
AMD
Automated GPU trace analysis system for LLMs, enabling rapid detection of performance regressions and kernel fusion opportunities across software builds.

The Acadev committee aims to make data science accessible by equipping students with practical skills and bridging the gap between classroom learning and real-world applications.
(01) — Our work
We lead and teach the DeCal course, “Introduction to Real World Data Science,” helping students of all experience levels build practical data science skills beyond the classroom.
Through a project-based curriculum, mentorship from our committee members, and an end-to-end team project using a real-world dataset, students gain the hands-on experience needed to tackle real data science and machine learning problems.
Our mission is to bridge the gap between classroom learning and industry practice, empowering students to build confidence and thrive in the rapidly evolving world of data science.

(02) — Portfolio
Alongside our teaching responsibilities, our committee also works on a client project during the semester. Here are some of the projects that have helped our members gain more project experience.
(03) — Committee life
Beyond the client work, this is what a semester in the committee looks like.

We plan and design the curriculum for Introduction to Real World Data Science, taking students through a full end-to-end project.

Our members give live lectures to dozens of students, practicing their teaching skills and reinforcing their understanding of complex concepts.

We have dinners, games, and committee socials that give everyone a reason to spend time together away from their usual responsibilities.
Interested?
We recruit in the first two weeks of Fall and Spring semester. Check the Join page for dates, timelines, and how to apply.