Yevgeniy B. Sirotin
Yevgeniy B. Sirotin
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About ME

Making a difference, staying humble

As a researcher, I am driven to identify ideas and supporting data to make a positive impact to the organization within which I work.  My Ph.D. from Columbia University is in Neurobiology and Behavior. I have diverse research interests and have contributed to diverse fields including Psychology, Neuroscience, and Computer Science.  

I believe that quality work speaks for itself. 

Meaningful results, beautiful evidence

The purpose of modern data science technology is to summarize data so as to inform human decision making, i.e.  telling stories with the evidence.  In my work, I combine modern tools with deep understanding in order to produce meaningful results.

What's important?

I enjoy challenging and meaningful work with interesting colleagues, but the most important thing in my life is my family.

Research Highlights

Cerebral Hemodynamics

Olfaction and Intensity Perception

Olfaction and Intensity Perception

My graduate and post-graduate work at Columbia University focused on multi-wavelength imaging of cerebral hemodynamics.  This research triggered a needed debate regarding the origin of brain imaging signals and produced startling images of brain function included in popular books.

Olfaction and Intensity Perception

Olfaction and Intensity Perception

Olfaction and Intensity Perception

During my work as a Fellow at The Rockefeller University, I studied olfaction in rodents as a model of object perception.  This work has led to new insights into how we perceive and how the brain represents object quantity and quality.

Demographics and Biometric Systems

Olfaction and Intensity Perception

Demographics and Biometric Systems

 For the last five years, I have been doing applied research in biometric systems using large scale scenario evaluations with diverse people at the Maryland Test Facility.  As part of this  work, I developed a new way to assay skin color and showed how to use this assay to measure the equitability of face recognition systems.

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