Akshitha Sriraman

Akshitha Sriraman

Assistant Professor

Carnegie Mellon University

I am an Assistant Professor in the Department of Electrical and Computer Engineering at Carnegie Mellon University. My research interests are in the area of bridging computer architecture and software systems, with a focus on making hyperscale data centers more efficient (via solutions that span the systems stack). The central theme of my work is to (1) design software that is aware of new hardware constraints/possibilities and (2) architect hardware that efficiently supports new hyperscale software requirements. I have been recently exploring ideas on designing “customized” hardware that can still generically support diverse applications, compiler-driven hardware design optimizations, novel software threading designs, and efficient I/O subsystems.

My systems solutions to improve hardware efficiency have been deployed in real hyperscale data centers and currently serve billions of users, saving millions of dollars and meaningfully reducing the global carbon footprint. Additionally, my hardware design proposals have influenced the design of Intel’s Alder Lake (Golden Cove and future generation) CPU architectures and Intel’s Infrastructure Processing Unit.

My research has been recognized with an IEEE Micro Top Picks distinction. I was also awarded a Facebook Fellowship, a Rackham Merit Ph.D. Fellowship, and a CIS Full-Tuition Scholarship. I was selected to attend the Rising Stars in EECS Workshop and the Heidelberg Laureate Forum. I completed my Ph.D. in Computer Science and Engineering at the University of Michigan and my MS in Embedded Systems at the University of Pennsylvania.

Prospective students: I am currently looking for motivated graduate students, postdoctoral scholars, and undergraduate researchers. If you are interested in working with me, please send me an email with (1) your CV, (2) your transcript, (3) thoughts about why my research excites you, and (4) thoughts about what you'd like to work on, to start a conversation. Additionally, if you are able to comment on the strengths, weaknesses, and opportunities on my OSDI '18, ISCA '19, or ASPLOS '20 papers, it'll be easier for me to recruit you. You can find out more about my work and vision through my Ph.D. dissertation (especially the section on my plans for future work).


  • PhD in Computer Science, 2021

    University of Michigan

  • M.S. in Embedded Systems, 2015

    University of Pennsylvania