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sunbc0120/README.md

Baichuan Sun, Ph.D.

Lead GenAI Engineer @ Google APAC

Orchestrating the Frontier of Enterprise Intelligence & Infrastructure Economics

Bridging Deep R&D, Corporate Strategy, and Production-Grade Engineering


🌐 The Convergence of Intelligence & Strategy

I architect the bridge between scientific rigor and sustainable business value. My work centers on translating the kinetic energy of frontier AI research into the potential energy of enterprise transformation. From computational physics to boardroom decision-making and hyperscale cloud AI engineering, I navigate the full stack of modern intelligence.


πŸš€ Current Focus: Frontier GenAI & Reasoning

At Google, I advise APAC’s enterprise C-suites on the sovereign adoption of Generative AI, focusing on:

  • Agentic Data Engines: Moving beyond simple RAG into autonomous, multi-modal reasoning loops.
  • Infrastructure Economics: Optimizing elastic HPC and training/inference costs for the next billion tokens.
  • Cognitive Trust: Engineering the guardrails, red-teaming frameworks, and safety layers required for enterprise-grade compliance.
  • Next-Gen CX: Deploying hyper-personalized, real-time multimodal agents that redefine human-computer interaction.

πŸ—οΈ Strategic Engineering & Selected Research

Bridging the gap between frontier research and production-grade systems.

🧠 Reasoning AI (GRPO)

Architected distributed NeMo-RL clusters on GKE to fine-tune Gemma 3 using Group Relative Policy Optimization (GRPO). Optimized FSDP sharding on NVIDIA B200 clusters.

Value: Achieved +6.2% absolute gain in MATH-500 accuracy via custom reward engineering.

πŸ” Enterprise Document AI (OCR)

Architected a multi-modal Financial Audit engine using LMMs and advanced OCR. Automated the extraction of complex, unstructured data from heterogeneous financial instruments.

Value: Eliminated 90% of manual data entry for Tier-1 financial institutions.

πŸ€– Spatial Intelligence & Robotics

Developed high-fidelity Computer Vision pipelines for autonomous robotic systems. Focused on real-time object detection and kinematic path planning in dynamic environments.

Value: Reduced manual oversight by 40% in industrial automation.

⏳ Predictive Prognostics

Leveraging my background in Thermodynamics, I built Time Series Forecasting models for high-value industrial assets to predict failure modes before they occur.

Value: Saved millions in unplanned downtime for energy providers.


πŸ› οΈ Technical Ecosystem

Frontier GenAI & Research Scalable Engineering & HPC Strategy & Domain
Gemini / Gemma 3 NVIDIA B200 C-Suite Advisory & Consulting
GRPO & RLHF (NeMo-RL) Ray on GKE (KubeRay) Unit Economics of AI
Vertex AI & Model Garden PyTorch FSDP & DCP AI ROI & TCO Modeling
Agentic RAG / Agents vLLM & FlashInfer Sovereign AI Frameworks
Dynamic Grounding Distributed Training (XLA) Gov & Risk Management

πŸ“ˆ Global Impact & Thought Leadership

"Science is only as useful as its ability to be democratized."

  • Lead GenAI Solutions: Architecting AI roadmaps for APAC Decacorns, transforming legacy data into Agentic Intelligence.
  • Open Source Authority: 80K+ downloads of tools designed to bridge the gap between complex data assets and business value.
  • 3M+ Professionals reached via technical publications and strategic guidance on AI infrastructure and economics.
  • Global Footprint: Mechanical Engineering (πŸ‡¨πŸ‡³) β†’ Robotics Researcher at Tohoku (πŸ‡―πŸ‡΅) β†’ Statistical Physics PhD at NTU (πŸ‡ΈπŸ‡¬) β†’ Wolfram Summer School (πŸ‡ΊπŸ‡Έ) β†’ CSIRO/McKinsey/AWS (πŸ‡¦πŸ‡Ί) β†’ Google.

πŸ“Š Vital Signs & Contribution Velocity

Stats Languages
Streak

πŸš€ Strategic Open Source Ecosystem

Active contributor to the foundational frameworks defining the future of AI/ML.


πŸ“‘ Digital Presence


Pinned Loading

  1. b200-nemo-rl b200-nemo-rl Public

    High-performance RLHF/GRPO pipeline scaling Gemma 3 on GKE Ray Clusters (B200/H200) using NVIDIA NeMo-RL. Includes native FSDP checkpoint merging and zero-shot vLLM benchmarking.

    Shell

  2. awslabs/amazon-denseclus awslabs/amazon-denseclus Public

    Clustering for mixed-type data

    Jupyter Notebook 101 20

  3. aws-samples/amazon-sagemaker-endpoint-deployment-of-fastai-model-with-torchserve aws-samples/amazon-sagemaker-endpoint-deployment-of-fastai-model-with-torchserve Public

    Deploy FastAI Trained PyTorch Model in TorchServe and Host in Amazon SageMaker Inference Endpoint

    Jupyter Notebook 75 9

  4. aws-samples/amazon-sagemaker-endpoint-deployment-of-siamese-network-with-torchserve aws-samples/amazon-sagemaker-endpoint-deployment-of-siamese-network-with-torchserve Public archive

    Twin Neural Network Training with PyTorch and fast.ai and its Deployment with TorchServe on Amazon SageMaker

    Jupyter Notebook 11 4

  5. Raiden Raiden Public

    Emulation of "Raiden" Game with Mathematica

    Mathematica

  6. aws-samples/streamlit-application-deployment-on-aws aws-samples/streamlit-application-deployment-on-aws Public

    Streamlit EDA Dashboard Powered by AWS Cloud

    Python 84 34