The top scariest possible results

Washington Irving was a famous writer of the early 1800’s who is best known for his short stories. The Legend of Sleepy Hollow was based on the folklore that each Halloween a decapitated Hessian soldier, killed in the American Revolution, rises as a ghost, a nasty ghost, who searches for his lost head.

Today is Halloween and while Ken and I are not searching for any lost heads, we do believe it is a good day to think about scary stories.

An initiative for women in computing

 AIA source

Louise Bethune was the first female professional architect in the United States, and possibly the world. She worked in Buffalo in the late 1800s through the early part of the 20th century.

Today we roll out ideas for an initiative on attracting women to computer science.

Some football wisdom from Dick Karp

 Cropped from S.I. Kids source

John Urschel is a PhD student in the Applied Mathematics program at MIT. He has co-authored two papers with his Penn State Master’s advisor, Ludmil Zikatanov, on spectra-based approximation algorithms for the ${\mathsf{NP}}$-complete graph bisection problem. A followup paper with Zikatanov and two others exploited the earlier work to give new fast solvers for minimal eigenvectors of graph Laplacians. He also plays offensive guard for the NFL Baltimore Ravens.

Today Ken and I wish to talk about a new result by the front linesman of ${\mathsf{NP}}$-completeness, Dick Karp, about football.

In the context of stable matching problems

Jamie Morgenstern is a researcher into machine learning, economics, and especially mechanism design.

Today Ken and I would like to discuss a joint paper of hers on the classic problem of matching schools and students.

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The winner of the 2016 ACM-IEEE Knuth Prize

 Coursera source

Noam Nisan has been one of the leaders in computational complexity and algorithms for many years. He has just been named the winner of the 2016 Donald E. Knuth Prize.

Today we congratulate Noam and highlight some of his recent contributions to algorithmic economics and complexity.

Local rules can achieve global behavior

Sarah Cannon is a current PhD student in our Algorithms, Combinatorics, and Optimization program working with Dana Randall. Sarah has a newly-updated paper with Dana and Joshua Daymude and Andrea Richa entitled, “A Markov Chain Algorithm for Compression in Self-Organizing Particle Systems.” An earlier version was presented at PODC 2016.

Today Ken and I would like to discuss the paper, and relate it to some recent results on soft robots.