Faculty Q&A: Archana Venkataraman

January 6, 2017

Photo of Archana VenkataramanArchana Venkataraman is an assistant professor in the Department of Electrical and Computer Engineering.

What made you initially interested in science?

I caught the science bug at an early age. My parents are both professors, so while growing up, the majority of our toys, activities and TV programming was educational. My birthday and Christmas gifts featured at least one science kit, math puzzle, or instructional computer game. My mother and I spent the weekends setting up science demos or doing math problems together. And even something as simple as a plush toy had to be scientifically-grounded. To this day, I have a growing menagerie of stuffed animals, from a three-toed sloth to an okapi to a red-eyed tree frog. But, I have never owned (or wanted to own) a teddy bear.


What groups/extracurricular activities did you participate in while studying in college?

My primary extracurricular was playing badminton. It was a nice break from my engineering coursework, and it allowed me plenty of exercise. Also, smashing the shuttlecock at your opponent is a wonderful stress reliever.


What made you decide to focus on engineering?

I have always been curious about the world, and I love solving puzzles. Engineering is a natural bridge between theory and application that enables me to leverage my technical background in order to explore new ideas and make an impact in the world. As an added benefit, I have gotten the opportunity to learn from brilliant researchers across a range of disciplines, from applied mathematics to child psychology.


What are your biggest research accomplishments?

I developed an entirely new framework to characterize network-based abnormalities in the brain. My approach was not derived from existing methodologies in the field. Rather, I went back to first principles and asked: how can we reasonably model neural interactions, and how do I represent this information in a clinically interpretable fashion? In the end, I formulated a probabilistic graphical model that assumes a latent organization for the brain, which we cannot observe but which captures the patterns of interest. This latent structure is complemented by subject-level imaging data from functional MRI. My work yielded three oral presentations at one of the most prestigious medical imaging conferences and is now being employed by researchers at several institutions.


What are you looking forward to focusing on in the future? 

I am excited to identify and tackle open challenges in the clinical neuroscience realm. The human brain is a myriad of interconnected pathways and complex dynamical interactions. My research focuses on building a comprehensive and system-level understanding of the brain by strategically combining analytical tools, such as probabilistic inference, signal processing, and matrix factorization, with key application-driven hypotheses. This approach promises to yield new insights into debilitating neurological disorders, such as autism and epilepsy, with the long-term goal of improving patient care.


What advice would you give students who are interested in engineering?

Don’t become so engrossed in a single technical problem that you lose sight of the broader picture. I believe that the most difficult challenges of the future will be interdisciplinary, such as medicine, energy, and the environment. These problems require, not only a solid technical foundation but the ability to collaborate with other experts and to blend information from multiple fields. Therefore, do not hesitate to venture beyond your current lab, coursework, research area and department.

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