Teaching

Classroom Teaching

In Spring 2025, I was a co-instructor for Concepts of Machine Learning, an undergraduate introductory course to machine learning.

In Spring 2024, I was a co-instructor of Ethics & Policy for Data Science, a required course for U of I’s X+DS program.

The Carpentries

I am a certified instructor of the Carpentries since March 2020. I believe in democratizing programming skills and promoting a diverse and inclusive data science workforce, and working for the Carpentries is how I fulfill this mission on a regular basis. I have served as an instructor for 17 workshops, which allowed me to reach a broader body of students beyond those I interact with at my institute. [Carpentries teaching history]

Mentoring Experience

As a PhD student in Information Science, I mentored 11 undergraduate and 4 master students on a variety of research projects.

Mentee-led publication/presentation

Stade, C., Schneider, J., & Fu, Y. (2025). From evidence to insights: GraphRAG as a dynamic knowledge layer for the collaboration for environmental evidence’s database of evidence reviews. Proceedings of the 3rd International Workshop on Knowledge Graphs for Sustainability (KG4S 2025), 4002, 39–45. https://ceur-ws.org/Vol-4002/short6.pdf

Stade, C., Schneider, J., Fu, Y., Making Sense of the Environmental Science Landscape: An exploration of the CEEDER database. METSTI 2024: Workshop on Informetric, Scientometric and Scientific and Technical Information Research, November 13, 2024.

Sarraf, I., Fu, Y., Schneider, J., Text mining scholarly publications using APIs, Poster presented at METSTI 2023: Workshop on Informetric, Scientometric and Scientific and Technical Information Research, October 27, 2023. https://doi.org/10.5281/zenodo.10581542

Haque, T., Lam, T., Rahman, M., González-Cruz, K., Fu, Y., Schneider, J., Annotating data to train machine learning models to classify citations in biomedical papers. Poster presented at the 2022 American Physician Scientists Association Northeast Regional Conference, January 15-16, 2022. In Abstracts of the 2022 American Physician Scientist Association (APSA) Northeast Regional Conference (NERC), In Int J Med Students Vol 10 (Suppl 1). https://doi.org/10.5195/ijms.2022.1359

Wan, Z., Fu, Y., Schneider, J. Using citation redistribution to estimate unbiased expected citation count from a biased citation network. Poster presented at the iSchool Research Showcase, University of Illinois at Urbana Champaign, October 27, 2021. http://hdl.handle.net/2142/112794

Explainable AI Study Group

I founded and organized Explainable AI study group at the iSchool in 2022 to 2023. This study group aimed to create a low-pressure, peer-mentoring learning space for students to learn and practice explainable AI (XAI) techniques. [XAI study group GitHub page]