Adam D. Edwards

Hi. I'm Adam.

I'm a philosophy student and teacher. Right now I'm a graduate student in the philosophy department at the University of Illinois at Urbana-Champaign, and an adjunct instructor at both Heartland Community College and Lincoln College.

My research is motivated by an interest in projects in philosophy of science and metaphysics that involve causal graphical models. These projects include defending a view of scientific explanation where causal models play a significant role, developing an empiricist-minded modal epistemology, and giving a causal modeling analysis of dynamic systems.

My dissertation is on causal modeling interventions and experimental design.

I also have research interests in the potential of data mining and machine learning to contribute to philosophical inquiry and in experimental philosophy.

Before grad school I worked with Dr. Sriraam Natarajan and the Statistical-Relational AI Team (StRAIT) at Wake Forest Baptist Medical Center on data mining and machine learning solutions to medical problems. While I was there we developed a pipeline algorithm that delivered high quality predictions of the onset of Alzheimer's disease using patient fMRI scans. Before that I did my undergraduate work at Wake Forest University in physics and philosophy.

Other than teaching and doing philosophy, I enjoy backpacking, board games, making coffee in increasingly complicated ways, and playing with my dog, Rose. 🌹

My ORCID is ORCID iD icon


Teaching Projects

Currently Teaching

In 2018, I am teaching courses in applied ethics, ethics, introduction to philosophy, and informal logic.

I am also responsible for pedagogical instruction and course development for the department of philosophy at the University of Illinois at Urbana-Champaign for the upcoming academic year (informally, the "Super TA"). This position involves training first-year graduate students on pedagogical strategies, classroom management techniques and technologies, and best-practices for assessment, communication, and problem-solving. I am also working to develop a course plan for the department's Advanced Composition curriculum.

Teaching Portfolio

A comprehensive picture of my development as a teacher can be found at the link above. I've tried to provide an overall picture of my approach to teaching: strategies, resources, and results. If you have questions about any of the materials presented here, feel free to contact me at


Research Projects

My primary interests are in philosophy of science, epistemology, and philosophy of information. I also have spent time working on issues in machine learning, digital humanities, metaphysics, and philosophy of physics. My dissertation is on the role that interventions play in the causal modeling framework for scientific explanations, causal inferences, and modal semantics.

Works in Progress

  • How to Account for Counterfactuals While Respecting the Laws

In this paper I argue that in a deterministic world Lewis-style "small miracles" make the evaluation of counterlegals impossible.

  • Ontological Levels and Abstract Objects

In this paper I make a case for taking the existence of abstract objects more seriously and argue that the 'levels' metaphor for discussing objecthood and fundamentality misleads us from a proper understanding of abstract objects.

  • Toulmin and the D-N Model of Explanation

In this paper I explore the work by Stephen Toulmin as it relates to the Deductive-Nomological model of explanation and develop a Toulmin-style isomorph to that model.

Network Analyses

In addition to working on explanation and the foundations of graphical models I enjoy learning the tools and techniques of scientists who work with those models. To that end I've been working on some projects that use the data produced by professional philosophy to get a network-level view of the field. See below for the results of this work.

Past Work

Before graduate school I worked with the Statistical Relational AI Team at Wake Forest University Baptist Medical Center to develop an AI pipeline for Alzheimer's diagnosis using statistical relational learning and expert knowledge. This work was presented at the 2012 Internation Conference on Machine Learning and Applications (ICMLA) [.pdf] and later published in the International Journal of Machine Learning and Cybernetics (IJMLC) [.pdf].