Departments: Electrical and Computer Engineering
Degree programs: B.S., Electrical Engineering
“I was drawn to Baskin Engineering because of its focus on fundamental research problems at the intersection of biology and computers. Also, the proximity to Silicon Valley offers connection to industries who are at the forefront of discovery, and opportunities to translate research into industry.”
Kamran Hussain is a second year electrical engineering student. He is part of the Braingeneers Group, where he leads an innovative project studying the electrical activity of neurons, using AI to predict the activity of neural circuits. He is the recipient of the Simons Foundation’s Shenoy Undergraduate Research Fellowship in Neuroscience (SURFiN), which allows him to conduct research in the Neural Prosthetics Translational Lab at Stanford University’s Department of Neurosurgery.
Why Baskin Engineering?
I was drawn to Baskin Engineering because of its focus on fundamental research problems at the intersection of biology and computers. Also, the proximity to Silicon Valley offers connection to industries who are at the forefront of discovery, and opportunities to translate research into industry.
What experiences shaped your interest in electrical engineering?
In high school, I reached out to neuroscientists to explore opportunities in neuroscience research. Before attending UC Santa Cruz, I interned at NASA Ames Research Center, where I spoke with engineers about their backgrounds. I also interned at the Translational Neuroengineering Lab at UC San Diego, where I first worked on Brain-Computer Interfaces and neural decoding. There, I saw how closely electrical engineering concepts are tied to Brain-Computer Interfaces. Throughout these experiences, everyone I spoke with recommended electrical engineering for its broad applicability across various scientific fields.
How did you get involved with the Braingeneers Group?
After becoming a student at UCSC, I sought out computational neuroscience labs focused on bioelectronic fabrication. I reached out to Mircea Teodorescu, an associate professor of electrical and computer engineering and biomolecular engineering, and Mohammend Mostajo-Radji, an assistant research scientist at the UCSC Genomics Institute. Both are members of the Braingeneers Group, which uses AI and cerebral organoids (miniature lab-grown brain structures) to study brain development and neural circuits. They invited me to a Zoom call, where I shared my background and expressed an interest in their work. That’s how I became a Braingeneer!
What are you working on with the Braingeneers Group?
I proposed and co-led a project with bioinformatics undergraduate Samantha Chan that used advanced AI techniques to develop a chatbot for the lab. The chatbot allows lab members to interface with the Braingeneers’ codebase, documentation, and papers via Slack. This project significantly boosted the research team’s productivity, and I also proposed integrating this idea with the wet lab devices system.
The main project I lead focuses on developing a foundational model for organoid electrophysiology, which involves analyzing and predicting the electrical activity of neurons in the brain. This work leverages machine learning techniques to create a model capable of predicting neural circuit activity, similar to how generative AI models like ChatGPT predict language. The project originated from discussions with Distinguished Professor of Biomolecular Engineering David Haussler, who emphasized the need for such models to better capture the brain’s complex behavior.
Can you tell us more about the Simons Foundation’s Shenoy Undergraduate Research Fellowship in Neuroscience?
I was recently awarded the SURFiN fellowship. As part of this fellowship, I will conduct research in the Neural Prosthetics Translational Lab at Stanford University’s Department of Neurosurgery. My research will analyze the neural correlates of speech in the human brain and how speech rate is encoded. This involves using statistical signal processing and machine learning to decode brain activity, and convert electrical signals into text or speech.
Where do you see yourself after graduation?
I’m passionate about translational computational systems neuroscience from a brain-computer interface perspective, and I plan to pursue a Ph.D. in this field. In the long term, I hope to apply insights from organoid models to humans, with the goal of improving neuroprosthetics, advancing Brain-Computer Interfaces as therapeutic tools, and addressing fundamental questions in systems neuroscience.
What advice would you give to students who are interested in a similar path?
Reach out to experts in your field and seek their guidance. It’s as simple as being curious and asking questions. Most people are happy to help!
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