Minutes November 13, 2024

Attendees: I. T. Abraham, U. Bhowmik, Z. Cheng, B. Hu, Y-C Hu, J. Huang, R. Iyer, O. Mironenko, 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 head.