cv
a quick overview of some professional experiences
Overview
| Name | Lucius EJ Bynum |
| Position | PhD Candidate, NYU Center for Data Science Microsoft Research PhD Fellow |
| Website | luciusbynum.com |
Education
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2020 - Present NYC, New York
Ph.D., Data Science (Ongoing)
Center for Data Science, New York University -
2014-2018 Claremont, CA
B.Sc., Data Science
Harvey Mudd College - Graduate with Distinction (2018)
- Henry A. Krieger Prize in Decision Sciences (2017)
- Dean's List (2014 - 2017)
- Superior Academic Performance (2014)
Funding and Awards
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2022 - Present -
2020 - Present NRT Future PhD Fellowship
Experience
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2020 - Present NYC, New York
Graduate Research Fellow
Center for Responsible AI, New York University -
2018-2020 Seattle, WA
Post-Baccalaureate Research Associate
Pacific Northwest National Laboratory -
Summer 2017 Chicago, IL
Software Engineering Intern
Civis Analytics -
Summer 2016 Los Angeles, CA
Team Lead, Research in Industrial Projects for Students
Institute for Pure and Applied Mathematics, UCLA
Teaching and Mentoring
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2022-Present USA + Ukraine
Research Advisor, R/AI Research Program
NYU Center for Responsible AI + Ukrainian Catholic University + National University of Kyiv-Mohyla Academy -
Spring 2023 NYC, New York
Teaching Assistant + Section Leader, Responsible Data Science
New York University -
Spring 2022 NYC, New York
Instructor, We Are AI
New York University + Queens Public Library -
2017-2018 Claremont, CA
Operations Research Mathematics Grader
Harvey Mudd College -
2015-2018 Claremont, CA
Writing Center Consultant
Harvey Mudd College -
2016-2017 Claremont, CA
Academic Excellence Mathematics Tutor
Harvey Mudd College -
2016-2017 Claremont, CA
Student Mentor
Harvey Mudd College
Publications
- For more info, see my publications page.
- Bynum, L.E.J., Loftus, J.R., & Stoyanovich, J. Counterfactuals for the Future. Proceedings of the AAAI Conference on Artificial Intelligence (AAAI 2023).
- Bell, A.; Bynum, L.E.J.; Drushchak, N.; Zakharchenko, T.; Rosenblatt, L.; & Stoyanovich, J. The Possibility of Fairness: Revisiting the Impossibility Theorem in Practice. Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency (FAccT 2023).
- Bynum, L.E.J.; Arif Khan, F.; Konopatska, O.; Loftus, J.R.; and Stoyanovich, J. An Interactive Introduction to Causal Inference. VISxAI: Workshop on Visualization for AI Explainability (VISxAI 2022).
- Bynum, L.E.J.; Loftus, J.R.; and Stoyanovich, J. Disaggregated Interventions to Reduce Inequality. Equity and Access in Algorithms, Mechanisms, and Optimization (EAAMO 2021).
- Bynum, L.E.J.; Doster, T.; Emerson, T.H.; and Kvinge, H. Rotational Equivariance for Object Classification Using xView. 2020 IEEE International Geoscience and Remote Sensing Symposium (IGARSS 2020). Note: alphabetical order.
- Loftus, J.R.; Bynum, L.E.J.; and Hansen, S. (2024). Causal Dependence Plots. Under Review.
- Rosenblatt, L.; Bynum, L.E.J.; Bell, A.; and Stoyanovich, J. (2024). A General Framework for Approximate Fairness. Under Review. Note: equal contribution.
- Bynum, L.E.J.; Loftus, J.R.; and Stoyanovich, J. (2024). A New Paradigm for Counterfactual Reasoning in Fairness and Recourse. Under Review.