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About
Vasilis Gkolemis is a researcher at the forefront of operationalizing artificial intelligence, with a primary focus on AI operations (AIOps), data-centric AI, and human-in-the-loop systems. His most cited work, "Bridging Data and AIOps for Future AI Advancements with Human-in-the-Loop. The AI-DAPT Concept" (2024), introduces a transformative framework that repositions data as the cornerstone of AI model development and deployment. Gkolemis argues that while data critically determine model performance, fairness, and robustness, they are frequently undervalued in AI pipelines. His AI-DAPT concept directly addresses this gap by integrating human oversight into automated data management and AI operations, ensuring that models remain adaptive, accountable, and aligned with real-world requirements. Though early in its citation trajectory, this work has already established Gkolemis as a thought leader in bridging the gap between data engineering and AI lifecycle management. His contributions are particularly significant for researchers and practitioners seeking to build more reliable, transparent, and human-centered AI systems—a pressing need as AI transitions from controlled research environments to high-stakes, production-level deployments.
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