Major in computer network, including distributed deep learning (DDL or DML), datacenter network (DCN), and content delivery network (CDN). (Prof. Yang Xu)

Major in computer science (CS).

Major in science.

Daily content maintenance for the institute website.

Computer architecture course-related QAs, design, and correction of homework and exams, Chisel-based RISC-V CPU evaluation platform design and deployment (Chisel, Docker).

Study of the content delivery network (CDN) and its load-balance algorithms.

Ninechapter front-end development (React, Django), LintCode front-end development (React, Django), and LintCode online code judgment platform development (C++, Docker).

A joint study of hardware-side channel attacks and machine learning methods.

Study related to machine learning, recommendation algorithms, and recommendation systems.

Software Defined Topology Testbed (SDT) offers a scalable, cost-effective, and time-efficient solution for conducting diverse network research experiments.

A synchronization approach that enhances the throughput of PS-based DDL training by overlapping the communication with the computation by a 2-stage synchronization strategy.

A customized transmission protocol that improves distributed machine learning throughput by properly exploiting link packet loss.

A rule semantics enabler enables multiple TCAM update algorithms in commodity SDN switches, which works as a transparent middle layer without modification to network devices.

This invention, related to communication technology, introduces a distributed collection communication method and related equipment. It sends and receives 'interest packets' between computing nodes in a cluster to process and reduce data. The method is designed to make the Named Data Networking (NDN) architecture compatible with global data reduction algorithms.