Thirty-third IEEE International Conference on Software Analysis, Evolution and Reengineering (SANER-26)
Evaluation of Data Quality Disparity and Implications for Fair Machine Learning
fairnessdata qualitybias
Authors
Mohit Sharma*, Pratik Mishra*, Sandeep Hans, Abhijnan Chakraborty, Vijay Arya
Mohit Sharma and Pratik Mishra contributed equally to this work.
Abstract
The performance of machine learning (ML) models heavily depends on the quality of the data they are trained on. While prior work often treats data quality as uniform across a dataset, we investigate whether it varies across different population subgroups within a dataset and examine its implications, a phenomenon we refer to as Data Quality Disparity (DQD). Our analysis reveals that many real-world datasets inherently exhibit DQD with underrepresented or marginalized groups...
Thirty-Eighth Annual Conference on Innovative Applications of Artificial Intelligence (IAAI-26)
NOVAID -- Natural-language Observability Visualization Assistant for ITOps Dashboard Widget Generation
aiopsllmvisualization
Authors
Pratik Mishra, Caner Gözübüyük, Seema Nagar, Prateeti Mohapatra, Raya Wittich, Arthur de Magalhaes
Abstract
Manual creation of IT monitoring dashboard widgets is slow, error-prone, and a barrier for both novice and expert users. We present NOVAID, an interactive chatbot that leverages Large Language Models (LLMs) to generate IT monitoring widgets directly from natural language queries. Unlike general natural language–to-visualization tools, NOVAID addresses IT operations–specific challenges -- specialized widget types like SLO charts, dynamic API-driven data retrieval, and complex contextual filters...
2024 IEEE 17th International Conference on Cloud Computing (CLOUD)
Optimizing Cloud Workloads - Autoscaling with Reinforcement Learning
clouddevopsrl
Authors
Pratik Mishra, Sandeep Hans, Diptikalyan Saha, Pratibha Moogi
Abstract
By 2027, over 50 % of enterprises are expected to adopt industry cloud platforms, driving potential EBITDA value of $3 trillion by 2030. In this landscape, software providers rely on Infrastructure-as-a-Service (IaaS) providers to access tailored virtualized resources based on usage. Optimizing resource utilization is crucial to reducing operating costs and maintaining quality standards for SaaS and IaaS providers. This creates an essential need for dynamic scaling mechanisms to adjust resources according to workload variations...