Eric Lagally
Leadership, Analytics,
& Learning Design
Solving problems at the interface of people, process, and technology.
Technologies are tools that are used by and for people. This is true in the educational context - the ways in which students access learning and conduct that learning - and it is true in the working world as well. My experience as a bioengineer taught me that just because we developed the fastest, most sensitive genetic detectors was not a guarantee that they would be accepted in the medical or biology research communities. Likewise, the newest AI tools function well only to the extent that the people and processes in an organization can adapt to make best use of them.
I have broad experience as a leader in higher education focused on equity - how can we provide access to those most under-served while also serving those from other groups in ways that drive everyone forward? Part of these solutions are technological, part are process-based, and part are leadership-focused. Threading through all of my experience has been analysis - the ability to quickly determine which approach is best used to address a given challenge. These pages provide some examples of my skills in analysis from both the technical as well as the non-technical domains.
Examples of my Work
The BIG WIRES Act (H.R. 5551, S. 2827) is a bill that would increase the ease of permitting for large electricity transmissions projects in the U.S. This analysis explores the current state of electricity generation and transmission, specifically capacity, state and regional needs, the emissions from current electricity generation, and the prevalence of solar and wind electricity projects nationwide.
Species Distribution Models (SDM) are commonly used in ecology to predict the likelihood of species occurrence given known environmental conditions. In this study, I compare several machine learning approaches to develop an SDM for Northern pikeminnow (Ptychocheilus oregonensis), a freshwater predatory fish native to the Pacific Northwest.
The Washington State Department of Fish and Wildlife (WDFW) maintains a website that presents data on hunting and trapping statistics by year. However, this website presents data in tables and does not allow easy comparison among years or among individual game management units. Using the public data from the WDFW site, I assembled and maintain a Tableau Public dashboard that presents these data in a manner more easily amenable to asking and answering questions about game management statistics over time.
As the number and types of artificial intelligence (AI) applications and methods continue to grow, one of the most common questions I receive is: “What are you doing with AI in your programs?” This question lacks proper scope - one must first define what part of the broad spectrum of AI is of interest. To help guide both students and others in their AI learning, I assembled a mind map of machine learning methods, major decisions used to choose a particular approach, and common use cases. Although certainly not an exhaustive list, it has nevertheless been helpful in guiding conversations around strategic decision-making in curriculum and approach.
