CS Prof Shahbaz Recruiting Undergrads for PhD Research
I am looking for amazing Ph.D. students to join my group at Purdue University in Fall 2023. The world of computing systems is changing; email me and apply here if you are interested in driving this change with me at Purdue University! It will be a fully-funded opportunity, if selected.
A little about myself.
Muhammad Shahbaz is a Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor in Computer Science at Purdue University. His research focuses on designing and developing domain-specific abstractions, compilers, and architectures for emerging workloads (including machine learning and self-driving networks). Shahbaz received his Ph.D. and M.A. in Computer Science from Princeton University and B.E. in Computer Engineering from the National University of Sciences and Technology (NUST). Before joining Purdue, Shahbaz worked as a postdoc at Stanford University and a Research Assistant at Georgia Tech and the University of Cambridge. Shahbaz has built open-source systems, including Pisces, SDX, and NetFPGA-10G, that are widely used in industry and academia. He received the Facebook, Google, and Intel Research Award; IETF/IRTF ANRP Prize; ACM SOSR Systems Award; APNet Best Paper Award; Best of CAL Paper Award; Internet2 Innovation Award; and Outstanding Graduate Teaching Assistant Award.
For prospective students.
Prof. Shahbaz is looking for graduate students to join his lab at Purdue CS, specifically focusing on applying networking, systems, architecture, and machine-learning concepts to tackle some of the most challenging problems in the computing landscape today. Some key focus areas are (the list non-exhaustive):
- Serverless Computing and 5G
- Help move today's rigid access infrastructure to the cloud by making novel innovations in serverless computing for emerging 5G applications with strict performance needs.
- What's in for the students? Other than publications, chance to work with an amazing team of researchers from Intel Labs who are working at the forefront of this emerging new area.
- Self-Driving Networks
- Designing and building hardware prototypes and language abstractions to run ML operations at line rate in datacenter switches.
- Developing new and novel ML algorithms to replace datacenter heuristics (such as load balancing, routing, and congestion control) with learned functions.
- What's in for the students? Other than publications, opportunity to work with a stellar team of experts from Stanford, Facebook, SambaNova Sytems, and Barefoot Networks.
- Networks for Machine Learning
- Exploiting domain-specific characteristics of the cloud infrastructure to scale ML training and inference at the datacenter scale.
- What's in for the students? Other than publications, the ability to make a strong impact by working closely with experts from Nvidia (Mellanox) and more.
- Cloud-Native CPU Architectures
- Current CPUs still follow the decade-old architecture from 50 years ago, designed to run monolithic applications really fast with the best average performance. However, in today’s cloud-native landscape, applications are made of a number of microservices, requiring the best tail performance. In this project, we are looking into designing new domain-specific CPU architectures with a full-stack software suite tailored for cloud-native applications.
- What's in for the students? Other than publications, an opportunity to work on the bleeding edge of systems and architecture with renowned architects from industry and academia and to help change industry best practices.
- And many more ideas …
If interested, please reach out to me. (Email is the best means of communication.)
Kevin C. and Suzanne L. Kahn New Frontiers Assistant Professor
Computer Science, Purdue Universitymshahbaz@purdue.edu