Portrait of Thomas Moscibroda

Thomas Moscibroda

Principal Research Manager
Cloud & Mobile Research Group


Thomas Moscibroda is a Principal Researcher and founding manager of the Cloud & Mobile (C&M) Research Group at Microsoft Research Asia. He is also the Chair Professor for Network Science at the Institute for Interdisciplinary Information Sciences (IIIS) at Tsinghua University. Before moving to China in 2011, Thomas was a member of the Systems Research group at Microsoft Research in Redmond, and he was also an affiliate member of the Networking Research and Computer Architecture Research groups, respectively.

Thomas’ research interests are in cloud computing, distributed systems, mobile and distributed computing, and networking, with ongoing projects in each of these areas. He has a particular focus on algorithmic and mathematical approaches to practical system design. He obtained his PhD in 2006 from ETH Zurich, and was awarded the ETH Medal for his doctoral thesis. His research is documented in more than 60 research papers, and he has received Best Paper Awards at several top-tier conferences, including IPSN 2007, SIGCOMM 2009, NSDI 2009, ASPLOS 2010, EuroSys 2012, PODC 2004 and 2012, as well as DISC 2015. His articles on DRAM scheduling and on-chip networking in multi-core systems were selected as IEEE Micro Top-Pick Computer Architecture papers in 2008 and 2010, respectively. He is also the recipient of the MICS Research on Communications Award by the National Research Foundation of Switzerland (NCCR) for his contributions to the area of Mobile Communications & Information Systems.


We are hiring! We are right now looking for exceptional full-time researchers and research interns. If you are interested in working with me and our team on cutting-edge research, please send me an email. We are particularly looking for candidates in Cloud Computing, Networking, and Mobile Computing, including people interested in handling Big Data, Databases, Algorithms and Optimization. We also have projects related to Blockchain technology. In other words, we are interested in candidates with expertise across a wide range of fields, ideally with strong first-hand system skills in real large-scale systems and networks. We are looking for freshly graduated campus hires as well as experienced people from industry; we are interested in hiring Chinese as well as non-Chinese; and we most definitely encourage female candidates. MSRA is a great place to work at in so many ways; so do not hesitate and send me your application!



Cloud Computing & Networking

  • Full-Utilization Data-Center: Hyperscale public cloud providers such as Microsoft invest billions of dollars into their cloud infrastructure. It is therefore critically important that the provisioned resources are as efficiently used as possible. For the past several years, we have been working closely with core Azure infrastructure teams to design state-of-the-art resource utilization technologies, including allocation and scheduling algorithms that maximize the utilization in our data centers. Numerous of our solutions are now in worldwide production across our Azure datacenters.
  • Intelligent Blockchain: Blockchain is an emerging technology with the potential to change the way businesses, industries, and public organizations conduct and verify transactions, thereby streamlining business processes, saving money, and reducing the potential for fraud. In our Blockchain project, we are currently working to design new innovative Blockchain (particularly Blockchain-as-a-Service (BaaS)) applications, to make blockchain more efficient, and to gain fundamental novel insight into Blockchain networks.
  • Data Center Networking: Data center networks hold a pivotal role in cloud computing, as it interconnects all of the data center resources. DCNs need to be scalable and efficient, connecting hundreds of thousands of servers to handle the growing data requirements of big data applications, and low-latency demands on online services. We work closely with Azure Networking on state-of-the-art (software-defined) networking technologies that power Microsoft’s data center networks.
  • FPGA-Accelerated Networking: Building network infrastructure for mega scale data centers and ever increasing data transfer rates requires fundamental shifts in networking technology. In this project, we are working on using FPGA-based smart network cards (NIC) and other hardware-based acceleration techniques to achieve unprecedented accelerated network performance.
  • Graph Computation & NoSQL: We are working on a highly efficient middle layer that can enhance any existing data storage system (SQL Server, Oracle, Azure DocumentDB) with graph processing capabilities. The underlying principle behind our work is a novel “NoSQL on SQL” approach – we believe (and prove!) that contrary to popular believe, a vast majority of NoSQL workloads can be highly efficiently managed and processed on top of existing data stores.
  • Next-Generation, Storage-Class Memory Systems: Emerging non-volatile memory (NVM) hardware is changing the landscape of data storage. Traditional dichotomy between fast volatile memory and slow persistent disks is shifting towards a unified memory-level persistent storage layer, which largely unlocks the performance potential of many applications. To that end, we revisit and innovate on many aspects of the traditional architecture and system stack, spanning processor/memory controller design, operating system/software framework and programming techniques.

Mobile Computing

  • FollowUs — Infrastructure-Free Plug-and-Play Indoor Navigation: There has been a proliferation of research work on indoor positioning in previous years. In this project, we take a different and novel approach. Focusing on the more constrained problem of navigation, and using the unique properties of the geo-magnetic field, we are building an easy-to-deploy completely infrastructure-free, plug-and-play indoor navigation system.
  • Public Bicycle Sharing: Public bike-sharing systems have emerged as a new innovative mobility strategy, and are now common-place in many big cities worldwide. In our project, we are collaborating closely with the world’s largest public bike-sharing operator, building spatio-temporal mobility models, traffic predictions and state-of-the-art bike rebalancing algorithms to optimize the system’s efficiency and customer-satisfaction.





Incentive Networks
Yuezhou Lv, Thomas Moscibroda, in AAAI 2015: 29th AAAI Conference on Artificial Intelligence, Austin, Texas, AAAI - Association for the Advancement of Artificial Intelligence, January 1, 2015, View abstract, Download PDF













List of Publications