Systems for ML · GPU Clusters
Heterogeneity-Aware GPU Scheduling
Schedulers that exploit hardware diversity in multi-GPU clusters to minimize DL training time. Combines learned predictors with optimization-based dispatch.
Assistant Professor, Department of Computer Engineering, Kuwait University and Visiting Researcher, Department of Computer Science, Virginia Tech
I build systems for large-scale machine learning: GPU scheduling, tensor caching, and storage efficiency for deep learning training. My ongoing work focuses on the memory wall in LLM training and inference.
About
I am an Assistant Professor in the Department of Computer Engineering at Kuwait University.
My research designs and optimizes systems for large-scale machine learning workloads including GPU scheduling, tensor caching, and storage efficiency for deep learning training. I am broadly interested in the intersection of High Performance Computing, Systems for ML, and ML for Systems.
My ongoing work explores how to improve LLM training and inference in the face of the memory wall, as well as problems at the intersection of systems and privacy-preserving machine learning.
I am currently a Visiting Researcher at Virginia Tech, where I previously completed my Ph.D. in Computer Engineering advised by Dr. Ali R. Butt in the Distributed Systems & Storage Laboratory.
Education
Research
Systems for ML · GPU Clusters
Schedulers that exploit hardware diversity in multi-GPU clusters to minimize DL training time. Combines learned predictors with optimization-based dispatch.
LLM Systems · Memory Wall
Addressing memory bottlenecks in large-model training and inference through heterogeneous resource-aware tensor caching across GPU HBM, CPU DRAM, and NVMe.
Storage · Container Systems
High-performance deduplication for container registries and Docker storage, and LSM-tree stores that integrate local storage with cloud storage for fast, efficient data access.
Emerging · Privacy × Systems
Efficient infrastructure for federated and confidential training workloads at scale, at the intersection of systems design and privacy-preserving machine learning.
Publications
Peer-reviewed publications, reverse chronological. Full list on Google Scholar and ORCID.
Conference Papers
Journal Articles
Teaching
CpE 363
Introduction to Embedded Systems
Fall'23 · Summer'24 · Spring'25 · Summer'25 · Fall'26
CpE 445
Operating System Principles
Fall'23 · Spring'24
ENGR 310
Engineering Ethics
Spring'24 · Fall'24 · Fall'26
CpE 262
Fundamentals of Digital Logic
Fall'24
Community & service
A selection of recent roles; full list in my CV.
Program Committees
Leadership & Outreach
Contact