����Ӱ��

Zahir Alsulaimawi, a postdoctoral researcher in the School of Electrical Engineering and Computer Science at ����Ӱ�� State University, received a best paper and presentation award at the .

Alsulaimawi, who earned master’s and doctoral degrees in electrical and computer engineering at ����Ӱ�� State, researches ways to make machine learning models smarter without compromising people’s privacy.

His work uses federated learning, a method to train models across multiple devices or servers holding local data samples without exchanging them. This allows researchers to build powerful AI models without moving sensitive data from people’s devices and ensures that personal information stays private.

“My work involves developing new techniques to make this process more efficient and secure, helping to balance the need for advanced AI capabilities with the critical importance of protecting user privacy,” Alsulaimawi said.

His paper, “,” focuses on privacy-preserving machine learning techniques applied to image classification tasks.

After earning a bachelor’s degree in electrical engineering from the University of Baghdad, Alsulaimawi chose to study at ����Ӱ�� State in 2015 for its innovative research in machine learning.

“This award serves as a recognition of the hard work and dedication I have invested in my research, particularly in the challenging field of privacy-preserving machine learning,” he said. “It motivates me to continue pushing the boundaries of what is possible in this field to contribute to safer and more ethical AI practices.”