About Me

I'm a computer scientist, software engineer, researcher, and now Co-Founder and CTO at Influxion Technologies. My interests span self-adaptive systems, goal-oriented software, dynamic resource optimization, and fault-tolerant/long-lived systems. I spent over a decade in systems research, most recently as a Research Computer Scientist at the USC Information Sciences Institute, and my work has been recognized in top systems and architecture venues.

At Influxion, I'm applying my expertise to help businesses manage—and optimize—their AI deployments. I’m excited to help make AI easier and more cost-effective for everyone!

Recent News

2025

Highlights

  • I'm co-founding a startup! Stay tuned for details.
  • Our paper "TRACER Software Switching at Waveform Timescales" was accepted to the IEEE High Performance Extreme Computing Virtual Conference (HPEC 2025).
  • Our paper "TRACER, the Next Generation Ultra-wideband Spectrum Processor" was accepted to the IEEE Military Communications Conference (MILCOM 2025).

2024

Highlights

  • Our paper "Timely Wildfire Perimeter Mapping for Unmanned Aerial Platforms" was presented and published in the 2024 Optica Imaging Congress (due to a scheduling conflict in 2023).
  • Our paper "Evaluating Deep Learning Recommendation Model Training Scalability with the Dynamic Opera Network" was accepted to The 4th Workshop on Machine Learning and Systems (EuroMLSys).
  • I've been promoted to Research Computer Scientist!

Software Releases

2023

Highlights

  • We shared the Best Paper Award at FMEC 2023!
  • Our extended abstract "Deep Learning Recommendation Model Training Co-design with the Dynamic Opera Network" was accepted to the IEEE Conference on High Performance Extreme Computing (HPEC 2023) for a poster presentation.
  • Our paper "Distributed Edge Machine Learning Pipeline Scheduling with Reverse Auctions" (a collaboration with Dave King at AFIT) was accepted to the IEEE International Conference on Fog and Mobile Edge Computing (FMEC 2023).
  • Our summary paper "Timely Wildfire Perimeter Mapping for Unmanned Aerial Platforms" was accepted for presentation at the 2023 Optica Imaging Congress.
  • Our "QuantPipe" paper on using post-training quantization to adapt to dynamic network conditions in distributed transformer pipelines was accepted to the 2023 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP).

Software Releases

2022

Highlights

  • Pervaiz et. al.'s paper "GOAL: Supporting General and Dynamic Adaptation in Computing Systems" was accepted to The ACM SIGPLAN Symposium on New Ideas, New Paradigms, and Reflections on Programming and Software (SPLASH Onward! 2022).
  • Our "PipeEdge" paper on pipelining large machine learning transformers across heterogeneous edge devices was accepted to Euromicro Digital System Design (DSD) 2022 special session on Applications, Architectures, Methods and Tools for Machine – and Deep Learning (AAMTM).

Software Releases

2021

Highlights

  • Our CASPER project paper on using the Halide programming language for HPC Synthetic Aperture Radar processing received an Outstanding Paper Award at HPEC 2021!
  • Oak Ridge National Lab published an article about our CASPER project. The article was also picked up by HPCwire.

Software Releases

2020

Highlights

  • Our paper on characterizing a large-scale NUMA shared memory system (an HPE SuperDome Flex) was accepted to the HiPar workshop at SC20 (Supercomputing 2020).
  • Our paper on CASPER's design was accepted to the ESPM2 workshop at SC20 (Supercomputing 2020).

Software Releases

2019

Highlights

  • We are working on CASPER (Compiler Abstractions Supporting high Performance on Extreme-scale Resources) for the DARPA PAPPA microexploration program.
  • Our "CoPPer" paper received the Karsten Schwan Best Paper Award at ICAC 2019!
  • Our paper Proteus: Language and Runtime Support for Self-Adaptive Software Development appeared in the March-April edition of IEEE Software.

Software Releases

2018

Highlights

  • As part of the NASA High Performance Spaceflight Computing project, we are designing and prototyping the systems sofware for a heterogeneous multicore fault-tolerant System-on-Chip.
  • I am presenting our paper Energy-efficient Application Resource Scheduling using Machine Learning Classifiers at ICPP 2018.
  • I am now working at USC/ISI in Arlington, VA!

Software Releases

Education

Ph.D., Computer Science, University of Chicago, 2018.
Dissertation: Balancing Performance and Energy in Computing Systems [pdf]
Committee: Henry Hoffmann, Shan Lu, Steven Hofmeyr

M.S., Computer Science, University of Chicago, 2015.
Thesis: Managing Diversity in Performance and Energy Characteristics on Embedded Systems [pdf]

B.S., Computer Engineering and Computer Science, University of Southern California, 2008.