Scholar
Ali Jannesari
Google Scholar ID: YhWnhQEAAAAJ
Associate Professor, Iowa State University
high-performance computing
machine learning
parallel computing
software analytics
Follow
Homepage
↗
Google Scholar
↗
Citations & Impact
All-time
Citations
1,531
H-index
20
i10-index
51
Publications
20
Co-authors
13
list available
Contact
Email
jannesari@iastate.edu
Publications
41 items
APQF: Agentic Profiling-Guided Structured Pruning and Mixed-Precision Quantization with Adaptive Fine-Tuning
2026
Cited
0
Interpretable Adaptive Sampling for LLM Test-Time Scaling
2026
Cited
0
Multi-turn RL with Structural and Performance Aware Rewards for CUDA Kernel Generation
2026
Cited
0
VarRate: Training-Free Variable-Rate KV Cache Compression for Long-Context LLMs
2026
Cited
0
ReM-MoA: Reasoning Memory Sustains Mixture-of-Agents Scaling
2026
Cited
0
POTracker: Optimizing Large Language Models for Standard-Compliant Power Outage Report Generation
2026
Cited
0
Sparse Subspace-to-Expert Sharing for Task-Agnostic Continual Learning
2026
Cited
0
LLM-Guided ANN Index Optimization for Human-Object Interaction Retrieval
2026
Cited
0
Load more
Resume (English only)
Academic Achievements
Paper accepted by ACM International Symposium on High-Performance Parallel and Distributed Computing (HPDC 2025)
Paper accepted by ACM International Conference on Supercomputing (ICS 2025)
Paper accepted by Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2025)
Paper accepted by Conference on Neural Information Processing Systems (NeurIPS 2024)
Two papers accepted at International Conference for High Performance Computing, Networking, Storage, and Analysis (SC 2024)
Background
Associate Professor in the Department of Computer Science at Iowa State University
Director of the Software Analytics and Pervasive Parallelism (SwAPP) Lab
Research focuses on the intersection of High-Performance Computing (HPC) and Artificial Intelligence (AI)
Aims to build reliable and efficient software using AI, parallel computing, and HPC
Helps developers utilize modern heterogeneous parallel computing platforms for complex software in data science and HPC
Co-authors
13 total
Felix Wolf
Professor of Computer Science, TU Darmstadt
Co-author 2
Nesreen K. Ahmed
Senior Principal Scientist, Cisco AI Research, Intel Labs, Purdue University
Co-author 4
Co-author 5
Co-author 6
Nathan R. Tallent
Pacific Northwest National Laboratory
Javid Taheri
Professor, Karlstad University (Sweden), Queen's University Belfast (UK)