Pavani

Pavani Kuppili

Research Assistant · University of Utah · Salt Lake City

pavani.kuppili@utah.edu · CV · GitHub · Google Scholar · LinkedIn


About me

Hi there!

My name is Pavani Kuppili, PhD student at the University of Utah, advised by Prof. Robert Ricci. My primary research interests are broadly in the areas of Programmable Networks, Data Center Networking, and Network Measurements. I am actively working on programming Tofino switches and FPGA-SmartNICs using P4. I collaborate with Prof. Michael Zink at the University of Massachusetts, Amherst, and Prof. Miriam Leeser at Northeastern University.
Prior to starting my PhD, I was a Master's student at the University of Utah where I had the opportunity to work with Prof. Ryan Stutsman. I have a Bachelor degree in Electronics and Communication Engineering from National Institute of Technology (NIT) Silchar, India.
I have previously worked at Amazon with AWS EC2 team as a Cloud Engineer where I explored hands-on a vast spectrum of AWS Services. Later, I worked as a Systems Development Engineer at Amazon where I was part of the Amazon global websites' Cloud Hosting team.


Events/Updates


Research

I build high-performance, resilient datacenter networks by programming Tofino switch ASICs and FPGA-SmartNICs in P4. I also have a soft spot for very large network logs—digging through them, tweaking measurement knobs, and seeing what the data is trying to confess.
Currently, my research focuses on prototyping and evaluating systems that bypass traditional application performance limits. I do this by offloading critical functions to programmable hardware (like AMD Pensando and NVIDIA BlueField DPUs) using acceleration frameworks such as DPDK, RDMA, and eBPF.
If you’re exploring anything in this space (or have a wild idea that might work), I’m always happy to collaborate.


Publications

  1. LatencyLab: A DPDK-Based P4 Pipeline Latency Measurement Framework for FPGA SmartNICs
    Pavani Kuppili, Yichen Qian, Suranga Handagala, Mike Zink, Miriam Leeser, Robert Ricci
    HPEC, 2026
  2. Poster: Topocloud: Getting Datacenter Network Experiments Into the Right Shape
    Pavani Kuppili; Aleksander Maricq; Brent E. Stephens; Ryan Stutsman; Robert Ricci
    ICNP, 2024
  3. Multi-attached network topology with different routing protocols and stub network resolution in OSPF routing
    Pavani Kuppili; Himanshu Mishra; Ramkumar Karsh
    MCCS, 2018
  4. Design and Analysis of QoS based Optimized Novel Optical Network Emulator for WDM Technology
    Pavani Kuppili; S. K. Tripathy; P. Puspa Devi
    ICCS, 2019

Work Experience

University of Utah

Salt Lake CIty · August 2023 – Present

Research Assistant - Flux Research Group

University of Massachusetts at Amherst

May 2024 – August 2024
May 2025 – August 2025
June 2026 – August 2026

Cloud Testbed Development Intern

Amazon Development Center, India(ICON)

January 2022 – July 2022

Systems Development Engineer

  • Designed automated scaling scripts in Javascript to address downtimes of Amazon Retail Website and could resolve over 70% of on-call tasks.
  • Executed the 100% live migration of Amazon Retail Website across global regions from legacy load balancers to AWS ELBs.

Amazon Web Services, India(EC2 Linux)

May 2019 – January 2022

Cloud Engineer

  • Debugged a critical bug in AWS SSM Agent and collaborated with cross-functional teams to enable integration of Custom OS logs with CloudWatch; mitigated 100% Custom OS SSM logging errors.
  • Resolved over 1000 customer cases, architecting multi-tier cloud solutions on AWS, optimizing resources, infrastructure costs, and performance.
  • Troubleshot and resolved AWS EC2 level critical performance and application issues by re-configuring Linux operating systems on cloud using CPU, Memory, Storage, and Network metric analysis, and optimizing system utilization.

Skills

Programming

P4, Python, C, Bash, Shell, SQL, Go, OpenMP, CUDA, MPI, Java, JavaScript, HTML, CSS

Systems/Networks

Tofino, VitisNetP4, Xilinx Open-NIC-Shell, Linux, AWS, Docker, GitHub, MapReduce, Network Monitoring, Network Performance, Firewalls, Virtualization, OS Logging, Authentication, GNS3, Wireshark

AI

Core ML, Supervised and Unsupervised learning, Ensemble methods, Neural Networks, CNN, Sklearn, ApacheSpark, MongoDB, Postgres, JupyterLab


Honors & Achievements


Course Work

  • Manage Data for & with ML(CS 6964) - Spring 2026
  • Machine Learning(CS 6350) - Spring 2025
  • Advanced Computer Networks(CS 6480) - Fall 2023
  • Software and System Security(CS 6956) - Spring 2023
  • Software Verification(CS 6110) - Spring 2023
  • Distributed Systems(CS 6450) - Fall 2022
  • Parallel Programming(CS 6230) - Fall 2022
  • Computer Architecture(CS 6810) - Fall 2022

Hobbies