Suraj Rampure
“soo-rudge rahm-poo-ray”
Lecturer III
Computer Science and Engineering, University of Michigan
4721 Beyster Building
rampure@umich.edu
Hey! 👋 I’m a member of the teaching faculty in Computer Science and Engineering at the University of Michigan. I am affiliated with MIDAS, serve on the undergraduate computer science and data science program committees, and am one of the hosts of Faculty Chats (come say hi!).
Previously, I taught in the Halıcıoğlu Data Science Institute at the University of California, San Diego, where I received the campus-wide Distinguished Teaching Award in 2024. I earned BS and MS degrees in Electrical Engineering and Computer Sciences from the University of California, Berkeley, and I’m originally from Windsor, Ontario 🇨🇦.
On this page: Teaching • Scholarship • Awards
Other links: CV • Teaching Faculty Application Materials • Rec. Letters • Python Teaching Commons
Totally random: Travel Recommendations
Teaching
University of Michigan, Ann Arbor (2024-)
EECS 245: Mathematics for Machine Learning 🧠Winter 2026, Fall 2025
EECS 398: Practical Data Science 🛠️
Spring 2025 (Half-Term) • Winter 2025 • Fall 2024
Other Teaching
Building Robust ML Models (MIDAS Biomedical Researchers Summer Academy 2025)
University of California, San Diego (2021-2024)
DSC 40A: Theoretical Foundations of Data Science I 🧠Spring 2024 • Fall 2021
DSC 95: Tutor Apprenticeship in Data Science 🧑🏫
Spring 2024 • Spring 2023
DSC 80: Practice and Application of Data Science 💪
Winter 2024 • Winter 2023 • Spring 2022
DSC 180AB: Data Science Project (Senior Capstone) 👷
Fall 2023 + Winter 2024 • Fall 2022 + Winter 2023
DSC 10: Principles of Data Science 📊
Fall 2023 (with Janine Tiefenbruck & Rod Albuyeh) • Spring 2023 • Fall 2022 (with Janine Tiefenbruck & Puoya Tabaghi) • Winter 2022 • Fall 2021 (with Janine Tiefenbruck)
CSS 201S: Introduction to Python Bootcamp (Week 1 only) 🥾
Summer 2022
DSC 90: History of Data Science Seminar 📚
Spring 2022 • Winter 2022
University of California, Berkeley (2016-2021)
Data 94: Introduction to Computational Thinking with DataSpring 2021 (now known as Data 6)
Data 100: Principles and Techniques of Data Science
Summer 2020 (with Allen Shen)
TA: Fall 2020 • Spring 2020 • Fall 2019 • Spring 2019 • Fall 2018
CS 198-087: Introduction to Mathematical Thinking [DeCal]
Spring 2019, Fall 2018
CS 70: Discrete Mathematics and Probability Theory
TA: Summer 2019
CS 375: Teaching Techniques for Computer Science
TA: Summer 2019
CS 61A: Structure and Interpretation of Computer Programs
TA: Spring 2018
Data 8: Foundations of Data Science
TA: Fall 2017
Tutor: Spring 2017
Scholarship
Papers
- The Challenges of Evolving Technical Courses at Scale: Four Case Studies of Updating Large Data Science Courses. Sam Lau, Justin Eldridge, Shannon Ellis, Aaron Fraenkel, Marina Langlois, Suraj Rampure, Janine Tiefenbruck, Philip Guo. In ACM Conference on Learning @ Scale (L@S), 2022.
- A New Data-Focused Introductory Programming Course. Suraj Rampure. 2021. Master’s technical report, UC Berkeley EECS.
- Experiences Teaching a Large Upper-Division Data Science Course Remotely. Suraj Rampure*, Allen Shen*, and Josh Hug. 2020. In Proceedings of the 52nd ACM Technical Symposium on Computer Science Education (SIGCSE ’21). (slides) (video)
Talks
- RISE and Shine: Teaching with Jupyter Notebooks in Real Time. Suraj Rampure, Nishant Kheterpal, and Janine Tiefenbruck. Talk at JupyterCon 2025.
- Different Mediums for Different Audiences: A Capstone Case Study. Suraj Rampure. Talk at Teaching and Evaluating Data Communication at Scale 2024. (slides) (video)
- Otter-Grader: A Lightweight Solution for Creating and Grading Jupyter Notebook Assignments. Suraj Rampure, Christopher Pyles, Justin Eldridge, and Lisa Yan. Talk at Jupytercon 2023. (materials) (video)
- Data 6: A New Introductory Course. Talk at 2021 National Workshop on Data Science Education. (slides) (video)
- Various sessions on Data 100: Principles and Techniques of Data Science at 2020 National Workshop on Data Science Education. (pre-recorded talk) (Q&A) (workshop)
Panels and Related Sessions
- A New Class of Teaching-Track Faculty: No Ph.D. Required. Birds of a Feather session at Proceedings of the 56th ACM Technical Symposium on Computer Science Education (SIGCSE ‘25).
- A New Class of Teaching-Track Faculty: No Ph.D. Required. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education (SIGCSE ‘23). (slides)
- Introduction to Computational Thinking with Data and Society. In 2022 National Workshop on Data Science Education.
- A New Class of Teaching-Track Faculty: No Ph.D. Required. In Proceedings of the 53rd ACM Technical Symposium on Computer Science Education (SIGCSE ‘22). (slides)
Media
- UC San Diego Today: Signature Program Demonstrates How UC San Diego Undergraduates Learn to Transform Data into Action
- ComputingPaths at UC San Diego: Meet Suraj Rampure, Lecturer in the Halıcıoğlu Data Science Institute
- UC Berkeley Research News: UC Berkeley and Tuskegee University Announce Data Science Partnership
- UC Berkeley Data Science Education Podcast: The Importance of Data Science Course Staff