CDS STUDENT
SEMINAR
SERIES
Join us every Friday at Boston University Faculty of Computing and Data Sciences (CDS) for cutting-edge research presentations by CDS PhD students across data science, AI, and beyond.
What We Do
We are a student-run initiative within the PhD department of Boston University Faculty of Computing & Data Sciences, dedicated to fostering knowledge sharing and academic growth across our community.
Our Mission?
Create a space where students can explore, present, and discuss the research topics they're passionate about in a supportive, collaborative environment.
Every Friday from 12:00 to 1:00 PM in CDS 1646, CDS researchers present on work that excites them—whether it's their current research, an inspiring paper they've discovered, or a hands-on workshop in their area of expertise. From artificial intelligence to biological sciences, our seminars cover the full breadth of computer and data science.
Meet the Organizers
Freddy Reiber
PhD student in CDS studying how society influences technology and how technology influences society.
Lingyi Xu
PhD student in CDS addressing the challenge of modality missingness in multimodal learning across visual, tabular, and textual data.
COMING UP
Stop the Nonconsensual Use of Nude Images in Research (Published at NeurIPS 2025 - Oral)
by Princessa Cintaqia
In order to train, test, and evaluate nudity detection models, machine learning researchers typically rely on nude images scraped from the Internet. Our research finds that this content is collected and, in some cases, subsequently distributed by researchers without consent, leading to potential misuse and exacerbating harm against the subjects depicted. We argue that the distribution of nonconsensually collected nude images by researchers perpetuates image-based sexual abuse and that the machine learning community should stop the nonconsensual use of nude images in research. To characterize the scope and nature of this problem, we conducted a systematic review of papers published in computing venues that collect and use nude images. Our results paint a grim reality: norms around the usage of nude images are sparse, leading to a litany of problematic practices like distributing and publishing nude images with uncensored faces, and intentionally collecting and sharing abusive content. We conclude with a call-to-action for publishing venues and a vision for research in nudity detection that balances user agency with concrete research objectives. You can check out the paper here: openreview.net/pdf?id=Ev5xwr3vWh
Get Involved
Ready to join our community of learners, researchers, and innovators?