Erika Melder
(they/them)
PhD Student
Research Interests
- Human-computer interaction
- Algorithms and theory
Education
- MS in Computer Science, University of Maryland
- BS in Computer Science, University of Maryland
Biography
Erika Melder is a PhD student at the Khoury College of Computer Sciences at Northeastern University. They earned both their bachelor’s and master’s degrees in computer science from the University of Maryland.
Melder is interested in the structures of social media platforms, as well as the ways users theorize about and understand those structures to communicate information. They are also interested in how certain information can be amplified or suppressed by social and technological methods, and the implications of this information control for sociotechnical equity. They are advised by Assistant Professor Michael Ann DeVito.
Prior to joining Northeastern, they worked as a policy analyst fellow at the American Mathematical Society Washington Office in Washington, D.C. They are also an advocate for underrepresented populations in STEM, particularly LGBTQ+ representation.
Publications
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A Chronology of Set Cover Inapproximability Results
Citation: Erika Melder (2021). A Chronology of Set Cover Inapproximability Results. CoRR, abs/2111.08100. -
Deep Learning-Based Data Fusion Method for In Situ Porosity Detection in Laser-Based Additive Manufacturing
Citation: Tian, Q., Guo, S., Melder, E., Bian, L., and Guo, W. “. (December 17, 2020). "Deep Learning-Based Data Fusion Method for In Situ Porosity Detection in Laser-Based Additive Manufacturing." ASME. J. Manuf. Sci. Eng. April 2021; 143(4): 041011. https://doi.org/10.1115/1.4048957