Shaoyi Huang

Shaoyi Huang is an Assistant Professor in the Department of Computer Science at Stevens Institute of Technology. She holds a PhD in Computer Engineering from the University of Connecticut (2024), where she was advised by Professors Caiwen Ding and Omer Khan. Her research focuses on advancing AI systems through algorithm-hardware co-design, with emphasis on efficient machine learning algorithms, energy-efficient privacy-preserving techniques, and large-scale machine learning for chip design. She has received multiple accolades including the 2024 Machine Learning and Systems Rising Star award and the 2022 DAC Publicity Paper Award.

• Education: PhD in Computer Engineering, University of Connecticut (2024)
• Appointments: Assistant Professor, Stevens Institute of Technology (2024–present)
• Key Research Areas: AI acceleration, graph neural networks, privacy-preserving ML, and EDA applications

Her work spans theoretical contributions to practical implementations, with publications in top-tier conferences like HPCA, ASPLOS, and NeurIPS. She actively contributes to the academic community through program committee roles (e.g., DAC 2025, IPDPS 2025) and serves as a Guest Editor for special issues on high-performance computing. Huang mentors PhD students and oversees a team advancing interdisciplinary AI research, including funded projects from NSF and industry partners like AWS and OpenAI.

Awards highlight her impact: Marion & Frederick Buckman Engineering Fellowship (2024), multiple fellowships from UConn, and recognition at WISE conferences for promoting women in hardware security. Her lab emphasizes scalable solutions for real-world challenges in AI and hardware systems.