Su J.

Most enterprise AI projects fail silently in production. Deploying a production-ready, fault-tolerant AI architecture is hard. Uncontrollable hallucinations, compounding token costs, and catastrophic memory loss across process restarts turn LLM experiments into expensive sunk costs. As a Ph.D. in AI Research with 5 years of frontline industrial R&D experience (formerly at Fujitsu & KDDI), I audit failing AI infrastructures, decouple perception from cognition, rescue broken Agentic pipelines. I then translate these hard-won fixes into project-based training, so your team learns to build reliable systems, not just prototypes. [Credibility & Authority] • Global Academic Authority: Ph.D. in AI from Kyushu University. First author of an IEEE TEVC Outstanding Paper (3,500+ citations, featured by BBC News & Hacker News) on deep neural network vulnerabilities. • Enterprise R&D Track Record: Former Researcher at Fujitsu Ltd. and KDDI Research. Specializing in translating complex academic theories into highly robust, commercial-grade visual recognition. Former Tech lead at famous global startups., operating closely with former members from AMAZON, GOOGLE, NASA etc to build a proprietary multimodal foundation model from scratch. • Cross-Border Tech Liaison: I seamlessly conduct technical due diligence and align complex architectural specifications across global engineering teams and management boards. • Deep Experience in AI Training: I design and implement comprehensive, project-based AI training programs tailored for both technical development teams and non-technical enterprise staff. Drawing from my experience as an internal corporate AI instructor, I provide end-to-end educational solutions ranging from curriculum planning and proprietary material development to live lecturing and one-on-one hands-on coaching. [Core Consulting Solutions] 1. AI-OCR System Rescue & Pipeline Re-engineering I specialize in rebuilding failing document processing pipelines due to serious hallucinations. I dismantle complex, untraceable monolithic prompts and re-engineer them into explicit, multi-agent workflows. By decoupling tasks based on complexity and volume, I design and deploy targeted sub-agents, specialized tool nodes, and confidence-based routing mechanisms. This optimized serial and parallel orchestration—coupled with rigorous task-specific evaluation metrics, completely eradicates the chronic hallucinations, token waste, and low usability inherent in raw multimodal OCR deployments. 2. Agentic RAG Architecture & AI Cost Optimization I perform deep Technical Due Diligence on current AI infrastructure. I have previously guided enterprise IT teams to bypass overpriced, opaque third-party wrappers, and reduce monthly AI operational costs by 75% while significantly mitigating data toxicity. 3. Vision Foundation Models & Specialized PoC Commercialization Leveraging my background in engineering spatio-temporal large vision models from scratch, I design robust architectures for specialized domains, including large-scale satellite imagery analysis and medical deep learning systems for disease recognition. I guide the strategic direction from edge-case data preprocessing to specialized fine-tuning and cloud-native commercial deployment. 4. Enterprise AI Curriculum Design & Technical Mentorship Drawing on my deep engineering background and extensive experience as an internal corporate educator across top-tier enterprises(3 curriculums, 64 hours+ in total), I design and deliver highly customized, project-based AI masterclasses. I bypass generic tutorials to address real-world business pain points, guiding engineering teams to build GraphRAG-enabled chatbot agents from scratch or optimize workflows for their specific operational needs. From cross-departmental technical alignment to executive-level strategic workshops, I handle end-to-end curriculum planning, material development, and hands-on technical mentoring. 5. Scalable Human-Object Interaction (HOI) Architecture Traditional HOI models fail to capture true interaction semantics and struggle to generalize to unseen classes. I spearhead zero-to-one R&D and commercial deployment of advanced anomaly detection architectures for large-scale retail and manufacturing environments. By integrating multimodal architectures and contrastive learning, I resolve foundational bottlenecks in generalization, enabling highly robust anomaly detection for complex physical operations and bridging the gap between academic theory and pragmatic industrial applications. KEYWORDS: - Artificial Intelligence - Agentic RAG Architecture - Technical Due Diligence - AI Cost Optimization - Multi-Agent Orchestration - Multimodal Vision Foundation Models - Vision-Language Models - Enterprise AI Mentorship - AI Curriculum Development - Corporate AI Training Struggling pipeline or unsure about training? Describe your bottleneck, then I'll give a candid, no-obligation diagnostic.