Fortune 50 AI/ML · ICML · Springer Nature · Elsevier · IEEE · OSS Contributor to HuggingFace Transformers · scikit-learn · vLLM · MCP

CLI-first tools designed to be called by other agents, not just humans. 15+ years turning applied machine learning and causal inference into production systems that move real business metrics, now extended to the agentic economy.

• Agentic Native Open Source Software (OSS) / Developer Community Contributions

  • Agent-Native Tools: 30+ self-built CLIs, MCP servers, and libraries, 35k+ downloads across npm and PyPI, also launched on Product Hunt
  • OSS Contributions: Merged PRs across high-impact repos
    • HuggingFace Transformers (158K+ stars)
    • scikit-learn (65K+ stars)
    • Ray (37K+ stars)
    • OpenAI Cookbook
    • TRL
    • PEFT
    • Google ADK
  • Open Pull Requests: 43 PRs under review across 17 repos

• Published Research (50+ publications · ORCID portfolio)

  • ICML 2026 Papers: 4 papers, multi-agent orchestration, model routing, prompt-injection defense, compound AI reliability
  • Books: Elsevier & Springer Nature
  • Peer-Reviewed Research: IEEE, Journal of Physics, Applied and Computational Engineering, SSRN

• Thought Leadership (21 articles · 10-article series · 5 talks)

  • Articles: 21 industry articles across 8 platforms, freeCodeCamp, DZone, Hackernoon, and 5 more
  • Causal Inference Series: Product Experimentation with Causal Inference, 10-article series at freeCodeCamp (10M+ monthly visitors)
  • Industry Conference Talks: Featured speaker across 5 top conferences on applied AI and scalable machine learning

I sit at the intersection of applied machine learning, causal inference, marketing measurement, and agentic B2A applications, building production AI systems that drive measurable business outcomes at scale.

My work has shaped AI and data strategy across retail media networks, AdTech, MarTech, CPG, and e-commerce at some of the world's largest companies. I specialize in problems where the math is hard, the stakes are high, and the answer has to work in production.

Core domains:

• Ads · Marketing Measurement · Incrementality Testing
• Agent-Native B2A/A2A Applications · Multi-Agent Orchestration
• Product Experimentation with Causal Inference on Gen AI and LLM Applications
• Generative AI · LLM Systems
• Retail Media Network (RMN) Measurement · Advertising Monetization
• Applied ML for E-commerce · CPG · AdTech · MarTech

Published author with ICML, Springer Nature, Elsevier, and IEEE. 50+ publications across peer-reviewed journals, books, conferences, and industry platforms.

Publication portfolio: orcid.org/0009-0008-0141-4690

ICML 2026: 4 papers published across various workshops at the top 3 global AI/ML conference.

Books (2)

• 📘 Applications of Artificial Intelligence in Healthcare, Elsevier
• 📘 AI for Advanced Manufacturing and Industrial Applications, Springer Nature

Peer-Reviewed Research

Articles (21)

Causal Inference Series for GenAI/LLM Product Experimentation: freeCodeCamp (10M+ monthly visitors)

Conference Talks (5)

• 🎤 AI Summit, New York, How Will Third-Party AI-Plugins Make an Impact on Business?
• 🎤 IEEE NAPS, Western Carolina University, Performance Comparison of Advanced ML Techniques for Electricity Price Forecasting
• 🎤 WPI Fintech Lab, Credit Risk Evaluation for Financial Inclusion
• 🎤 CONF-CIAP, xCovNet: A Wide Deep Learning Model for CXR-based COVID-19 Detection
• 🎤 CONF-MLA, Automated FX Currency Transaction Forecasting for E-commerce and Fintech

30+ self-built, agent-native CLIs, MCP servers, and libraries, with 35k+ combined npm and PyPI downloads.

Most ship on both npm and PyPI with a JSON/structured-output mode built for AI agents to call directly, not just humans.

Packages published on npm and PyPI.

Contributing to the infrastructure layer of AI, the frameworks, SDKs, and tooling that every ML engineer depends on.

• 16 OSS contributions merged across 9 repos: HuggingFace Transformers, TRL, PEFT, scikit-learn, Optuna, Instructor, Ray, Google ADK, and Pandas
• 11 additional PRs opened across HuggingFace Accelerate, Optimum, Tokenizers, Datasets, chat-ui, lighteval, and PyTorch Lightning: all narrow, single-purpose fixes (type hints, bugfixes, docs), each independently duplicate-checked and policy-checked before submission
• 2 more in the pipeline: a PR approved by a maintainer awaiting final merge (sklearn #33728), plus a contribution acknowledged and shipped by the maintainer team
• 43 PRs under review across 17 repos: Anthropic Cookbook, OpenAI Cookbook, HuggingFace Tokenizers, HuggingFace Accelerate, scikit-learn, HuggingFace TRL, chat-ui, HuggingFace Datasets, HuggingFace Evaluate, lighteval, HuggingFace PEFT (consolidated), Anthropic Courses, vLLM, spaCy, MCP, HuggingFace Optimum, and PyTorch Lightning

These contributions are now part of the official codebases used by millions of engineers worldwide.

✅ huggingface/transformers #45352 (merged)

Fixed an incorrect return type annotation on Qwen3MoeSparseMoeBlock.forward in HuggingFace Transformers (158K ⭐), the most widely-used library in AI/ML. Propagated the fix to two generated model files (qwen3_vl_moe, qwen3_omni_moe). Reviewed and approved by a Transformers core maintainer. Ran make fix-repo consistency checks and resolved CI failures before merge.

✅ huggingface/transformers #45370 (merged)

Fixed 5 docstring errors in Gemma3nTextConfig across HuggingFace Transformers (158K ⭐), correcting typos, grammar, and formatting issues in Google's Gemma 3n model configuration. Passed the anti-slop check and all CI checks.

✅ huggingface/transformers #45351 (merged)

Fixed a crash in get_device_capability() in HuggingFace Transformers (158K ⭐) testing utilities when CUDA is installed but no GPU is present. Refactored CUDA/ROCm and XPU split per @remi-or's review, both accelerator paths are now independent. Reviewed and merged by Transformers core maintainers.

✅ optuna/optuna #6631 (merged)

Fixed a Sphinx RST directive typo in Optuna (11K ⭐), correcting .. note: to .. note:: in the QMCSampler docstring, which prevented the note from rendering in the documentation. "Good catch!" response from maintainer before merge.

✅ huggingface/trl #5527 (merged)

Contributed a new training template for DeepSeek-V3 to HuggingFace TRL (12K ⭐). This template enables engineers to correctly fine-tune DeepSeek-V3 models using SFT loss masking, ensuring the model learns only from the assistant's responses, not the user's questions. Reviewed and approved by the TRL core maintainer.

✅ huggingface/trl #5522 (merged)

Contributed a new training template for Alibaba's Qwen2.5 language model to HuggingFace TRL (12K ⭐). This change enables engineers to correctly train Qwen2.5 models so the AI learns only from the assistant's responses, a critical capability for building production chatbots and AI assistants. Reviewed and approved by the TRL core maintainer.

✅ huggingface/trl #5526 (merged)

Contributed a new training template for Microsoft's Phi-3 model family to HuggingFace TRL (12K ⭐). Adds {% generation %} markers for SFT assistant-only loss masking. Approved by the TRL core maintainer and merged into main.

✅ huggingface/trl #5493 (merged)

Contributed the equivalent training template for Meta's Llama 3 model family to HuggingFace TRL (12K ⭐). Llama 3 is one of the most popular open-source AI models in the world. This template is now part of TRL's official release and is used daily by ML engineers fine-tuning Llama 3 for production applications.

✅ huggingface/trl #5494 (merged)

Added a working code example to HuggingFace TRL's documentation showing how to use a key training feature (completion_only_loss) that was previously undocumented, helping new users get started faster with a feature the community had been asking about.

✅ scikit-learn/scikit-learn #33723 (merged)

Clarified in scikit-learn (65K ⭐) documentation that best_estimator_ in HalvingGridSearchCV and HalvingRandomSearchCV reflects only the winner of the final halving iteration, a subtle but important distinction for users interpreting search results. Approved by two scikit-learn core maintainers (StefanieSenger, betatim) and merged. Also closed issue #24901.

✅ scikit-learn/scikit-learn #33722 (merged)

Clarified in scikit-learn (65K ⭐) that VotingClassifier.estimators_ contains models fitted on integer-encoded labels, not the original string class names. This subtle distinction causes silent misinterpretation when users inspect the fitted sub-estimators. Reviewed by jeremiedbb and merged; also closed issue #12189.

✅ huggingface/peft #3144 (merged)

Added type annotations to utility functions across src/peft/utils/ in HuggingFace PEFT (17K ⭐), merge_utils.py, other.py, loftq_utils.py, and integrations.py. Ran pyright across the full module to target the most impactful errors. Approved by PEFT lead maintainer BenjaminBossan after an iterative review addressing 5 inline change requests.

✅ 567-labs/instructor #2280 (merged)

Fixed exception propagation in Instructor (10K ⭐): when an LLM returns an incomplete response, IncompleteOutputException was being swallowed inside a tenacity RetryError wrapper, hiding the root cause from callers. The fix propagates it directly, giving users the correct exception type without the wrapping noise. Merged by Jason Liu.

✅ ray-project/ray #62756 (merged)

Fixed incorrect import count in the PyTorch CIFAR tutorial notebook in Ray (37K ⭐), the comment stated 3 Ray-specific imports where only 2 existed. Reviewed by @pseudo-rnd-thoughts (LGTM) and merged.

✅ google/adk-python #5235 (merged)

Fixed a crash in adk web for Google ADK (9K ⭐), Google's Agent Development Kit, by adding support for flat-module agent layouts in _determine_agent_language. The dev UI was breaking for agents that didn't follow a package-style module structure; the fix makes language detection work for both layouts. Merged into main via Google's internal Copybara import process.

✅ pandas-dev/pandas #65291 (merged)

Added a docstring with usage examples to NDFrame.__invert__ in Pandas (45K ⭐), and documented DataFrame.__invert__ in frame.rst. Approved and merged by @jbrockmendel.

📋 openai/openai-agents-python #2876 (acknowledged)

Submitted docstrings for the Computer and AsyncComputer abstract methods in the OpenAI Agents SDK (19K ⭐). The maintainer responded "Thank you so much for sending this" and resolved the gap via #2877. The contribution identified a documentation need that the core team then prioritized and shipped.

Active tracks: HuggingFace Transformers · HuggingFace TRL · HuggingFace PEFT · HuggingFace Accelerate · HuggingFace Optimum · HuggingFace Tokenizers · HuggingFace Datasets · HuggingFace Evaluate · HuggingFace chat-ui · lighteval · PyTorch Lightning · scikit-learn · Google ADK · MCP · Instructor · OpenAI Agents SDK · Optuna · spaCy · Ray · vLLM · Pandas · Anthropic Courses · Anthropic Cookbook · OpenAI Cookbook

Python · TypeScript · Node.js · PyTorch · HuggingFace · LLMs / Gen AI · MCP · vLLM · LangChain · Causal Inference · SQL · Spark · Claude Code