Structuring the Process of Exploration in AI Research | Bibekananda | AI in The New Era | FEB 2026

Описание: Structuring the Process of Exploration in AI Research

Speaker: Bibekananda Hati
Organization: ExperQuick Research Infra
Conference: AI in The New Era – FEB 2026

Modern computational research has reached a paradoxical state: while compute, GPUs, and storage systems continue to scale rapidly, research velocity itself often does not. The bottleneck is no longer running experiments—it is managing them.

In this session from AI in The New Era (FEB 2026), Bibekananda Hati introduces PyLabFlow, an open-source experiment management framework designed to bring structural order to computational research.

Instead of treating experiments as ad-hoc scripts with logged metrics, PyLabFlow treats experiments as structured, immutable, and queryable systems built from reusable components.

Key Takeaways:
• Why research velocity slows despite increasing compute
• The hidden cost of fragmented experiment management
• How structured experiment frameworks improve reproducibility
• Component-level reproducibility and lineage tracking
• Building scalable and transparent research workflows

This session is ideal for:
• AI Researchers
• ML Engineers
• Infrastructure Engineers
• Open-source Contributors
• Research Workflow Architects

About the Speaker:
Bibekananda Hati holds an MSc in Data Science and focuses on improving reproducibility and decision-making in computational research. He is the creator of PyLabFlow and founder of ExperQuick.org.

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