activity
20232025
most citedSustainability of Data Center Digital Twins with Reinforcement Learning

25 citations · 32 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2025

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…

cs.CV2025

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…

cs.LG20242 cited

Robustness and Visual Explanation for Black Box Image, Video, and ECG Signal Classification with Reinforcement Learning

Soumyendu Sarkar, Ashwin Ramesh Babu, Sajad Mousavi +3

We present a generic Reinforcement Learning (RL) framework optimized for crafting adversarial attacks on different model types spanning from ECG signal analysis (1D), image classif…

cs.LG20243 cited

A Configurable Pythonic Data Center Model for Sustainable Cooling and ML Integration

Avisek Naug, Antonio Guillen, Ricardo Luna Gutierrez +5

There have been growing discussions on estimating and subsequently reducing the operational carbon footprint of enterprise data centers. The design and intelligent control for data…

cs.AI20241 cited

Function Approximation for Reinforcement Learning Controller for Energy from Spread Waves

Soumyendu Sarkar, Vineet Gundecha, Sahand Ghorbanpour +5

The industrial multi-generator Wave Energy Converters (WEC) must handle multiple simultaneous waves coming from different directions called spread waves. These complex devices in c…

cs.DC202425 cited

Sustainability of Data Center Digital Twins with Reinforcement Learning

Soumyendu Sarkar, Avisek Naug, Antonio Guillen +4

The rapid growth of machine learning (ML) has led to an increased demand for computational power, resulting in larger data centers (DCs) and higher energy consumption. To address t…