David Zaretsky

David Zaretsky is an Associate Professor of Instruction and Assistant Chair of Electrical and Computer Engineering at Northwestern University. He teaches advanced courses in computer engineering, focusing on AI systems, high-performance computing, computer architecture, electronic design, and technical entrepreneurship. His teaching emphasizes translating foundational theory into real systems, enabling students to apply knowledge to practical engineering challenges. His research and professional interests include scalable computing architectures, hardware/software co-design, AI acceleration, and the transition of laboratory concepts to deployed platforms.

David Zaretsky is a researcher at Northwestern University specializing in AI, FPGA, Computer Vision, Machine Learning, and EDA. His work focuses on translating software into hardware, particularly through compiler development for reconfigurable computing systems. He has published extensively on MATLAB-to-FPGA synthesis, automatic translation of software binaries onto FPGAs, and the design of tools like BINACHIP-FPGA for mapping DSP software to hardware. His research also includes streaming implementations of algorithms such as ZLIB and sequential decompression on FPGAs, as well as dynamic resource sharing and scheduling in high-level synthesis for FPGA designs.