New York City faces over 100 billion potential cybersecurity threats each week. As the frequency and severity of these threats increase, the tech sector turns toward automated solutions.
The Google Cybersecurity Grant is part of Google Cyber NYC Institutional Research Program, launched in 2021 to address these challenges. This award is part of Alphabet Inc.’s initiative to fund $12 million on research at CUNY, New York University, Columbia University and Cornell University. It aims to sponsor 90 research projects in total.
CUNY in partnership with Google, is tackling these problems through research. Distinguished Professor of Electrical Engineering Yingli Tian was awarded the 2025 Google Cybersecurity grant for her research project “Towards Safer Privacy: Leveraging Synthetic Face Generation for Facial Data Protection.”
Tian is among 5 CCNY faculty members from CUNY who will share the $3 million award for pathbreaking research on emerging cybersecurity issues. Leading Principal Investigators, such as Tian, will receive $80,000 to fund their team, as well as a shared $140,000 in Google Cloud Platform credits.
Yingli Tian. Photo Credit: CCNY
“Privacy is getting more and more important,” Tian said. “Two Harvard students just used the [Meta AI Glasses with] face recognition software, so they can recognize your face. Then you can get linked to your address, email, phone number, everything. So in this digital world, there is not any privacy anymore.”
Tian joined CCNY’s faculty in 2008. Previously, she was a research Staff Member at IBM T. J. Watson Research Center, where she led the video analytics team and received the company’s Outstanding Innovation Achievement Award in 2007 due to her contributions to IBM Smart Surveillance System. She also made significant contributions to automatic facial expression analysis and received the “Test of Time Award” at IEEE International Conference on Automatic Face and Gesture Recognition 2019. Since arriving at CCNY she’s focused on applying computer vision, machine learning, and artificial intelligence to assistive technology for people with disabilities.
Computer vision is the AI technology that enables machines to interpret and analyze visual information the same way humans do. For her project, Tian trained machine learning models to analyze and edit faces protecting individuals’ privacy while maintaining a natural appearance.
“We can do a lot to make the algorithms work well,” Tian said. “Currently, our algorithm…can generate realistic synthetic face images that hide a person’s real identity from face recognition systems, while still looking like the same person to other people.”
To Tian, facial privacy and authenticity is at risk. She cited deepfakes– false mockups that depict often used to scam, cheat, and humiliate– as a rising problem. As technology evolves, it becomes more difficult to spot the discrepancies. She wants to see if she can train the models that can protect a person’s facial identity even when the face is viewed from a side angle.
In addition to facial recognition, Tian has worked on machine learning systems for recognizing American Sign Language to help ASL users communicate more effectively with non-ASL users.
Other CCNY awardees include Professors Nelly Fazio and Tushar Jois for “Cryptographically Secure Mesh Messaging for Large-Scale Protests,” Zhigang Zhu for “On-the-Go Privacy: Real-Time and Predictive Visual Privacy Alerts for Smartphone or Wearable Systems,” and Tushar Jois and Rosario Gennaro for “Cryptographic Computation over Spot VMs.”
Mia Euceda is an alumna of Baruch College, where they studied journalism and served as an editor for The Ticker newspaper and Refract Magazine. Their work has been published in The New York Review of Books and Treble Zine.