Sergio Verga

AI Engineer | ML Engineer

Sergio VergaBuilding reliable data and AI pipelines for LLMs, robotics, and analytics.

AI/ML engineer with an MSc in Data Science and a BSc in Physics. I design data pipelines, evaluation loops, and LLM/RAG workflows that move research prototypes into reliable systems.

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Featured Projects

A focused snapshot of recent work spanning robotics, computer vision, and GenAI pipelines.

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Automatic KPI Interpretation with Multimodal LLMs

Automatic KPI Interpretation with Multimodal LLMs

Interpreting business KPI dashboards with multimodal LLMs inside KNIME.

  • - Built a modular LLM workflow to explain KPI shifts with structured summaries.
  • - Highlighted anomalies and trends using multimodal dashboard inputs.
  • - Delivered consistent, human-readable explanations for stakeholders.
GenAIKNIMELLMAnalytics
KNIME Hub
Vision-Language-Action (VLA) Models for Robotics

Vision-Language-Action (VLA) Models for Robotics

Multimodal agents for robotic pick-and-place following prompt-specified features.

  • - Research activity (band 25CE114) with currently private repositories (paper under submission).
  • - Benchmarked teleoperation interfaces (with 1-to-1 kynematic map) to train Imitation Learning models.
  • - Experimented extensions of ACT model to support multi-tasking.
RoboticsVLAMultimodalDatasetEvaluation
LeRobotLeRobot Docs

Experience

Research and engineering roles with a focus on data pipelines, evaluation, and ML systems.

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Intelligent Sensing Lab (ISLab), Univ. of Milano-Bicocca logo

External Research Collaborator (AI for Robotics)

Intelligent Sensing Lab (ISLab), Univ. of Milano-Bicocca
Mar 2025 - Oct 2025
  • - Research project: “Data Collection and Analysis of Human–Machine Interaction in the Context of Industry 5.0” (Cod. 25CE114).
  • - Part of HOMEY – A Human-centric IoE-based Framework for Supporting the Transition Towards Industry 5.0 (PRIN 2022, ID 2022-NAZ-0329/PER, funded by the EU – NextGenerationEU).
  • - Collected and analyzed human-robot interaction data using the LeRobot framework.
  • - Extended ACT policy models with visual task encoding, evaluated multi-task learning performance, and benchmarked wearable-sensor-based control (Movella Xsens Dot) vs. leader-arm teleoperation.

Writing

Short technical pieces on analytics, KPI interpretation, and ML applications.

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Contact

Open to data engineering and AI engineering roles, collaborations, and research projects.

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