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.

Fridays • 12–1 PM • CDS 1646

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

The students who run the series week to week.

Freddy Reiber

Freddy Reiber

Freddy is a third-year PhD student in the Computing and Data Science department at Boston University, and advised by the fantastic Allison McDonald. His work explores how power dynamics are shifted by technology with a focus on applying human-driven methods to complex issues. Currently, his projects are on 2nd order dynamics in digital spaces within labor unions and the motivations used by cryptographers for their research.

Lingyi Xu

Lingyi Xu

Lingyi Xu is a Ph.D. student in the Faculty of Computing & Data Sciences at Boston University. She works with Professor Vijaya B. Kolachalama to seek solutions to data missingness in multimodal learning. Her work investigates how different data modalities can be represented and aligned to make learning more adaptable and their relationships more interpretable.

Yan (Stella) Si

Yan (Stella) Si

Stella is a PhD student at Boston University Computing and Data Sciences, where she works at the intersection of cognitive science and AI.

Her research centers on modeling human decision making, combining neural networks with traditional cognitive models to uncover the psychological principles behind how we choose. She is also building large-scale, high-quality datasets to drive this work forward.

Outside the lab, she is working on startup building. Check out her work on GitHub: github.com/sbel2

Coming Up

We are currently on break!

We will be back in session next semester! More details soon.

Get Involved

Ready to join our community of learners, researchers, and innovators?