Daniel J. Kowalski

The site highlights my research, data portfolio, and efforts to promote accessible scientific knowledge, spanning chemistry, machine learning, and education, with a focus on digital tools for discovery.

Research Interests

My research interests cover the intersection of chemistry with data science, machine learning, and robotics. The aims are to enable discovery by developing new methods, models, and ideas that expand how we search for and understand chemical systems.

• Digital Discovery Strategies
  Developing machine learning workflows for the exploration and exploitation of chemical search spaces, with a focus on fostering serendipity.
• Earth-Abundant d-Block Chemistry
  Exploring the structures, reactivity, and properties of systems built around first row transition metals.
• Self-Driving Laboratories
  Developing systems that integrate robotics and machine learning for closed-loop material discovery.
• Deconvolution of Chemical Mixtures
  Applying machine learning to interpret analytical data and visualise meaningful relationships within mixtures with high compositional diversity.
• Digitisation of Chemical Synthesis
  Creating interpretable and generalisable representations of synthetic data for machine learning.

Data Portfolio

A selection of projects demonstrating the application of data science and machine learning techniques to problems in chemistry and common business scenarios. Projects are written in python3. AI agents (e.g. ChatGPT, CoPilot) have not contibuted code to these projects.

Links are provided to: (i) a discussion of each project suitable for a general audience, and (ii) the full code for each project on GitHub.

1 | Optimising a Neural Network for Solubility Prediction

Integer eu ante ornare amet commetus vestibulum blandit integer in curae ac faucibus integer adipiscing ornare amet.

• Read More
• GitHub

2 | Conway's Game of Life with Generative AI

Integer eu ante ornare amet commetus vestibulum blandit integer in curae ac faucibus integer adipiscing ornare amet.

• Read More
• GitHub

3 | Calculating the Convex Hull for Exotic Sodium Chlorides

Integer eu ante ornare amet commetus vestibulum blandit integer in curae ac faucibus integer adipiscing ornare amet.

• Read More
• GitHub

4 | Virtual Screening? Alphafold?

Integer eu ante ornare amet commetus vestibulum blandit integer in curae ac faucibus integer adipiscing ornare amet.

• Read More
• GitHub

Technical Publications

(2) Automated Library Generation and Serendipity Quantification Enables Diverse Discovery in Coordination Chemistry

J. Am. Chem. Soc. 2023, 145(4), pp.2332

• Journal
• GitHub

(1) An Autonomous Chemical Robot Discovers the Rules of Inorganic Coordination Chemistry without Prior Knowledge

Angew. Chem. Int. Ed. 2020, 59(28), pp.11256

• Journal

Wikipedia Projects

Education and open knowledge are very important to me. Contributing to Wikipedia enables me to help promote accurate, well-referenced scientific information and make it freely accessible to all. Below are a list of my contributions to Wikipedia, including links to each page.