Yikai Yang

Acting as an Enterprise AI & Automation Engineering Lead within the AI team at Australian Unity, driving key initiatives including: - Define & own the enterprise AI technology target state and co-own the AI & Automation operating model strategy, driving the evolution from traditional automation to agentic AI platforms that enable scalable and intelligent enterprise workflows. - Mentor a high-performing group of AI engineers and AI Champions, guiding AI adoption across teams and building internal capabilities in AI engineering, prompt engineering, and agent-based architectures. - Lead the transformation from traditional RPA automation to agentic AI platforms, introducing multi-agent architectures that enable autonomous workflows integrating LLM reasoning, enterprise systems, and intelligent decision-making. - Collaborate with external researchers to support the development of the organisation’s AI Governance Framework, establishing guardrails, risk controls, and responsible AI practices aligned with enterprise standards.

First AI Engineer joined the Central AI Team, reporting to the Head of AI (Jonathan Byun); contributed to AI strategy and governance framework, and led AI practice including production environment setup and end-to-end AI solution delivery. Leadership & Delivery: - Take the lead in building bespoke Large Language Model (LLM) AI solutions & GenAIOps, open opportunity to save tens of millions in costs annually. - Lead ~8 AI developer, data scientist, software engineer, AI champions to deliver 10 AI solutions from PoC to Production within 12 months (including 2 vendor solution | 2 low code solution | 6 in-house solution). - Lead in building the fundamental AI Production Environment & Code Practice. AI Strategy & Governance: - Contributing in developing AI Strategy Pack & AI Governance Framework with Head of AI and AI Steward, ensuring they aligned with the organization’s strategy and security standards. Stakeholder Engagement & Influence: - Work closely with all major business units in AU for AI innovation, including Retail (private insurance), Home Health, Wealth&Capital Market.Communicate with various stakeholders to understand their business requirements. - Collaborate closely with cross-functional technology teams to lead the successful delivery of the AI solution. (Including cybersecurity, risk, service delivery, cloud, data science, data engineering, and BI development) Tools: Python, langchain, Autogen, SQL, flask, fastAPI, Spark, ETL....... Platform: Azure, AWS, Genesys cloud, Salesforce, Appian..... Other vendor tools: M365 Copilot, AI builder, Copilot studio.......

Founded AI Visibility Lab, a research initiative exploring how small and medium-sized organisations can improve their visibility in AI-generated answers and generative search systems. The lab focuses on emerging techniques in AI search visibility, knowledge graph optimisation, and Generative Engine Optimisation (GEO). If you're interested in our research or would like to learn more about what we're building, feel free to reach out anytime or book a demo at https://aivislab.org

Report to Head of AI (Alexander Wendel), work closly with CEO (Mark Richards), Head of Product (Alex Virgona) Develop the first Vision LLM application in the heavy industry.

Laing O’Rourke spins out Presien since 2020, funded by Main Sequence Ventures and Laing O’Rourke Regular Task: Docker, DVC, CML, CI/CD for ML, Jira, Bitbucket, AWS, Azure..... Fine-tuning pretrained model for real-time object detection

The fellowship is a 6 week residency with 25 of Australia’s top AI Engineers, Hackers and Enthusiasts. The program is supported by Aura Ventures and backed by the likes of AWS, Google, Microsoft, Databricks and Relevance AI, Sahha to name a few!

lead a team of 6 to build whole 3D virtual try on AI system mvp (www.ipomoea.xyz) Utilized Swift to develop an iOS app for automatically generating 3D digital human heads by capturing various facial angles (RGBD). Employed the three.js package to showcase a 3D virtual try-on experience on the website.

Original Standford Incubator Program. ODF14, Gain AI insight from the most talent people, lead a team of 6 to build whole 3D virtual try on AI system mvp (www.ipomoea.xyz) Utilized Swift to develop an iOS app for automatically generating 3D digital human heads by capturing various facial angles (RGBD). Employed the three.js package to showcase a 3D virtual try-on experience on the website.

Gain idea of different projects from the most talent people deal sourcing, community relations, industry research and due diligence

Led the development of novel AI algorithms (Conv-LSTM) and clinical graphical user interface (GUI) software for seizure detection and prediction algorithms in a clinical setting. The software maintained the same accuracy as clinicians while saving more than 10 times in time and cost during the clinical trial.

The Australian E-Health Research Centre (AEHRC) Machine learning/Deep learning for Human Identification in Smart Homes for Aged Care ---Human Identification via CNN from the UWB (ultra-wideband radar) Radar Data ---Develop a new CRNN model achieve the state of art results compare with current famous model structure.

New Technology of 3D TV-Summer Research Project

Winners of the world competition - Neureka 2020 AI Epilepsy Challenge (Second Place)