"Research is a seeking that he [sic] who wishes may know the cosmic secrets of the world."
—Zora Neale Hurston
My areas of support include:
Researchers often find themselves needing to pick up new ancillary skills to get the job done, and this includes computer coding and similar tools, especially for working with data. If you're in this situation, and lack the time to pursue courses in Computer Science, my trainings are for you.
No prior knowledge or experience is required. I particularly invite researchers positioned in labs and research groups, so that you can co-learn a new skill with your lab collaborators, but any ad-hoc group of learners in the Pitt community may request a training. Scheduling, timing (number of hours, sessions), and precise topics studied are flexible. Trainings may include asynchronous components (e.g., "assignments" to practice your new skills) if desired. Trainees are also free to contact me for follow-up support once the training is concluded.
Trainings are informed by evidence-based pedagogy and designed to teach foundational, practical skills for cleaning up and combining data, performing analysis, and creating plots. As a self-taught coder, I empathize with the struggle many researchers face in trying to acquire a new technical skill or two "on their own"--but it doesn't have to be that way.
Technical training topics include:
I am also available for brief (~30 minutes) presentations on such topics as these:
On-request trainings are provided, free of charge, to Pitt affiliates but may be constrained or time-delayed depending on competing job duties.
I also offer one-off workshops open to the wider Pitt community and general public. The topics discussed are the same as in my on-request training, but these are typically shorter and in a more demonstrative than hands-on format. These are good for getting a first taste and a general sense of what the tool is like.
If you are interested in a workshop but unable to attend, please let me know. I would be happy to share materials with you as well as arrange one-on-one time for questions you have.
Kerzendorf, Wolfgang E., Ferdinando Patat, Dominic Bordelon, Glenn van de Ven, and Tyler A. Pritchard. 2020. “Distributed Peer Review Enhanced with Natural Language Processing and Machine Learning.” Nature Astronomy, April. https://doi.org/10.1038/s41550-020-1038-y.
Grothkopf, U., Meakins, S., & Bordelon, D. (2018). ESO telbib: learning from experience, preparing for the future. Proceedings of the SPIE, 10704. https://doi.org/10.1117/12.2311667
Grothkopf, U., Bordelon, D., Meakins, S., & Emsellem, E. (2017). On the Availability of ESO Data Papers on arXiv/astro-ph. The Messenger, 170, 58–61. https://doi.org/10.18727/0722-6691/5056
Patat, F., Boffin, H., Bordelon, D., et al. (2017). The ESO Survey of Non-Publishing Programmes. The Messenger, 170, 51–57. https://doi.org/10.18727/0722-6691/5055
Leibundgut, B., Bordelon, D., et al. (2017). Scientific Return from VLT instruments. The Messenger, 169, 11–15. https://doi.org/10.18727/0722-6691/5032
Bordelon, D., Grothkopf, U., et al. (2016). Trends and developments in VLT data papers as seen through telbib. Proceedings of the SPIE, 9910. https://doi.org/10.1117/12.2231697
Currently enrolled: Post-Baccalaureate student, University of Pittsburgh
Master of Library and Information Science (MLIS), Louisiana State University
B.A., English, concentration in Writing & Culture (Folklore, Linguistics), LSU
B.A., Spanish, LSU
B.A., History, LSU