CDS Lectures & Seminars

The Faculty of Computing & Data Sciences hosts a suite of lecture and seminar series designed to foster interdisciplinary scholarship, critical dialogue, and community engagement. Open to students, faculty, and collaborators across BU and beyond, these programs bring together leading voices to explore the intersections of computing, data, and society. CDS Lectures & Seminars are open to CDS faculty, students, staff, partners, and the broader BU community.

CDS Colloquium Series

The CDS Colloquium Series was developed to build an intellectual community within and beyond the academic unit. Since its inception, the series has welcomed dozens of visiting scholars to engage with BU faculty, students, and staff on a broad range of topics in computing and data sciences. While the series is primarily intended for the CDS community, we welcome interest and attendance from across the Boston University campus and beyond.

Led by: CDS Faculty Affairs Office

Industry Connections Lecture Series

The Industry Connections Lecture Series offers valuable insights from experts, providing a deep dive into current trends and challenges within a specific field. Each session is designed to enhance understanding and career prospects through practical advice and real-world examples. The series, organized by Leonidas Kontothanassis, MassMutual Professor of the Practice of Computing & Data Sciences and Director of Industry Engagement, welcomes data science experts from a variety of sectors including technology, healthcare, film industries, and more.

Intellectual Property and Information Law

The Faculty of Computing & Data Sciences and School of Law co-host a dynamic seminar series exploring key issues in intellectual property (IP) and information law. Kicking off in late September and continuing through early December, the series features expert speakers and panel discussions on a wide range of topics—including artificial intelligence (AI), copyright, "copywashing," and the evolving landscape of IP and information governance. Sessions take place at both the Duan Family Center for Computing & Data Sciences and the BU School of Law. All students are encouraged to attend.

Led by:

  • Stacey Dogan, Professor of Law
  • Ngozi Okidegbe, Moorman-Simon Interdisciplinary Career Development Assistant Professor of Computing & Data Sciences & Associate Professor of Law
  • Mayank Varia, Associate Professor of Computing & Data Sciences

Machine Learning Symposium

The CDS Machine Learning Symposium brings together leading scholars in machine learning to explore cutting-edge developments and foundational technologies shaping the field. Hosted by the Faculty of Computing & Data Sciences, the symposium promotes cross-disciplinary dialogue around core technical areas such as algorithmic design, model architecture, and optimization techniques.

Developed by Assistant Professors Aldo Pacchiano and Xuezhou Zhang, the symposium invites participants from across BU and beyond to engage with current trends, challenges, and innovations in machine learning research.

Led by:

PhD Student Seminar Series

The CDS PhD Student Seminar Series offers a low-pressure, supportive space for doctoral students to present their research, sharpen communication skills, and receive feedback from peers and faculty. Open to all areas of data science, the series also fosters community by encouraging cross-disciplinary learning and connection. The series meets bi-weekly on Fridays from 11 AM to noon, followed by lunch. Students interested in presenting can contact the organizers.

Led by: Freddy Reiber and Lingyi Xu

Quantitative Biology Seminar Series

The Quantitative Biology Seminar Series, jointly launched by the Faculty of Computing & Data Sciences and the BU Bioinformatics Program, is a pedagogical initiative designed to connect computationalists, quantitative experimentalists, and theorists across disciplines. The series features cutting-edge research and facilitates meaningful dialogue between communities with shared interests in biological systems, modeling, and computation.

The series was developed by Brian Cleary and Pawel Przytycki, Assistant Professors of Computing & Data Sciences and core faculty members in the Bioinformatics Program, along with Pankaj Mehta, Professor of Computing & Data Sciences. Attendees can expect in-depth presentations, cross-disciplinary discussions, and networking opportunities that foster collaboration and broaden research horizons.

Led by:

  • Brian Cleary, Assistant Professor of Computing & Data Sciences and Core Faculty, Bioinformatics Program, Biology + Biomedical Engineering
  • Pawel Przytycki, Assistant Professor of Computing & Data Sciences and Core Faculty, Bioinformatics Program
  • Pankaj Mehta, Professor of Computing & Data Sciences, Professor of Physics

Social Justice for Data Science Lecture Series

The Social Justice for Data Science Lecture Series brings together leading scholars in law, computer science, the humanities, and the social sciences to examine the current state of data science and social justice. The goal of the series is to engage with the relationship between justice (as a historically contingent and value-laden category) and data science (with a focus on datafication, automation, predictive analytics, and algorithmic decision-making).

This series was developed by Ngozi Okidegbe, Moorman-Simon Interdisciplinary Career Development Assistant Professor of Computing & Data Sciences and Associate Professor of Law, and Allison McDonald, Assistant Professor of Computing & Data Sciences. Their aim is to explore how data science can advance, transform, or hinder justice-oriented movements, particularly those led by underrepresented and politically marginalized communities—and to draw lessons that can help reorient the field of data science toward justice.

Led by:

  • Ngozi Okidegbe, Moorman-Simon Interdisciplinary Career Development Assistant Professor of Computing & Data Sciences and Associate Professor of Law
  • Allison McDonald, Assistant Professor of Computing & Data Sciences

Teaching Tea 

Teaching Tea is a monthly gathering designed for Faculty of Computing & Data Sciences instructors to come together, share ideas, and strengthen their teaching practice. Organized by Kevin Gold, the series offers a relaxed but purposeful space for conversation, collaboration, and problem-solving around the craft of teaching.

Each month, faculty will explore topics that matter most to their classrooms and students. Past and upcoming discussions include scaling and revising classes, making the most of course evaluations, designing effective syllabi and assignments, using auto-graders, and best practices for giving and receiving feedback. Sessions often include short presentations, group reflections, and ample time for open discussion, ensuring that every participant leaves with practical takeaways they can apply immediately.

Led by:

  • Kevin Gold, Associate Professor of the Practice of Computing & Data Sciences and Preceptor for Instruction

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