Hadi S. Esmaeilzadeh

Halicioğlu Chair in Computer Architecture

Associate Professor

University of California, San Diego
Department of Computer Science and Engineering

hadi [AT] eng [DOT] ucsd [DOT] edu

9500 Gilman Drive, #0404
La Jolla, CA 92093-0404

Research Group: Alternative Computing Technologies (ACT) Laboratory

Curriculum Vitae

Hadi was awarded early tenure at the University of California, San Diego (UCSD), where he is an associate professor in Computer Science and Engineering. Prior to UCSD, he was an assistant professor in the School of Computer Science at the Georgia Institute of Technology from 2013 to 2017. There, he was the inaugural holder of the Catherine M. and James E. Allchin Early Career Professorship. Hadi is the founding director of the Alternative Computing Technologies (ACT) Lab, where his team is developing new technologies and cross-stack solutions to build the next generation computer systems. He is also the associate director of Center for Machine Integrated Computing and Security (MICS) at UCSD.

Dr. Esmaeilzadeh received his Ph.D. from the Department of Computer Science and Engineering at the University of Washington in 2013. His Ph.D. dissertation received the 2013 William Chan Memorial Dissertation Award from the University of Washington. Hadi was inducted to the ISCA Hall of Fame in 2018.

His research has been recognized by four Communications of the ACM Research Highlights, four IEEE Micro Top Picks, recently one more nominations for Communications of the ACM Research Highlights, one more honorable mention in IEEE Micro Top Picks, and a Distinguished Paper Award in HPCA 2016.

Hadi has received the Air Force Young Investigator Award (2017), College of Computing Outstanding Junior Faculty Research Award (2017), Qualcomm Research Award (2017 and 2016), Google Research Faculty Award (2016 and 2014), Microsoft Research Award (2017 and 2016), and Lockheed Inspirational Young Faculty Award (2016).

His team was awarded the Qualcomm Innovation Fellowship (2014), one of his student is a Microsft Research Fellow, and another won the the 2017 National Center for Women and IT (NCWIT) Collegiate Award. Four of his undergradaute students have been awarded the Georgia Tech President's Undergraduate Research Award (PURA). Hadi's work on dark silicon has been profiled in New York Times.

I am eagerly looking for students that ambitiously want to make a difference! Please read my research statement before contacting me.

Project PHI: System Design for Pervasive Hierarchal Intelligence

Currently, we are focusing on Project PHI (Pervasive Hierarchical Intelligence), a holistic effort to provide a comprehensive solution for making immersive machine intelligence a reality.  Our guiding principle is to retain as much generality and automation while delivering large performance and efficiency gains through specialization and acceleration for a wide range of learning and intelligence workloads. As the first milestone of Project PHI, we have developed Tabla, which is open source and available at http://act-lab.org/artifacts/tabla/. This cross-stack solution - spanning from programming language to the hardware - rethinks the hardware/software abstraction by delving into the theory of machine learning. It leverages the insight that many learning algorithms can be solved using stochastic gradient descent that minimizes an objective function. The solver is fixed while the objective function changes with the learning algorithm. Therefore, Tabla uses stochastic optimization as the abstraction between hardware and software. Consequently, programmers specify the learning algorithm by merely expressing the gradient of the objective function in our domain specific language. Tabla then automatically generates the synthesizable implementation of the accelerator for scale-out FPGA realization using a set of template designs. Real hardware measurements show orders of magnitude higher performance and power efficiency while the programmer only writes 60 lines of code. These encouraging results show that rethinking the hardware/software abstractions from an algorithmic perspective can open new dimensions in system design for Pervasive Hierarchical Intelligence.


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Past Undergraduate Students