Richard Lee, Author at ACD/Labs

Enabling Collaboration in R&D | The Evolving Story of Data & Access

Richard Lee Apr 5, 2023

User expectations are driving development in scientific informatics. If developers are paying attention, then new tools will take careful account of the user interface and user experience.

Benefits of Automating Workflows in Analytical Data Management & Tips on Getting Started

Richard Lee Jun 23, 2022

For scientists that use analytical data in daily decision-making, automation of analytical workflows can help relieve the burden of data management and support faster decision-making. Automation can also significantly reduce data collection and preparation time. Should you be looking to automate analytical data workflows? Read more here.

The Next Era of Chemistry: Data Science and Coding

Richard Lee Aug 31, 2021

Coding can take scientists from participants to owners of their data. More and more it is becoming clear that every organization needs to employ workers with data science skills. As more scientists become data scientists, the move towards digitalized data will accelerate.

How ML and AI Can Leverage Data to Streamline Projects and Find Insights

Richard Lee Jun 16, 2021

Richard Lee discusses the global trend around the development of machine learning (ML) and artificial intelligence (AI) capabilities. As utilization of ML/AI continues to grow, R&D organizations will likely continue to focus on how to normalize data into a format that can be fed into a ML/AI framework.

Reflections on Leveraging Chemistry Data in Machine Learning

Richard Lee May 14, 2020

Richard Lee reflects on how biotechnology organizations can use their historical data to address real chemistry world problems; especially during this time when more and more scientists are working remotely.

Defining Technology Buzzwords: What Machine Learning, Data Lakes and Artificial Intelligence Means for You

Richard Lee May 15, 2019

Richard Lee breaks down the current technology buzzwords and what you need to know about machine learning, data lakes, artificial intelligence, and more.

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