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The 32nd Annual Conference on Neural Information Processing Systems (NeurIPS 2018) was held in Montreal between December 2 and 8. The proceedings brought together 8000 attendees and 1011 papers. It also included posters and workshops covering an array of algorithms, theories, experiments, and ideas presented by the crème de la crème of researchers on machine learning. Sieving through this massive database, the insightful platform Medium has shortlisted its influential list of papers and poster presentations. In the latter list is “Training DNNs with Hybrid Block Floating Point,” which was presented by EPFL researchers Mario Drumond, Tao Lin, Martin Jaggi, and Babak Falsafi.

Teaching is an art, and not all teachers are blessed with that skill. It is one thing to deliver lectures to a classroom, and quite another to connect with the students in that classroom. Katerina Argyraki, Tenure Track Assistant Professor at EPFL’s School of Computer and Communication Sciences, clearly belongs to the rarer category of teachers who believe in understanding students’ aptitudes and tailoring lessons accordingly. It is, therefore, not at all surprising that she was recently chosen as “best teacher.”

In early September, scientists, researchers, and industry leaders assembled in Rome for the 26th European Signal Processing Conference (EUSIPCO 2018). This year, the conference received 869 submissions, out of which about 550 were accepted. The reviewers sieved through those hundreds of important research papers to finally announce the Eurasip Best Student Paper Award. The authors of the winning paper are Mira Rizkallah (INRIA, visiting scholar at EPFL), Francesca De Simone (Post-doctoral fellow at EPFL), Thomas Maugey (INRIA), Christine Guillemot (INRIA), and Pascal Frossard (Associate Professor, EPFL).