CV & Résumé
Technical résumé
Detailed curriculum vitae
The web version below provides a quick, accessible overview of the full academic CV.
Research interests
Dependable AI and large language model resilience; fault tolerance and reliability for high-performance computing; scientific data compression; hardware–software co-design; and machine learning systems.
Education
- Expected May 2027
Ph.D. in Computer Engineering · University of Florida
GPA: 3.93 / 4.00 · Advisor: Prof. Guanpeng Li
- Aug 2025
Master of Computer Science · The University of Iowa
GPA: 3.99 / 4.00
- May 2023
B.S. in Computer Science · Lahore University of Management Sciences
GPA: 3.61 / 4.00
Research experience
Argonne National Laboratory
Visiting Graduate Researcher · Lemont, Illinois
- Designed an end-to-end hardware–software co-design framework for FPGA/CPU scientific data compression at the Advanced Photon Source, achieving up to 19.8× cycle speedup over matched software and 46–65% lower end-to-end workflow time.
- Developed a modular Chisel/RTL compression library supporting LZ4, Snappy, StreamVByte, SZ3, SZp, SZx, zfp, and extensible new designs.
University of Florida
Graduate Research Assistant · Dependable Systems Lab
- Developed TRACE, a runtime detector for silent data corruption during LLM inference, achieving 95.3% average detection coverage across 15 LLMs and 3 datasets with 0.56% runtime overhead; paper accepted at SC26.
- Characterizing the resilience of LLM inference, pretraining, and parameter-efficient fine-tuning to transient hardware faults, including models fine-tuned with LoRA, QLoRA, LoRA-FA, and DoRA.
The University of Iowa
Graduate Research Assistant · Iowa City, Iowa
- Developed an LLVM-based silent-error detector for scientific and HPC applications using selective monitoring of informative program locations, achieving 86.19% average detection coverage at 4.90% runtime overhead across 15 benchmarks.
- Compared compiler- and runtime-based error-detection techniques across scientific workloads, analyzing their behavior under different fault-propagation patterns and quantifying trade-offs between detection coverage and runtime overhead.
Publications
- Abdullah Naveed, Mahina Sheikh, and Guanpeng Li. “Low-Overhead Silent Error Detection for Large Language Model Inference at Scale.” SC ’26, 2026. Accepted; to appear.
- Darren Ng, Abdullah Naveed, Duo Zhang, Guanpeng Li, Sheng Di, and Xiaoyi Lu. “Z-SPDK: Accelerating Lossy Compressed I/O on NVMe-SSDs.” SC ’26, 2026. Accepted; to appear.
- Muhammad Hassan, Talha Tahir, Muhammad Farrukh, Abdullah Naveed, et al. “Evaluating Container Debloaters.” IEEE SecDev 2023, pp. 88–98.
Manuscripts under review
- 2026
LLM Pretraining Reliability
Large-scale characterization of transient soft-error effects and resilience during Transformer pretraining.
- 2026
LLM Fault Resilience
Study of LLM behavior under increasing fault intensity, multi-bit corruption, and emerging high-error computing environments.
- 2026
HPC Reliability
Compiler-based, low-overhead detection of silent errors in scientific and HPC applications.
Teaching experience
- Aug–Dec 2023
Teaching Assistant · Database Systems
The University of Iowa · Guided 30+ students in schema design, query formulation, debugging, and MySQL project implementation.
- Sep 2022–Jan 2023
Teaching Assistant · Data Structures
Lahore University of Management Sciences · Led tutorials for 100+ students in data structures, algorithms, programming, and problem solving.
Selected technical projects
- NLP · Vision
Multimodal Fake News Classification
Integrated textual and visual representations to classify misleading content across language and image modalities.
- Robotics · LLMs
Cozmo’s Star Wars Odyssey
Combined character recognition, LLM-driven narrative generation, and question answering for context-aware robot interaction.
- PyTorch · OpenCV
COVID SOP Violation Detection
Built a real-time multi-camera pipeline with YOLOv5 detection, top-view projection, and spatial density heatmaps.
- React Native · Firebase
LUMS Mobile App
Developed a cross-platform student portal for deadlines, GPA calculation, communication, and real-time cloud-backed data management.
Technical skills
ProgrammingPython, C, C++, Bash, SQL, Scala, JavaScript, Git
Machine learning / AIPyTorch, Hugging Face Transformers, TensorFlow/Keras, scikit-learn, OpenCV
HPC / parallel computingMPI, OpenMP, Slurm, large-scale CPU/GPU experimentation, fault injection, resilience analysis
Hardware / systemsChisel, Verilog/RTL, Chipyard, RISC-V, Verilator, Vivado, LLVM, Linux, Docker
Scientific computing / data analysisNumPy, Pandas, Matplotlib, Jupyter, MATLAB
Professional service
- Conference reviewer / subreviewer for SC, DSN, ICS, AAAI, and HPDC.
- Contributing team member to the ProdeBench benchmarking project, supporting implementation and experimental evaluation.
Academic CV preview
If the preview does not load, open the PDF in a new tab.