Jiang Hu

**Jiang Hu** is a Full Professor of Electrical and Computer Engineering at Texas A&M University, holding a Hans Fischer Senior Fellowship at the Technical University of Munich (TUM-IAS). He earned his B.S. in Optical Engineering from Zhejiang University (1990), M.S. in Physics from the University of Minnesota (1997), and Ph.D. in Electrical Engineering (2001). Before joining Texas A&M in 2002, he worked at IBM Microelectronics. His research focuses on Electronic Design Automation (EDA), VLSI physical design, and hardware security, with notable contributions to machine learning-driven CAD tools and approximate computing architectures.

**Education**:

• B.S., Optical Engineering, Zhejiang University (1990)
• M.S., Physics, University of Minnesota (1997)
• Ph.D., Electrical Engineering, University of Minnesota (2001)

**Research Interests**:
Jiang Hu's work bridges EDA and computer architecture, emphasizing optimization of large-scale computing systems. His projects include automated power modeling frameworks (e.g., APOLLO), neural network-driven placement algorithms, and security-enhanced dataflow architectures. He also explores plasmonic materials and perovskite solar cells through interdisciplinary collaborations.

**Awards**:

• IEEE Fellow (2012)
• Alexander von Humboldt Research Fellowship (2011)
• Multiple best-paper awards at IEEE/ACM conferences (2003–2021)

**Grants & Leadership**:
He served as Technical Program Chair for ACM International Symposium on Physical Design (2011–2012) and co-chaired the ACM/IEEE Workshop on Machine Learning for CAD (2023). His research has led to 10 patents and supervision of 24 Ph.D. students.

**Labs & Teams**:
His group collaborates with TUM-IAS on projects like *A New and Scalable Methodology for Fast Machine Learning Accelerator Design*, advancing EDA tools for next-generation hardware systems.