Google Scholar page
rvinayak[at]cs.cmu[dot]edu
Gates 9011

News

• Google Faculty Research Award 2018.
• NSF CRII 2018.
• Program committee member for USENIX NSDI 2020.
• Invited talk at ITA 2019.
• Invited attendee at Microsoft Systems Faculty Summit 2018.
• Program committee member for USENIX OSDI 2018.
DART used in Top 5 WSDM 2018 Music Recommendation Challenge winner.
• Program committee member for SysML 2018.
• Joined CMU CS as an assistant professor.
• Received Eli Jury Award 2016 for best thesis in the area of Systems, Communications, Control, or Signal Processing at EECS, UC Berkeley.
• Invited talk at ITA Graduation Day 2016.
• Invited talk at Allerton 2015.
• Awarded Google Anita Borg Memorial Scholarsihp 2015.
• 'Reducing I/O cost in distributed storage codes' at USENIX FAST 2015. Chosen as the best paper of USENIX FAST 2015 by StorageMojo.
I am an Assistant Professor in the Computer Science Department at Carnegie Mellon University, with a courtesy appointment in the ECE department. I lead the TheSys research group at CMU, and also a part of the Parallel Data Lab (PDL). My research interests lie in the broad area of computer and networked systems with a current focus on reliability, availability, scalability, and performance challenges in data storage and caching systems, in systems for machine learning and in live video streaming.

A bulk of my past research has focussed on the storage/caching layer and in part on the application (specifically, machine learning) layer:

  • Storage/caching: My research focus here has been on fault tolerance, scalability, load balancing, and reducing latency in large-scale distributed data storage and caching systems. We designed coding theory based solutions that we showed are provably optimal. We also built systems and evaluated them on Facebook's data-analytics cluster and on Amazon EC2 showing significant benefits over the state-of-the-art. Our solutions are now a part of Apache Hadoop 3.0 and are also being considered by several companies such as NetApp and Cisco.

  • Machine learning: My research focus here has been on the generalization performance of a class of learning algorithms that are widely used for ranking. We designed an algorithm building on top of Multiple Additive Regression Trees, and through empirical evaluation on real-world datasets showed significant improvement over classification, regression, and ranking tasks. The new algorithm that we proposed is now deployed in production in Microsoft's data-analysis toolbox which powers the Azure Machine Learning product.

TheSys (theory + systems) research group


My research group is called "TheSys (Theory + Systems)" since we take a principled and holistic approach towards solving real-world problems considering both theoretical and systems perspectives. We design solutions rooted in fundamental theory as well as build systems that employ the resulting insights and solutions to advance the state-of-the-art.

Here is our group's Github.

I am fortunate to be advising and working with the following amazing students at CMU.

PhD students:
Jack Kosaian
Michael Rudow
Saurabh Kadekodi (co-advised with Prof. Greg Ganger)
Juncheng (Jason) Yang
Francisco Maturana

Devdeep Ray (Prof. Srini Seshan's PhD student)

Masters students:
Jiaan Dai
Jiaqi Zuo
Jiongtao Ye
Sai Kiriti Badam
Xuren Zhou

Undergraduate students:
Eliot Robson (CMU)
Ian Chiu (CMU)


Publications

(On Google Scholar)

Preprints


Conference Papers


Workshop Papers


Journal Papers


* indicates equal contribution

Bio

Rashmi K. Vinayak is an assistant professor in the Computer Science department at Carnegie Mellon University. She recieved her PhD in the EECS department at UC Berkeley in 2016, and was a postdoctoral researcher at AMPLab/RISELab and BLISS. Her dissertation received the Eli Jury Award 2016 from the EECS department at UC Berkeley for outstanding achievement in the area of systems, communications, control, or signal processing. Rashmi is the recipient of the IEEE Data Storage Best Paper and Best Student Paper Awards for the years 2011/2012. She is also a recipient of the Facebook Fellowship 2012-13, the Microsoft Research PhD Fellowship 2013-15, and the Google Anita Borg Memorial Scholarship 2015-16. Her research interests lie broadly in the area of computer and networked systems with a current focus on addressing reliability, availability, scalability, and performance challenges in data-storage-and-analytics systems and live video streaming based on theoretical foundations.