collaborators

5 papers

cs.SE2026

An Empirical Investigation of Pre-Trained Deep Learning Model Reuse in the Scientific Process

Nicholas M. Synovic, Karolina Ryzka, Alessandra V. Vellucci Solari +3

Deep learning has achieved recognition for its impact within natural sciences, yet the prohibitive financial and technical cost of training models from scratch inhibit adoption. Fo…

cs.SE2026

SysLLMatic: Large Language Models are Software System Optimizers

Huiyun Peng, Arjun Gupte, Ryan Hasler +7

Automatic software system optimization can improve software speed, reduce operating costs, and save energy. Traditional approaches to optimization rely on manual tuning and compile…

cs.SE2026

Beyond Local Code Optimization: Multi-Agent Reasoning for Software System Optimization

Huiyun Peng, Parth Vinod Patil, Antonio Zhong Qiu +2

Large language models and AI agents have recently shown promise in automating software performance optimization, but existing approaches predominantly rely on local, syntax-driven…

cs.SE2026

AgentHub: A Registry for Discoverable, Verifiable, and Reproducible AI Agents

Erik Pautsch, Tanmay Singla, Parv Kumar +6

LLM-based agents are rapidly proliferating, yet the infrastructure for discovering, evaluating, and governing them remains fragmented compared to mature ecosystems like software pa…

cs.CY2024

Can Large-Language Models Help us Better Understand and Teach the Development of Energy-Efficient Software?

Ryan Hasler, Konstantin Läufer, George K. Thiruvathukal +5

Computing systems are consuming an increasing and unsustainable fraction of society's energy footprint, notably in data centers. Meanwhile, energy-efficient software engineering te…