From the Dean's Desk - Oct. 28, 2020

Dear GT Computing community,

Georgia Tech Dean of Computing Chrales Isbell

As you may have heard already, the College of Computing and the Ivan Allen College of Liberal Arts are launching a new center together. The new Ethics, Technology, and Human Interaction Center (ETHICx) will advance, um, the ethics of technology-centered research, education, and policy.

Our own Ayanna Howard will co-direct the center, and Betsy DiSalvo will be on the leadership team. This new center builds on a strong foundation of work inside the College and elsewhere at the Institute and will support and extend our push toward Responsible Computing, through creating an interdisciplinary community of experts who study the impacts of our work on a variety of communities (including our own). I am very excited and looking forward to all that will come of this effort.

On another note, it’s pretty clear that many of us can all feel the stress level rising as election season draws to a close (at least I hope it’s drawing to a close… is there a Zeno’s paradox for elections?). Given the raw energy in the air, I think we can expect that stress to come spilling out in at least some of our classrooms (whether they be physical or virtual). I encourage all of you to check out the Institute’s new workshop on teaching during the election, and on managing student’s political emotions.

Finally, I’d like to take a moment to congratulate Richard Peng and Santosh Vempala (both members in good standing of the School of CS) for winning the Best Paper Award for this year’s ACM-SIAM Symposium on Discrete Algorithms (SODA21) with their paper, “Solving Sparse Linear Systems Faster than Matrix Multiplication.”  Well done, and thank you for representing the best of our community.

Stay safe everyone.



Charles L. Isbell, Jr.
John P. Imlay, Jr. Dean
College of Computing
Georgia Tech

EA: Alicia Richhart,, 404-894-8357

Don't just adopt opinions,  develop them

The ethics:

Teaching during the election:

Solving Sparse Linear Systems Faster than Matrix Multiplication:

The best: