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#FacesofPhotonics: Rising Researcher Alina Zare

Alina Zare
SPIE's #FacesofPhotonics is sharing the story of Alina Zare, Associate Professor at the The Machine Learning and Sensing Lab at the University of Florida. Dr. Zare was recognized as a 2018 Rising Researcher for her work in Electronic Imaging & Signal Processing, at the SPIE Defense + Commercial Sensing conference.

This program recognizes early career professionals who conduct outstanding research in the defense, commercial, and scientific sensing, imaging, optics, or related fields. If you want to learn more about the program, the details are here.

Enjoy the interview with Alina!

1. Tell us about when you first became interested in optics and photonics.

In my senior year of  undergraduate studies in computer science, I was taking an Image Processing elective.  I really enjoyed the course, and the professor for the class, Dr. Gerhard Ritter, encouraged me to do some undergraduate research.  

So I joined Dr. Paul Gader's research lab as a undergraduate researcher where I helped on a project for analyzing hyperspectral imagery for buried target detection. I really enjoyed the research and ended up staying for my PhD in the same lab!

2. Describe a memorable experience from an SPIE event. 

The first technical conference I attended was SPIE Defense + Security Sensing in 2007, and I presented my hyperspectral unmixing research. I was incredibly nervous but was excited to share my work, and I got a lot of positive feedback through questions and discussion with the audience. It is a great first conference presentation memory.

At "Touchdown Terrace" on the University 
of Florida's football stadium, giving a 
speech to prospective graduate students
3. Share your favorite outreach or volunteer story.

As a PhD student, I taught an Introduction to Machine Learning course for high school students over one summer. There was a student in the course who made it clear that she intended to be a medical doctor and had no interest in computer science. Throughout the class, I made it a point to show various applications and uses of machine learning in the world.

During the last day of the course, she came up to me and said that was really glad she took the course and is reconsidering her goals, that computer science was a lot more interesting to her now! This was the first time I received feedback from a student on the impact my teaching was having. Every time I have gotten this sort of feedback since, it is still a wonderful feeling.

4. Explain your current research, and how it can impact society.

My lab develops machine-learning methods for automatically analyzing and understanding sensor data. We investigate and develop machine learning, pattern recognition, computational intelligence, signal processing, and information fusion methods for application to sensing. Applications we have studied include landmine and explosive object detection, automated plant phenotyping, sub-pixel target detection, and underwater scene understanding.

We have developed algorithms for ground-penetrating radar, hyperspectral imagery, electromagnetic induction data, synthetic aperture SONAR, and minirhizotron imagery.  Much of our research focuses on developing methods that can learn from imprecise training labels because, in practice, obtaining precisely labeled training data can be extremely costly and, in some cases, unfeasible.
On campus at the University of Florida

SPIE’s #FacesofPhotonics social media campaign connects SPIE members in the global optics, photonics, and STEM communities. It serves to highlight similarities, celebrate differences, and foster a space where conversation and community can thrive.

Follow along with past and upcoming stories on SPIE social media channels:

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