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Data Provenance, also referred to as Data Lineage, is metadata that describes from where a digital artifact came. People have argued that such metadata is useful for myriad applications such as reproducibility, forensic analysis, intrusion detection, data retention, regulatory compliance, and more. Unfortunately, the vast majority of work in the area focuses on standardization and collection, not applications. As a result, adoption of provenance in industry has been practically non existent.

With rapidly growing amounts of experimental data, machine learning is increasingly crucial for automating scientific data analysis. However, many real-world workflows demand expert-in-the-loop attention and require models that not only interface with data, but also with experts and domain knowledge. My research develops full stack solutions that enable scientists to scalably extract insights from diverse and messy experimental data with minimal supervision. My approaches learn from both data and expert knowledge, while exploiting the right level of domain knowledge for generalization.

In the talk I will share insights and experiences gained during my work on three industrial research projects in distributed systems. The three research projects reached production and had profound, sometimes surprising, impact on foundations of distributed computing.

Connect and celebrate with your classmates at this casual, fun reception honoring our returning alumni.  The reception will feature finger food, beer, wine, and other beverages.  You will be able to talk to students about their ongoing work and, weather permitting, enjoy games on the LSRC lawn.  Register now to let us know you will join us.

Register: https://rsvp.duke.edu/ORW8M0

“The classroom remains the most radical space of possibility in the academy” -bell hooks

This panel of undergraduates will share their perspective as a student enrolled in a course that was developed as a result of the 3C (Cultural Competence in Computing) Fellows Program. With representation across multiple institutions, panelists will reflect on personal experiences, classroom dynamics, and key learnings derived from their time in the course. Topics will also include suggestions for educators who are looking to teach a course on an identity-inclusive topic.

In this talk we examine how high performance computing has changed over the last ten years and look toward the future in terms of trends. These changes have had and will continue to impact our numerical scientific software significantly. A new generation of software libraries and algorithms are needed for the effective and reliable use of (wide area) dynamic, distributed, and parallel environments.

The Computer Science 2023 graduation ceremony will be held at the Durham Convention Center, Ballrooms A-C, 301 W. Morgan Street, Durham, NC 27701. Register Now: https://bit.ly/register-dukecs2023commencement