Teaching Professor
CSE Data Science Undergraduate Programs, Program Representative
WiCS (Women in Computer Science) Supporter, Faculty Advisor Emeritus
Wash U Climbing Club, Faculty Advisor
m dot neumann at wustl dot edu
Department of Computer Science and Engineering
Washington University in St. Louis
Campus Box 1045
St. Louis, MO 63130
office: Lopata 204G
**NEWS**
Published at EAAI-24 colocated with AAAI-24: Practical Sentiment Analysis for Education: The Power of Student Crowdsourcing by Robert Kasumba, Marion Neumann [paper, video]
EAAI-24 was a great success! Read more about EAAI and AAAI-24 here: What Excited Us at AAAI 2024
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Marion is the recipient of the 2024 CSE Department Teaching Award. The award recognizes her contributions to our programs over the years, and in particular her recent efforts in introducing team-based active learning in CSE 217A.
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Marion at the Researchers IdeaBounce event hosted by the Skandalaris Center
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We Belong! CS@Wash U Fl23 was a huge success!
Thanks for participating 🙂
My Educational Mission
- advancing Data Science, AI, and CS education
- creating an inclusive and student-centered learning environment
- advancing equity in higher-education
**In the (WashU) news**
WeBelong! provides mentorship, community for computer science students
AI for STL summer camp pilot was a success!
CSE and Math launched the joint major in Data Science! Contact me if you have questions about the DS curriculum.
SIGCSE TS 2021 publication: M. Neumann, R. Linzmayer, Capturing Student Feedback and Emotions in Large Computing Courses: A Sentiment Analysis Approach [paper, presentation]
About me
I am a Teaching Professor at Washington University in St. Louis. I teach and develop courses in machine learning and data science on all levels in the undergraduate and graduate curriculum. I also oversee the data science bachelor programs in the CSE department und promote diversity and inclusion in CS education. I was the WiCS (Women in Computer Science) Faculty Advisor from 2017 to 2022. In my research we study ways to help course instructors bridge the feedback gap that arises when teaching and managing large CS classes. To this end we use sentiment and text analysis to predict emotions in students’ unit-of-study or homework reflections.
I joined the CSE faculty in July 2015 as a Lecturer for machine learning and cloud computing. Before that, I was a phd student in the Knowledge Discovery and Machine Learning research group at the University of Bonn (2010–2015) and a research assistant at the Fraunhofer Institute for Intelligent Analysis and Information Systems IAIS and the Bonn-Aachen International Center for Information Technology.
Education:
Ph.D. in Computer Science (Dr. rer.-nat.), University of Bonn, Germany
M.S. in Business Mathematics (Diplom Wirtschaftsmathematik, Univ.), University of Ulm, Germany
B.S. in Business Mathematics, University of Ulm, Germany
Oh, and try to remember:
“Don’t move faster than the speed of thought.”
Brad Smith