Regular biography
Hadi Esmaeilzadeh is a faculty member in the Department of Computer Science at the University of California, San Diego. His research interests include areas related to computer science, though specific details are not provided. He maintains a professional website at https://cse.ucsd.edu/people/faculty-profiles/hadi-esmaeilzadeh, where additional information about his work and contact details can be found. His profile page indicates his affiliation and contact information, but further details about his academic background, awards, or specific research projects are not available.
Scholar-generated biography
Hadi Esmaeilzadeh is an Associate Professor in Computer Science and Engineering at the University of California, San Diego. His research focuses on Computer Architecture, Machine Learning, VLSI, Approximate Computing, and Dark Silicon. He explores innovative solutions to address the challenges of power efficiency and performance in modern computing systems, particularly in the context of deep neural networks and datacenter services. His work includes developing architectures for approximate computing, reconfigurable fabrics, and neural acceleration techniques. Esmaeilzadeh's research also addresses the limitations of multicore scaling and the implications of dark silicon on future computing paradigms.