Meryll Dindin

What happens when a company connects its data warehouse, documents, tickets, and code into a single AI agent that any employee can talk to in Slack.

Your chronological age is a timestamp. Your biological age is a signal. How epigenetic clocks, aging pace, and organ-level data changed how I think about getting older.

The AI productivity story focuses on individuals. The real bottleneck is how information moves between teams. Production got cheaper. Coordination didn’t.

Full-stack used to mean frontend and backend. Now it means one person shipping what used to take a cross-functional team. What changed.

AI adoption doesn’t start with a strategy deck. It starts with one person who has the authority to make it everyone’s job.

AI tools for special education are outpacing the policies meant to govern them. A look at IDEA compliance, assistive technology, data privacy, and what districts are getting wrong.

Algorithmic models for learning disability identification fail at the level of chance. The research case for clinical reasoning over formulaic gatekeeping.

The U.S. Department of Labor just made AI literacy a foundational workforce skill. What that means for every role at every company, and what the framework gets wrong.

How we built a data system to track IEP progress across thousands of students, and what 98% at-or-above target tells us about virtual special education.

Five dispatches from HLTH 2025 on ambient AI, teen chatbot dependency, clinical oversight, and why human ingenuity still sets the ceiling.

Learning differences like dyslexia and ADHD are common neurological variations requiring tailored interventions and supports. This article explains how learning disabilities are identified and treated.

In the 9th episode of Compliance Uncomplicated, I discussed the importance of compliance and security in handling sensitive data, the transformative role of AI in cybersecurity, and the significance of open-source communities in AI's future​.

Explore how generative AI reshapes children's storytelling, boosting creativity and inclusivity, while addressing ethical and data security concerns. Understand the impact of AI tools like OpenAI's GPT-4, Midjourney-Storybird, and Replika, and uncover the future of AI in education.

In this podcast episode, I discuss Polygon as a unique psychology practice that provides online support for individuals with dyslexia, ADHD, and other learning differences. I share my personal journey, business scale-up plans, importance of data security, and the promising role of AI in healthcare.

As Co-Founder of Thrive Education, I join Mark on an episode of Founders Grit. I share about my journey to founder and CTO and how deals with people from different parts of the globe. Moreover, I share about the difficulties and struggles I faced while hiring remote.

At IBM's Code in Cloud conference, I highlighted the crucial role of developers in shaping digital transformation. The discussion emphasized their influence on open-source technologies, cloud computing, and their ability to discern trends amidst overwhelming information.

During a project at Politecnico, Quentin Biabaud recounted my leadership journey, as a French engineer made entrepreneur.

In my latest article, I delve into applying Topological Data Analysis (TDA) in deep learning models for arrhythmia classification, outlining its use, integration, and effect on predictive precision.

Unravel complex concepts like fluid and crystallized intelligence, the Cattell-Horn-Carroll theory, and the working memory theory. I delve into the criticisms of traditional models, the Flynn effect, and the potential of new research for a clearer understanding of intelligence and its impact on education.

This article takes an intricate journey through the use of machine learning in classifying sleep stages. Delving into the handling of EEG data, feature engineering, model building, and prediction smoothing, it reveals how modern techniques can revolutionize our understanding of sleep health and improve everyday lives.

This article discusses the application of Topological Data Analysis (TDA) in clustering through the ToMATo algorithm. This novel approach helps identify the number of data clusters and gathers data into distinct sets. I share here insights on the ToMATo algorithm, providing a proof-of-concept code and real-world examples, and discusses its potential implications.

Dive into the revolutionary field of Topological Data Analysis (TDA) and its role in shaping the future of machine learning and deep learning. Understand core concepts like persistence homology, Betti curves, persistence landscapes, and more, along with their practical applications and significance in data analysis.