Purdue University · Computer Science

Ethan Dickey

PhD candidate in Computer Science

Ethan Dickey

I am a sixth-year PhD candidate in Computer Science at Purdue University, advised by Sabre Kais and Alex Psomas. I expect to graduate in May 2027.

My main research uses graph theory and spectral methods to understand how classical networks can realize quantum-like states, and what we can control and measure in those systems. I also study the computational complexity of voting rules and how students learn with generative AI. Teaching and mentoring are a substantial part of my work: I lead Purdue’s competitive programming course sequence and have advised twelve undergraduate researchers.

dickeye@purdue.edu Request my CV Google Scholar ORCID LinkedIn

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Research

Quantum-like information in classical networks

A network’s collective modes can have the mathematical structure of a qubit. I study how to build networks with a desired state, how their structure determines the available operations, and what can be learned from their response to a measurement. My work gives explicit constructions using signed regular graphs and Hermitian weighted graphs, and develops readout methods for effective two-qubit states.

I am now studying composition, dynamics, and robustness: when does a useful logical description survive imperfections, and how do leakage and spectral isolation affect what the network can do? I am also developing a review and tutorial on graph-based quantum-like information and collaborating with Gregory Scholes’s group on network dynamics.

Signed-graph constructionsComplex statesMeasurement & readout

Algorithms & computational social choice

I study the computational difficulty of collective decision making. With Alex Psomas and Athina Terzoglou, I proved that finding a winner under Stable Voting or Simple Stable Voting is PSPACE-complete. My work with Aidan Casey considers how the assumptions and possibilities of voting change in quantum models.

My ongoing projects examine tournament solutions, restricted voting instances, and the complexity of computational games.

Stable VotingQuantum voting

Generative AI & computing education

I study how to teach students to use generative AI while developing the judgment and problem-solving skills they need to work independently. My research combines classroom studies with the design of instructional tools, from structured AI-literacy activities and reflection on code to simulated students for teaching-assistant training.

In a randomized algorithms-course study, we found that evaluating GenAI solutions improved homework scores without a statistically significant difference in exam performance. That distinction motivates my broader interest in when AI-supported activities lead to learning that transfers beyond the activity itself. My current work also examines how a tool’s design assigns instructional authority, preserves learner agency, and gives instructors meaningful oversight.

Ongoing studies include GLOW-based GTA preparation and how constructing test cases helps students evaluate and understand programs.

Learning & evaluationAI-Lab studyInstructional governanceTools & materials

Recent news

Publications & preprints

Journal articles and accepted conference papers, followed by public preprints and poster presentations. Ongoing research is described above.

Journal articles & accepted conference papers

Preprints

Posters & extended abstracts

Teaching

I developed Purdue’s CS 211/311/411 competitive programming sequence beginning in Fall 2021 and have been Instructor of Record for CS 211 since Fall 2022. I coordinate the sequence, develop its curriculum and assessments, and mentor its teaching staff. CS 211 typically enrolls about 100 students each semester.

My approach starts with students learning to recognize a problem’s structure, explain a solution, and test whether it works. The sequence builds toward timed individual and team contests after students have developed a broader foundation in algorithmic problem solving. This work is described in my curriculum design paper.

Selected teaching experience
CS 211 · Competitive Programming IInstructor of Record, Fall 2022–present; curriculum development and teaching assistance, Fall 2021–Spring 2022.
CS 211 / 311 / 411Course-sequence leadership, assessment design, and TA supervision.
CS 240 · Programming in CGraduate Teaching Assistant, Summer 2026.
CS 251 · Data Structures and AlgorithmsGraduate Teaching Assistant and course development, Summer 2022.

I earned Purdue’s Graduate Certificate in Teaching and Learning in Engineering in 2023. I also coach Purdue’s ICPC teams and have supported teams at regional, North American, and World Finals competitions.

Teaching & service recognition

Mentoring

I have advised twelve undergraduate researchers on computing-education projects, including the development and study of GLOW, Owlgorithm, CodeStylist, BoilerSketch, and BoilerTAI. My earlier mentoring included co-advising students with Andres Bejarano through Summer 2025 and independently advising Ashok Saravanan and Alex Siladie from Fall 2025 through Summer 2026. Since Fall 2026, I have been advising Thanh Dat Le on adversarial test design in competitive programming.

Undergraduate research mentees
ResearcherDatesProjects
Thanh Dat LeFall 2026–presentAdversarial test design in competitive programming
Ashok SaravananSummer 2025–Summer 2026GLOW
Alex SiladieSummer 2025–Summer 2026GLOW
Peter KurtoFall 2024–Spring 2025CodeStylist; Owlgorithm
Erin KramerFall 2024–Spring 2025Owlgorithm
Juliana Nieto-CardenasFall 2024–Spring 2025Owlgorithm; GoBoiler
Libra VentoFall 2024–Spring 2025CodeStylist; GoBoiler
Vivan TiwariSummer 2024–Spring 2025BoilerTAI; BoilerSketch
Anvit SinhaSpring 2024–Spring 2025BoilerTAI; BoilerSketch
Shruti GoyalFall 2023–Spring 2024BoilerTAI
Zachary SyFall 2023–Spring 2024BoilerTAI
Yashwi ThakkarSummer 2023Exploratory research

I have also advised instructors developing competitive-programming courses, including Metin Aktulga at Michigan State University and Sam Weese at the University of Cincinnati.

Service & research support

Building academic communities

I served as president of Purdue’s Computer Science Graduate Student Association from 2024 to 2026, after earlier roles on the graduate student board. I founded and chaired the inaugural Purdue CS Graduate Research Symposium in 2025.

I have also served on the ICPC Curriculum Committee and helped build Purdue’s community of instructors working with generative AI in education.

My reviewing service includes ACM Transactions on Computing Education, Computers and Education: Artificial Intelligence, SIGCSE, IEEE FIE, and IEEE EDUCON.

Support for computing-education research

With Andres Bejarano, I served as co-PI on Purdue Innovation Hub project IH-AI-23002 (2023–2025), supported by an initial $88,000 award and a $99,000 extension. This support enabled our work on generative AI in computing education and funded undergraduate research opportunities.

Research experience

My experience also includes a research internship at Blue Wave AI Labs in Summer 2026 and a quantum-computing research internship at IBM in Summer 2021.

Teaching & research resources

Materials for instructors, workshop participants, and researchers. Poster PDFs are linked with their presentations above.

GLOW: GTA training

Evaluating GenAI solutions

AI-Lab

GAIDE

Tools & demonstrations

GLOW

Office-hour practice with AI-simulated students and rubric-based feedback for graduate teaching assistants.

Visit GLOW · Research poster

Owlgorithm

Reflection prompts that ask students to explain their code and reasoning during competitive programming. The live demo is currently offline; example inputs are available below.

Example problems & code

CodeStylist

Course-aware feedback on code style for early undergraduate programmers. The live demo is currently offline; the original Java examples remain available.

Example code

BoilerSketch

A TA-supervised workflow for generating and discussing structured diagrams in introductory computing courses. Contact me for a demonstration.

Example prompts & recorded demonstrations

BoilerTAI

Draft responses to course-forum questions, with instructional staff reviewing and editing each response before it is posted.

Recorded demonstration (MP4)

Poster templates

Horizontal Purdue poster template (PowerPoint) · Vertical Purdue poster template (PowerPoint)

Writing & outside of research

I enjoy explaining research and teaching ideas to audiences outside my own field. My blog includes classroom activities, occasional reflections, and a little satire.

Outside research, I love hiking Colorado’s fourteeners, skiing double-black-diamond terrain, and climbing outdoors. I also enjoy Sudoku and host weekly board game nights. My wife and I train our border collies, Kali and Rogue, in agility on a course we built ourselves. They have rather different opinions about toys: Kali’s defense of the tennis ball prompted a rebuttal from Rogue.