Posted by Jacqueline Corricelli
On Thursday, 9/24/2020, I had the opportunity to talk with Connecticut Affiliate NCWIT Collegiate Award Winner, Tiffanie Edwards.  Read on to learn more!  

She’s Here Now by J. Corricelli

On Thursday, September 24, 2020, I had the opportunity to talk with the Connecticut NCWIT Affiliate Collegiate Winner, Tiffanie Edwards.  Now a first semester graduate student at University of New Haven, Tiffanie won the award while studying computer science at Southern Connecticut State University.  I left our conversation inspired and thrilled to report about how she, a Bridgeport/Connecticut native, has had multiple positive experiences in our university system that have led to her degree, continuing education, and interest in computer science.  

Opportunities to grow and learn more about computing were not available to her until she began her university studies. Upon entering SCSU, she changed her plans from a major in chemistry to a major in computer science. She recalls feeling a bit out of place because she was majoring in something that she did not really know about until college.  However, she has realized that, “it does not matter that I did not have these experiences growing up because I’m here now”.  

Winning the NCWIT Collegiate Award further affirms that yes, she is here now and she will be using computer science to make a positive difference in our world.  Tiffanie first learned about the NCWIT Collegiate Award through her research project advisor at Southern CT State University, Dr. Hossain, and the computer science department head, Dr. Lancor.  At first, she was hesitant to apply because she was not sure that her research “was good enough” to earn this recognition.  Her project was entitled, “Deep Learning for Score-based Serial Fusion for User Verification”.  It proposes to determine how well a deep learning model performs with serial fusion at the score level in user verification. This multimodal classification is done with the finger, facial, and palm biometrics. Deep learning is an advanced subfield of machine learning that learns data representations from unstructured or unlabeled data. A deep learning approach does not depend completely on domain knowledge or handcrafted features (features chosen in advance by the programmer). Biometric fusion is the combination of biometric matchers to either enhance incomplete data, improve the ability to handle large databases or improve user protection.

From pursuit and winning this recognition, Tiffanie feels grateful that she applied and validated in winning.  Reflecting on this, she said she realized that,  “Even when I think I am not doing well, there are people who believe in me.”   She continues, “computer science does not have to be a male-dominated field”.  

Tiffanie advises that all college students should take at least one computer science course because knowing even a little bit can put you ahead of your counterparts.  

Be here now.  Nominate a student for this recognition.  To find out more about NCWIT and the difference it is making toward changing the demographics of the computer science profession, go to