purpose.

Studying neural systems became a way to pursue both the biological questions raised by my illness and the questions about experience that these texts had brought into focus. Together, they shaped the direction I wanted my work to take: developing a deeper understanding, and using the advanced technical tools of our time to turn that understanding into help for as many people as possible.

My coursework in machine learning gave me a practical starting point. Working with C. elegans let me begin studying nervous systems computationally: how connectivity, cellular properties, and activity relate, and what a model can reasonably tell us about the living system it represents. The notebooks were a learning pipeline, through which I developed the ability to turn broad biological questions into analyses and experiments.

My own search also drew me toward genetic, mitochondrial, and myelination mechanisms. I was interested in how nervous-system function can be disrupted through processes that are difficult to see in a conventional structural investigation.

Some of that reading informed things I tried personally, including DHA and palmitoylethanolamide with luteolin. I experienced benefits, although that experience cannot establish which mechanism was responsible or what would help someone else. It gave me further questions to investigate.

The autism and myelination work became especially personal when I saw a young relative suffering. I recognized something of the helplessness I had experienced myself, and I wanted to help in whatever way I could. My experience with DHA was part of what first directed my attention toward lipid supply and myelination. From there, the task was to examine whether the biological evidence supported the initial idea—and how the question needed to change when it did not.

My interest in anesthesia and sleep grew from another observation during treatment: profound changes in nervous-system state could interrupt acute suffering. That made reversibility especially compelling to me. How can a nervous system enter a dramatically different state and then return? What distinguishes reduced activity, quiescence, sleep, and anesthesia? Computational models offered a way to begin exploring those questions.

These projects share a personal origin, but each needs evidence appropriate to its own claims. My experience helps explain why I ask the questions. The research has to determine what answers they can support.

As my technical skills developed, my work expanded into decoding information from neural signals.

LibriBrain brought me into MEG analysis and the challenge of extracting useful information from noisy measurements. It also made evaluation itself a central part of the work: understanding how much of a model’s performance reflects the neural signal and how much can be explained by timing or other features of the task.

The wrist-EMG handwriting project explores a different interface between nervous systems and computation. It asks how signals associated with intended movement can support communication, and how adaptation to an individual changes a model’s usefulness.

These projects are opportunities to demonstrate the engineering skills behind my broader interests: working with complex data, training and adapting models, designing evaluations, and investigating why a result changes. They also connect to something that has become deeply important to me—how computation can help preserve or recover a person’s ability to act, communicate, and participate in life.

I want to bring this combination of personal commitment and technical ability to a research team or company working on consequential problems in biology, neural systems, or machine learning.

There is much I still want to learn. I’m looking for work that demands depth: difficult data, mechanisms that remain uncertain, and tools that need to function beyond a demonstration. I want collaborators who care about both the quality of an explanation and what it could make possible for people.

Illness changed the life I expected to have. It also helped clarify the work I want to devote myself to. My goal is to use machine learning, neuroscience, computation, and philosophy to tackle the hardest problems I can contribute to solving—and, through that work, make suffering more bearable.