25 citations · 50 across the 19 of their papers we have counts for
7 papers · 1 filter
Fast 3D Surrogate Modeling for Data Center Thermal Management
Soumyendu Sarkar, Antonio Guillen-Perez, Zachariah J Carmichael +6
Reducing energy consumption and carbon emissions in data centers by enabling real-time temperature prediction is critical for sustainability and operational efficiency. Achieving t…
DCcluster-Opt: Benchmarking Dynamic Multi-Objective Optimization for Geo-Distributed Data Center Workloads
Antonio Guillen-Perez, Avisek Naug, Vineet Gundecha +8
The increasing energy demands and carbon footprint of large-scale AI require intelligent workload management in globally distributed data centers. Yet progress is limited by the ab…
LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers
Avisek Naug, Antonio Guillen, Vineet Kumar +7
Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock gre…
Robustness Evaluation for Video Models with Reinforcement Learning
Ashwin Ramesh Babu, Sajad Mousavi, Vineet Gundecha +5
Evaluating the robustness of Video classification models is very challenging, specifically when compared to image-based models. With their increased temporal dimension, there is a…
Coordinated Robustness Evaluation Framework for Vision-Language Models
Ashwin Ramesh Babu, Sajad Mousavi, Vineet Gundecha +5
Vision-language models, which integrate computer vision and natural language processing capabilities, have demonstrated significant advancements in tasks such as image captioning a…
Hierarchical Multi-Agent Framework for Carbon-Efficient Liquid-Cooled Data Center Clusters
Soumyendu Sarkar, Avisek Naug, Antonio Guillen +7
Reducing the environmental impact of cloud computing requires efficient workload distribution across geographically dispersed Data Center Clusters (DCCs) and simultaneously optimiz…
Reinforcement Learning Platform for Adversarial Black-box Attacks with Custom Distortion Filters
Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi +5
We present a Reinforcement Learning Platform for Adversarial Black-box untargeted and targeted attacks, RLAB, that allows users to select from various distortion filters to create…