Netdev 0x17 venue

Manya Ghobadi is faculty in the EECS department at MIT. Her research spans different areas in computer networks, focusing on optical reconfigurable networks, networks for machine learning, and high-performance cloud infrastructure. Her work has been recognized by the ACM-W Rising Star award, Sloan Fellowship in Computer Science, ACM SIGCOMM Rising Star award, NSF CAREER award, Optica Simmons Memorial Speakership award, best paper award at the Machine Learning Systems (MLSys) conference, as well as the best dataset and best paper awards at the ACM Internet Measurement Conference (IMC). Manya received her Ph.D. from the University of Toronto and spent a few years at Microsoft Research and Google before joining MIT.

Manya will be speaking to us about the hot topic of machine learning workloads and networking. What makes machine learning workloads challenging? She will explore three dimensions of designing next-generation machine learning systems: congestion control, network topology, and computation frequency. More details later.

Come, listen, interact and benefit from some wisdom from professor Ghobadi.