To be honest, today's talks were not that attractive. I think the problem with sleep cannot be resolved by wearable devices. And the presenters could not persuade me by the introductions. That's why there is no interest to continue listening to it.

Multiscale Biofabrication Towards System ‘Engineering’ Biology

Presenter: Prof. Olli Ikkala
Professor of Bioengineering, Aalto University (Finland)

Prof. Olli Ikkala is a distinguished researcher at the Department of Applied Physics, Aalto University in the Helsinki metropolitan area. Originally trained in quantum physics, he spent a decade in industry working on supramolecular self-assemblies of electrically conducting polymers, tailoring them for real-world applications. His current research focuses on bioinspiration—using nature as a guide to create novel static and dynamic properties in soft matter. His work spans hierarchical self-assemblies, nacre-mimetic materials, functional nanocelluloses, and stimulus-responsive soft systems that mimic behavioral learning like Pavlovian conditioning, habituation, and sensitization.

I’m not sure what qualifies as fundamental research—I’m feeling a bit confused. So I’m looking at how Zhenan Bao described her lab’s research in this podcast:

🎧 Podcast episode

Tonight, I had the pleasure of virtually attending a seminar hosted by Stanford University. The first presentation immediately resonated with my own research interests in sensor design and fabrication.

Today, I attended an inspiring online workshop hosted in Sweden, focused on “Functional Additive Manufacturing in 2D & 3D: Novel Inks and LASER-Based Patterning Technologies.” I really appreciate this kind of remote event — it saves both time and money! 😅

Multiscale Biofabrication Towards System ‘Engineering’ Biology

Presenter: Prof. Yan Yan Shery Huang
Professor of Bioengineering
Funding: ERC (European Research Council)

Context

Medical and technological innovations bring direct health and economic benefits in the near and intermediate terms. But what about the future? Multiscale biofabrication opens new possibilities for:

Decision Trees: A Powerful Tool for Machine Learning

Decision trees are versatile machine learning algorithms that can perform both classification and regression tasks, and even multioutput tasks. They are the fundamental components of random forests, which are among the most powerful machine learning algorithms available today.

Tonight, I had the opportunity to remotely attend a seminar held at Stanford University, where two insightful presentations shed light on advancements in wearable sensors.

Introduction

Welcome to this exciting chapter Again!

Introduction

Welcome to this exciting chapter! In this blog, I’ll work through an end-to-end machine learning project, turning raw data into actionable insights and a working model. Follow these structured steps to tackle any ML problem confidently.