Yue LI

• Collaborated with product managers and business analysts to define KPIs and success metrics, aligning ML models with strategic objectives. • Led the implementation of serverless ETL pipelines (GCP, BigQuery) to process raw data into business‑ready datasets for real‑time machine learning inference (latency < 5 ms). • Produced dashboards and presentations for product and executive teams to drive data‑informed decisions. • Delivered end‑to‑end ML lifecycle management including data validation, model training, deployment, and monitoring. • Conducted client‑style workshops internally to gather requirements, translate them into actionable technical tasks, and prototype solutions.

• Led end‑to‑end delivery of a regulated financial platform, including requirements gathering, compliance alignment, and solution rollout. • Facilitated client workshops to define functional specifications and align technical architecture with business processes. • Collaborated with stakeholders to gather requirements and design a machine learning‑based recommendation engine aligned with CRM workflows and client segmentation needs. • Delivered technical documentation, test plans, and validation reports in line with industry‑standard practices.

• Directed collaborative AI projects with external partners, including an event matchmaking engine based on real‑time user behavior. • Delivered a network intrusion detection system using ML models, integrating cybersecurity requirements with advanced data science. • Designed and delivered technical training sessions for 50+ engineering students on AI, data pipelines, and model deployment, bridging academic knowledge with real‑world use cases. • Collaborated with external stakeholders (industry and startups) to define project requirements and deliver working prototypes.

• Built predictive models on Hadoop/Spark clusters in a real‑time streaming context. • Deployed algorithms using Docker and Kubernetes in production settings.

• Collaborated within the EU Fed4FIRE+ consortium, working closely with multiple European partners to define work packages, responsibilities, and project milestones. • Presented solution architectures and technical approaches to consortium members, ensuring alignment across diverse stakeholders. • Contributed to the integration of experimental network platforms, enabling interoperability across federated testbeds.

• Contributed to the EU FP7 COMBO project, collaborating with multiple industrial and academic partners to define work packages and ensure alignment across deliverables. • Actively participated in dissemination of project results, including technical presentations, reports, and publications targeted at both technical and non‑technical audiences. • Delivered prototypes, technical documentation and patents to industrial stakeholders within collaborative innovation frameworks. • Organised and led training and teaching sessions, developing strong presentation, coaching, and knowledge transfer skills.

• Study data consistency in Amazon Dynamo and Apache Cassandra • Study the MapReduce and Hadoop framework • Propose and implement an algorithm to optimize energy consumption in Cloud Computing, and deploy it on Grid’5000 (Perl, Python)

• Work in AGILE mode and with Scrum for iterative development • Develop new features for the SaaS solution and enhance existing ones using Eclipse, JAVA, and REST • Propose simple, maintainable, relevant, and scalable technical solutions • Contribute to functional and architectural discussions, with a focus on ergonomics (HTML, CSS, JavaScript), performance, and simplicity • Maintain and update the virtual server under Linux using Shell BASH