Books, research frameworks, Springer chapters, and editorial review.
Enterprise LLM deployment readiness, data-centric ML, privacy-preserving AI, and multi-agent simulation.
Sculpting Data for ML: The First Act of Machine Learning
Co-authored with Rishabh Misra—a hands-on Python guide to Data-Centric AI covering dataset curation, weak supervision, labeling workflows, and class imbalance.
- Prof. Julian McAuley — Professor of Computer Science, UC San Diego
- Laurence Moroney — AI Lead & Bestselling Author
- Dr. Mengting Wan — Senior Applied Research Scientist
“The authors do a good job in explaining the process of creating a dataset for Machine Learning models. A dataset is not merely a raw CSV or JSON file that one downloads from the internet... The example code provided in the book is very easy to follow and understand, explaining why each preprocessing step is important for Machine Learning models to function efficiently and to produce accurate results.”
Chapters & conference papers
SSRN · AI Assurance Council Practitioner Framework (SSRN 7477058)
Co-authored six-pillar operational governance, evaluation, security, compliance, and observability framework for moving enterprise LLMs from pilot to production.
Springer — Data Protection in a Post-Pandemic Society
Examines membership, input, and property inference attacks alongside differential privacy, federated learning, synthetic data, and AI privacy regulations.
Springer — Deep Learning for Social Media Data Analytics
Comparative analysis of deep learning architectures for misinformation detection, fairness, interpretability, and dataset drift.
ACM — International Workshop on Smalltalk Technologies (IWST)
Introduces live spatial visualization interfaces for multi-agent ecological modeling in CORMAS and Pharo.
Square Bracket Associates
Open-source contributor to the flagship guide on the Pharo live object-oriented programming environment.
Technical book reviewing
Technical Book Reviewer — Scalable AI Systems (2026) & Machine Learning with Python Cookbook, 2nd Ed. (2023); cited in AI-Assisted Programming
Technical Book Reviewer — Exploring Deepfakes (2023) & Applied AI Manuscripts