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Keynote talks

Keynote Speakers

Aditya Akella (UT Austin)

Networking and Cloud: A Match Made in Heaven


Over the past few years, networking advances have spurred fundamental transformations in cloud computing. Technologies such as software defined networking, network virtualization, and high-bisection fabrics have simplified cloud design and operation, brought exciting new workloads to the cloud, and helped lower the bar to cloud adoption. Networking is poised to bring even more interesting and fundamental transformations to the cloud over the next few years. In this talk, I will describe several promising networking ideas, spanning high-performance fabrics and network stacks, programmable hardware, abstractions for network automation, and novel inter-domain protocols and services. I will discuss the tantalizing opportunities these ideas offer for cloud computing, and the fundamental new research and practical challenges they introduce. I will conclude my talk with observations on what it would take for our research community to make rapid and meaningful progress in this space.


Aditya Akella is a Regents Chair Professor of Computer Science at UT Austin and a software engineer at Google. Aditya received his B. Tech. from IIT Madras (2000), and PhD from CMU (2005). His research spans computer systems and networking, with a focus on programmable networks, formal methods in systems, and systems for big data and machine learning. His work has influenced the infrastructure of some of the world’s largest online service providers. Aditya has received many awards for his contributions, including being selected as a finalist for the US Blavatnik National Award for Young Scientists (2020 and 2021), UW-Madison “Professor of the Year” award (2019 and 2017), IRTF Applied Networking Research Prize (2015), SIGCOMM Rising Star award (2014), NSF CAREER award (2008), and several best paper awards.

Peter Bailis (Sisu Data)

The Future of Cloud Data: Challenges and Research Opportunities


The last several years have seen the creation of hundreds of billions of dollars in market value – including the largest software IPO of all time – centered around one technology category: cloud data. While cloud data is not new, the rate of adoption across almost every industry and the associated pace of development around all aspects of cloud data (from pipelines to extract-load-transform (ELT) tools to storage and analytics) are unprecedented. In this talk, I’ll present a research-oriented perspective on the future of cloud data that combines my experiences as an academic at Stanford and as a startup founder and CEO at Sisu Data. My goal is to provide an overview of the seismic changes in the cloud data landscape that – in my opinion – have yet to receive sufficient attention from research, and to highlight several tantalizing research opportunities in systems and databases that result.


Peter is the CEO and Founder of Sisu Data. Before Sisu, Peter was an assistant professor of Computer Science at Stanford University, where he maintains an adjunct appointment. Peter received a Ph.D. from UC Berkeley and an A.B. from Harvard College, both in Computer Science.

Ranjita Bhagwan (Microsoft Research)

Leveraging Data to Improve Cloud Services


Today’s cloud services are large, complex, and dynamic, often supporting billions of users. Such a complex and dynamic environment poses several challenges such as ensuring fast and secure development and deployment, and prompt resolution of service disruptions. Nevertheless, new opportunities to address such challenges have emerged. Large-scale services generate petabytes of code, test, and usage-related data within just one day. This data can be harnessed to provide valuable insights to engineers on how to improve service performance, security and reliability. However, cherry-picking important information from such vast amounts of systems-related data proves to be a formidable task. Over the last few years, we have developed many analysis tools that leverage code, test logs and telemetry to address these challenges. In this talk, I will talk about our experience with building such tools, and describe our journey which started with determining the right problems to solve, making research contributions and ended with widespread deployment across Microsoft’s services.


Ranjita Bhagwan is Senior Principal Researcher at Microsoft Research India. She has worked for more than a decade on applying machine learning to improve system reliability, security and performance. Recently, her work has focused on using data-driven approaches to improve cloud services and has led to several publications (including a best paper award at OSDI 2018), as well as several tools that are widely used by Microsoft’s services. She is the recipient of the 2020 ACM India Outstanding Contributions to Computing by a Woman Award and has chaired multiple top conferences in the fields of systems and networking. Ranjita received her PhD and MS in Electrical and Computer Engineering from University of California, San Diego and a BTech in Computer Science and Engineering from the Indian Institute of Technology, Kharagpur.

Krysta Svore (Microsoft)

Accelerating the cloud with quantum


Azure Quantum. The power of Azure, accelerated by Quantum. This is the present and future of cloud computing. A quantum-classical compute fabric that holds the promise of helping to remake our global economy, by offering new capabilities to help solve some of our planet’s biggest challenges—in energy, climate, agriculture, and health—and across a broad span of industrial sectors, including computational chemistry, materials science, and nuclear and particle physics. Quantum computers are accelerators to large-scale classical compute and receive instructions and cues from classical processors. The success of quantum computation requires seamless integration in a high-performance cloud, to enable hyperscale workloads with complex classical pre- and post-processing. It also requires scaling up; to achieve the full promise, we need a leadership-class quantum machine with more than 1M physical qubits. I’ll share the types of problems such a quantum machine will accelerate in the cloud, and how you can program and develop towards these advances today with Azure Quantum. I’ll also share how quantum ideas are being emulated to enhance classical solutions, enabling quantum impact right now. Welcome to the quantum era of computing.


Dr. Krysta Svore is General Manager of Quantum Systems at Microsoft. She believes empowering people with the power of quantum computing, today and tomorrow, will be one of the greatest revolutionary steps in our history. She leads a team dedicated to realizing a commercial-scale quantum computing system and ecosystem to solve today’s unsolvable problems. She spent her early years at Microsoft developing machine-learning methods for web applications, including ranking, classification, and summarization algorithms. In 2018, Dr. Svore was named one of the 39 Most Powerful Women Engineers according to Business Insider. Dr. Svore serves as a member of the Advanced Scientific Computing Advisory Committee of the Department of Energy and as a member of the ISAT Committee of DARPA.  She is an appointee of the National Quantum Initiative Advisory Committee.  She has received an ACM Best of 2013 Notable Article award and was a member of the winning team of the Yahoo! Learning to Rank Challenge in 2010. She chaired the 2017 Quantum Information Processing Conference. Dr. Svore is a Kavli Fellow of the National Academy of Sciences, a Senior Member of the Association for Computing Machinery (ACM), a representative for the Academic Alliance of the National Center for Women and Information Technology (NCWIT), and a member of the American Physical Society (APS). Dr. Svore has authored over 70 papers and has filed over 25 patents. She received her PhD in computer science with highest distinction from Columbia University and her BA from Princeton University in Mathematics with a minor in Computer Science and French.

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