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Meet the Inspiring Researcher Rachel at John Hopkins University -- Neuro Signal Processing

Updated: Mar 19, 2021

Nathan and Molly interviewed Rachel June Smith, a postdoctoral fellow at Johns Hopkins University working on neural signal processing for adult epilepsy patients. Her work has focused on processing various types of biomedical signals: ECG signals while doing research in college, arterial blood pressure waveforms through an internship at Edwards Lifesciences, and EEG signals during her Ph.D.

BioTEC: Rachel, why don’t you start by telling us what you work on at JHU?

Rachel: Absolutely! My Ph.D. was focused on analyzing raw EEG signals to inform treatment plans for infants with epilepsy. We were trying to predict things like how a baby might respond to a certain intervention and what their expected clinical outcome would be.

Later in my Ph.D., I learned about Sri’s lab at JHU and began following her work closely. About a year later, I finally met her at a conference, and am fortunate to now be working in her group!

Now as a postdoc, I’m using controls theory and systems modeling to guide interventions for adult epilepsy patients. Around 30% of patients don’t respond to drug-based treatments and need surgery to remove the parts of their brain causing seizures.

By building mathematical models of the brain, perturbing them, seeing how they respond, and performing systems and controls analysis on the results, we can identify this seizure onset zone.

BioTEC: How does the modeling process actually work? Did your group build a brain model from scratch?

Rachel: Adam Li, a graduate student in our group, showed that if you only consider a short time window, the brain acts relatively linearly and maintains stationarity. Within this small timeframe, we can use really simple models to capture very complex behavior.

We aren’t really building these computational models from the ground up, neuron by neuron. Rather, we’re taking EEG signals and building mathematical tools to help us better make sense of how these signals fit together -- usually, clinicians visually inspect these signals. We’re trying to build a computational tool that will give them a holistic picture of how the brain is working during these critical moments.

BioTEC: Is this already being used by clinicians?

Rachel: Well, during my PhD I was always in close contact with clinicians and epileptologists. I’d always try to better understand their needs -- for example, by asking what features of the signal were useful -- before going back to the lab to identify algorithms and build tools.

That project is at a point where some of the neurologists we worked with are already taking these algorithms into the clinic and using them, not for decision-making but as a first step in the validation process. Since these algorithms make very high-stakes decisions, a lot of testing is needed to prove their efficacy. The other reason for the slower clinical adoption of computational tools in neuroscience is more of a cultural one. These clinicians have trained for years, so we really need to build their trust before they alter their clinical decisions based on an algorithm.

My postdoc, on the other hand, is a lot broader and early-stage. We still have a ways to go before we see this tool being used in the clinic.

BioTEC: We’d love to learn more about your path from undergrad to now. What are some key experiences you’ve had?


I must say, my story has been very roundabout!

During my undergrad, I got involved with research on ECG signal processing but had never seriously considered academia as a career. Later on, I spent a summer at Oak Ridge National Laboratory working on materials and additive manufacturing. That experience was what prompted me to go to grad school.

I came to UC Irvine, intending to do my Ph.D. on 3D printing orthopedic implants, but it turned out that the professor I was hoping to work with didn’t have enough funding! So I continued doing lab rotations and finally, a professor ended up reaching out to me because she felt my experience with ECG signal processing was translatable to her neuroscience work.

At first, I was very reluctant to join her lab because I didn’t even know how to code -- back in college, I had failed a course on MATLAB! -- and didn’t think I’d be a good fit. However, this professor, who ended up being my Ph.D. supervisor, was extremely encouraging. She taught me about the field from the ground up and has been an incredible mentor throughout.

Finally, in the fourth year of my Ph.D., I had the opportunity to intern at Edwards Lifesciences. There, I was writing algorithms to analyze blood pressure waveforms and determine whether a patient needed additional fluids or a vasopressor to maintain adequate blood perfusion.

BioTEC: During this process, did you face any moments of adversity?

Rachel: Honestly, I don't have a great answer to this because I’ve always had exceptional mentors and colleagues that have supported me through various stages.

One thing that I did find tougher at first was the grad school process itself.

No one in my family has a graduate degree and it was hard to have to know and navigate the system before even starting. I’m incredibly passionate about paying it forward in this area and similarly serving as a mentor for first-generation college and grad students.

BioTEC: What lessons did you learn that you’d like to share with our audience?

Rachel: It’s extremely important to choose a supervisor based on how they will help you develop as a researcher, for example, in critical thinking, research design, and writing grants. A Ph.D. only lasts a few years, and it’s essential that you are passionate about the topic, but try to build skills that are going to take you even farther. It’s critical that young people focus on professional development early on.

As well, I would say that finding a work-life balance that matches your energy balance is key. In my case, this is a very work-hard-play-hard dynamic. During my Ph.D., for example, my qualifying exams were on a Friday afternoon; after spending the week studying, I finished my exam, hopped in my friend’s car, and proceeded to spend the weekend snowboarding. I think you can be so much more productive after finding what balance works for you and leveraging it.


Rachel is happy to connect with students to chat further; she can be reached by email at

Nathan is a fourth-year biomedical engineering student and Molly is a first-year biology student, both at the University of Waterloo.


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