DATA INSIGHT
LIVE WEBINAR
Accelerating Innovation with Design of Experiments and Active Learning
Date: Tuesday, June 2
Time: 2:00–2:30 p.m. ET | 11:00 a.m. PT
Duration: 30 minutes
Registration: FREE
Finding the best settings for a process or system can be slow, costly, and uncertain – especially when relying on trial and error or one‑factor‑at‑a‑time (OFAT) approaches. Design of experiments (DOE) and active learning provide a structured and efficient way to explore complex systems, shorten development cycles, and uncover high‑performing solutions with confidence. With the right strategy, you can shift from guesswork to guided discovery and make smarter decisions in fewer experimental trials.
Learn how to:
- Design smarter experiments that extract maximum insight from every run.
- Prioritize the most informative next steps using data-driven guidance.
- Identify optimal settings faster while reducing cost, risk, and rework.
In this 30-minute webinar, see how DOE and active learning empower scientists and engineers to accelerate understanding, optimize performance, and maximize limited resources.
About the presenters
Tom Donnelly,
Principal Systems Engineer
Tom Donnelly is a Principal Systems Engineer at JMP, where he supports users in the defense and aerospace sectors. He has been actively using and teaching design of experiments (DOE) methods for the past 35 years to speed development and optimization of products, processes and technologies.
Prior to joining JMP, Donnelly worked as an analyst for the Modeling, Simulation & Analysis Branch of the U.S. Army’s Edgewood Chemical Biological Center. For 20 years, he served as a partner with the first DOE software company to enter the market, teaching more than 300 industrial short courses to engineers and scientists.
Monique Roerdink Lander,
Systems Engineer
Monique Roerdink Lander is a Systems Engineer for JMP Statistical Discovery, which creates interactive and highly visual statistical discovery software for scientists and engineers. As such, she is the technical contact for users and prospective users, providing training on how to do things in JMP. Roerdink Lander has a doctorate in materials science and technology of polymers from the University of Twente in the Netherlands.
Prior to joining JMP, she spent more than a decade in product development in R&D for Ecolab, most recently as a Senior Staff Scientist. A JMP user for a decade, she has more than 20 peer-reviewed papers and patents.
Jed Campbell,
Senior Systems Engineer
Jed Campbell is a Senior Systems Engineer at JMP Statistical Discovery, which creates interactive and highly visual statistical discovery software for scientists and engineers. An educator by training, Campbell helps people see how they can get better and faster insights to their data by using JMP.
A Master Black Belt in Six Sigma, he has a vast experience as a problem solver, ranging from process improvement in manufacturing to designing and coaching experiments in rocket science. Campbell led a successful application process for which he won the enterprise-level Shingo Prize in 2011. He has a strong business acumen, sharpened by a nationally ranked MBA, focusing on entrepreneurship. Campbell also understands quality systems and how they can be incorporated into existing businesses without undue bureaucracy.