Author: Kaibo Liu
Please be aware of Industrial & Systems Engineering Research Conference (ISERC) this year is on May 30 – June 2, 2015 in Nashville, Tenn. Details can be found: http://www.iienet2.org/Annual2/default.aspx
I would like to recommend two featured panel discussion sessions on data analytics that I chaired in ISERC this year. Please don’t miss the sessions!
1. “ Panel Discussion – Industrial analytics courses: the needs, contents and expectations”:
Date: Sunday, May 31
Invited Panelists: Prof. Shiyu Zhou from UW-Madison, Prof. Diego Klabjan from Northwestern University, Prof. Satish Bukkapatnam from Texas A&M University, and Prof. Soundar Kumara from Penn State University.
The goal of this session is to push the frontiers and increase the exposures of the analytics courses offered by the IE department. During the discussions, a wide range of topics will be included but not limited to: the necessary and optional technical contents that should be included in the analytics course, the effective ways of teaching analytics materials, the selections of the analytics software, the design of the analytics projects, the expected skills for students after taking the analytics course, and the experience and challenges learned (both good and bad) from past and current analytics course. Through this panel discussion, we may establish an interactive forum for discussions and sharing of analytics materials, which strengthens the curriculum and enhances the representative of IE department for analytics research and education.
2. “ Panel Discussion – Present and Future of Analytics Programs ”:
Date: Monday, Jun 1
Time: 11 AM – 12:15PM
Invited Panelists: Prof. Joel Sokol from Georgia Tech, Prof. Diego Klabjan from Northwestern University, Prof. David Shmoys from Cornell University, and Prof. Michael Rappa from NC State University.
The goal of this session is to push the frontiers and increase the exposures of the analytics programs. During the discussions, a wide range of topics will be included but not limited to: the effective ways of teaching analytics courses, the balanced designs of course curriculum from multidiscipline, the unique strengths and resources of different analytics programs, the expected skills for students after the analytics training program, the experience learned (both good and bad) from past and current analytics program, and the future strategies for better education, improvement and sustainability of analytics program.