Attendees: IS. T. AbrahamBogdanov, UX. BhowmikChen, Z. Cheng, BH. Hu, Y-C Hu, J. Huang, R. Iyer, O. MironenkoKim, E. Kudeki, O. Mironenko, M. Raginsky, U. Ravaioli, C. Schmitz, A. Umrawal.
The first action in the meeting was to examine the new course ECE 364 for possible inclusion in the approved list of Software Laboratories. Ujjal Bhowmik asked whether MATH 257 is a sufficient prerequsite and wondered if ECE 313 should also be recommended. Ravi Iyer indicated that based on his experience with teaching ECE 313 and courses with machine learning content, ECE 313 is not necessary given the practical approach taken in ECE 364. By unanimous consent, ECE 364 was approved as a Software Laboratory course.
The group discussion then covered a range of issues important for the undergraduate experience. Chris Schmitz addressed how the growing enrollment which is putting a stress in the process to plan for courses and scheduling laboratories. Ravi Iyer commented how it is important to provide all students more curricular opportunities data science and machine learning, which are skills in great demand. While we have some introductory course and advanced ones suitable to prepare for research, we should introduce also other offerings at the intermediate level to give practical skills useful for applications on the job. These topics generated a fair amount of brainstorming. There should be an effort to define tracks for students to pursue these skills, which could range from specialized minors to more deliberate pipelines linking undergraduate and Master’s programs. Several members commented on the need to look at the existing courses in greater depth and develop a more strategic approach to curriculum, which often progress more through grass-root proposals driven by individual interests. The discussion will continue in future meetings, with anticipation for specific task which will be defined in the forthcoming charge letter from the department headJ. Schuh, Y-L Wei.
We had a preliminary discussion about ECE 498 “Deep Generative Models” submitted by Romit Roy Choudhury for first offering in Fall 2025. The course has been submitted with a companion ECE 598 for graduate students. Prerequisites are relatively low-level (MATH 257 and ECE 313) so on the one hand it should be accessible to undergraduates, but at the same time it is hard to see what makes it suitable for ECE 598 which implies a more advanced graduate audience. Given the goals the make the material accessible, we would have expected a 498 section, targeting beginning graduate students perhaps. While this is a graduate committee question, we still would like to have a much coordination as possible if undergraduates have to sit in the same classroom. The other courses with more direct overlap are ECE 598 LV and CS 598 AB , indeed 500-level courses. The proposal indicated an overlap of 40% to 50% with them, which seemed to be considerable for a separate offering. Since there was a mention of a slower treatment of topics and coverage of very modern topics, the committee would like to hear more about what differentiates your new course in terms of content and pedagogy. While it would be great to make the material accessible for lower-level students, the other side of the coin is that generative models may require a certain level of sophistication and there is genuine curiosity to understand better how you want to achieve your goals with the course. Romit has been invited to attend the next meeting of the committee and he has agreed to it. A question was raised also about area committee vetting. The course was reviewed by the Computer Engineering group, but it was suggested that also Signal Processing and Data Science should provide input given the subject matter. Romit has agreed to send them the proposal for feedback.
During the reminder of the meeting, we looked at the items in the department charge letter for the committee. Erhan Kudeki gave overview of the step needed to prepare material for the upcoming ABET review and the role the curriculum committee will need to play. Some discussion followed regarding introductory course which have been subject of some student complaint in townhall meeting settings. Chris Schmitz discussed ECE 210, for which om student have expressed discomfort with The chair wondered whether this is due to the fact that students might be expecting the same environment of ECE 110 and get a bit overwhelmed by the faster pace and increase in rigor. Jonathon Schuh share his thought on comparison between ECE 110 and ECE 210. There were suggestions to improve communications with students to explain the shift in pace that ECE 210 entails. The discussion shifted to consideration of more advanced courses (ECE 385, ECE 391) which tend to be difficult for many students and the measures taken to tamp down on instances of cheating and the role that AI tools (e.g. ChatGPT) might play. The more personalized nature of assignments does not seem to be too amenable to AI-assisted cheating/plagiarism in terms of code generation. This might be more possible in course like data structures which covers more standard material. One further conversation was about possible efforts to improve student enrollment in courses for the Quantum sequence. Simeon Bogdanov provided some context for that. Erhan Kudeki suggested to seek more participation from students interested in electromagnetics, who are about 20% of the EE student body.